global.json

{
    "VERSION": "1.0.1",
    "CONFIG_KEYS": ["Contact Network", "Transmission Network", "Sample Times", "Viral Phylogeny (Transmissions)", "Viral Phylogeny (Seeds)", "Mutation Rates", "Ancestral Sequence", "Sequence Evolution"],
    "DESC": {
        "Contact Network": "The <b style='color:red;'>Contact Network</b> graph model describes all social interactions:<ul><li>Nodes represent individuals in the population</li><li>Edges represent all interactions across which the pathogen can transmit</li><li>Currently, FAVITES-Lite only supports static (i.e., unchanging) contact networks</li></ul>",
        "Transmission Network": "The <b style='color:red;'>Transmission Network</b> compartmental model describes how the pathogen propagates along the contact network. State transition rates are in unit of Poisson process arrivals per time (reciprocal of expected time to next arrival). The user will specify the number of individuals in each compartment, and individuals will be placed into each compartment uniformly.",
        "Sample Times": "The <b style='color:red;'>Sample Times</b> model describes the time(s) at which individuals in the transmission network are sampled (i.e., sequenced).",
        "Viral Phylogeny (Transmissions)": "The <b style='color:red;'>Viral Phylogeny (Transmissions)</b> coalescent model describes the topology and branch lengths (in unit of time) of the viral phylogeny throughout the epidemic, which is constrained by the transmission network.",
        "Viral Phylogeny (Seeds)": "The <b style='color:red;'>Viral Phylogeny (Seeds)</b> phylogenetic model describes the topology and branch lengths (in unit of time) of the viral phylogeny prior to the epidemic (i.e., the viral phylogeny of the seed individuals).",
        "Mutation Rates": "The <b style='color:red;'>Mutation Rates</b> model describes how mutation rates (i.e., mutations/time) are sampled along each branch of the viral time phylogeny.",
        "Ancestral Sequence": "The <b style='color:red;'>Ancestral Sequence</b> model describes how the ancestral (i.e., root) sequence is generated/selected.",
        "Sequence Evolution": "The <b style='color:red;'>Sequence Evolution</b> model describes how sequences evolve down the phylogeny."
    },
    "MODELS": {
        "Contact Network": {
            "Barabasi-Albert (BA)": {
                "PARAM": {
                    "n": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes"
                    },
                    "m": {
                        "TYPE": "positive integer",
                        "DESC": "Number of edges attached from new nodes to existing nodes"
                    }
                },
                "DESC": "The <b><a href='https://en.wikipedia.org/wiki/Barab%C3%A1si%E2%80%93Albert_model' target='_blank'>Barabasi-Albert (BA)</a></b> model is an algorithm for generating undirected random scale-free networks using a preferential attachment mechanism.",
                "CITE": "<ul><li>Albert R, Barabasi AL (2002). \"Statistical mechanics of complex networks.\" <i>Rev Mod Phys</i>. 74(1):47-97. <a href='https://doi.org/10.1103/RevModPhys.74.47' target='_blank'>doi:10.1103/RevModPhys.74.47</a></li><ul>",
                "PROP": [
                    "The total number of edges is: <b style='color:red;'>m</b>(<b style='color:red;'>n</b>-<b style='color:red;'>m</b>)",
                    "The expected degree is approximately: 2<b style='color:red;'>m</b>"
                ]
            },
            "Barbell": {
                "PARAM": {
                    "m1": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes in each of the two complete subgraphs"
                    },
                    "m2": {
                        "TYPE": "non-negative integer",
                        "DESC": "Number of nodes in the path connecting the two complete subgraphs"
                    }
                },
                "DESC": "A <b><a href='https://en.wikipedia.org/wiki/Barbell_graph' target='_blank'>barbell</a></b> graph is an undirected graph composed of two complete graphs, each with <b style='color:red;'>m1</b> nodes, connected by a path of <b style='color:red;'>m2</b> nodes.",
                "CITE": "<ul><li>Ghosh A, Boyd S, Saberi A (2006). \"Minimizing Effective Resistance of a Graph.\" <i>Proc 17th Internat Sympos Math Th Network and Systems</i>. 1185-1196. <a href='https://doi.org/10.1137/050645452' target='_blank'>doi:10.1137/050645452</a></li></ul>",
                "PROP": [
                    "The total number of nodes is: 2<b style='color:red;'>m1</b> + <b style='color:red;'>m2</b>",
                    "The total number of edges is: <b style='color:red;'>m1</b>(<b style='color:red;'>m1</b>-1) + <b style='color:red;'>m2</b> + 1"
                ]
            },
            "Complete": {
                "PARAM": {
                    "n": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes"
                    }
                },
                "DESC": "A <b><a href='https://en.wikipedia.org/wiki/Complete_graph' target='_blank'>complete</a></b> graph is a simple undirected graph in which every pair of distinct vertices is connected by a unique edge.",
                "PROP": [
                    "The total number of edges is: <b style='color:red;'>n</b> choose 2 = <b style='color:red;'>n</b>(<b style='color:red;'>n</b>-1)/2",
                    "The degree of every node (and thus also the average degree) is: <b style='color:red;'>n</b>-1"
                ]
            },
            "Cycle": {
                "PARAM": {
                    "n": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes"
                    }
                },
                "DESC": "A <b><a href='https://en.wikipedia.org/wiki/Cycle_graph' target='_blank'>cycle</a></b> graph is an undirected graph that consists of a single cycle. In other words, the vertices are connected in a closed chain.",
                "PROP": [
                    "When <b style='color:red;'>n</b> > 2, the number of edges is: <b style='color:red;'>n</b>"
                ]
            },
            "Erdos-Renyi (ER)": {
                "PARAM": {
                    "n": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes"
                    },
                    "p": {
                        "TYPE": "probability",
                        "DESC": "Probability of existence of an edge"
                    }
                },
                "DESC": "The <b><a href='https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model' target='_blank'>Erdos-Renyi (ER)</a></b> model is an undirected graph model in which each of the <b style='color:red;'>n</b> choose 2 possible edges have probability <b style='color:red;'>p</b> of existing.",
                "CITE": "<ul><li>Erdos P, Renyi A (1959). \"On Random Graphs. I.\" <i>Publ Math</i>. 6:290-297.</li><li>Gilbert EN (1959). \"Random Graphs.\" <i>Ann Math Stat</i>. 30(4):1141-1144. <a href='https://doi.org/10.1214/aoms/1177706098' target='_blank'>doi:10.1214/aoms/1177706098</a></li></ul>",
                "PROP": [
                    "The expected degree is: <b style='color:red;'>p</b>(<b style='color:red;'>n</b> choose 2) = <b style='color:red;'>pn</b>(<b style='color:red;'>n</b>-1)/2",
                    "The degree distribution is: Binomial(<b style='color:red;'>n</b>-1, k)"
                ]
            },
            "Newman-Watts-Strogatz (NWS)": {
                "PARAM": {
                    "n": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes"
                    },
                    "k": {
                        "TYPE": "even positive integer",
                        "DESC": "Number of nearest neighbors to connect to"
                    },
                    "p": {
                        "TYPE": "probability",
                        "DESC": "Probability of adding a new edge"
                    }
                },
                "DESC": "The <b><a href='https://networkx.org/documentation/stable/reference/generated/networkx.generators.random_graphs.newman_watts_strogatz_graph.html' target='_blank'>Newman-Watts-Strogatz (NWS)</a></b> model is an undirected graph model as follows:<ol><li>Start with a ring of <b style='color:red;'>n</b> nodes</li><li>Connect each node with its <b style='color:red;'>k</b> nearest neighbors</li><li>For each edge (u,v) in the ring, add a new random edge (u,w) with probability <b style='color:red;'>p</b></li></ol>",
                "CITE": "<ul><li>Newman MEJ, Watts DJ (1999). \"Renormalization group analysis of the small-world network model.\" <i>Phys Lett A</i>. 263(4-6):341-346. <a href='https://doi.org/10.1016/S0375-9601(99)00757-4' target='_blank'>doi:10.1016/S0375-9601(99)00757-4</a></li></ul>",
                "PROP": [
                    "The number of edges in the connected ring is: <b style='color:red;'>nk</b>/2",
                    "The number of newly added edges is: Binomial(<b style='color:red;'>nk</b>/2, <b style='color:red;'>p</b>)"
                ]
            },
            "Path": {
                "PARAM": {
                    "n": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes"
                    }
                },
                "DESC": "A <b><a href='https://en.wikipedia.org/wiki/Path_graph' target='_blank'>path</a></b> graph (or linear graph) is an undirected graph whose nodes can be ordered in a line, and there exists an edge between every adjacent pair of nodes.",
                "PROP": [
                    "The number of edges is: <b style='color:red;'>n</b>-1"
                ]
            },
            "Ring Lattice": {
                "PARAM": {
                    "n": {
                        "TYPE": "positive integer",
                        "DESC": "Number of nodes"
                    },
                    "k": {
                        "TYPE": "even positive integer",
                        "DESC": "Number of nearest neighbors to connect to"
                    }
                },
                "DESC": "A <b><a href='https://runestone.academy/ns/books/published/complex/SmallWorldGraphs/RingLattice.html' target='_blank'>ring lattice</a></b> graph is an undirected graph in which every node has an edge to each of its <b style='color:red;'>k</b> nearest neighbors.",
                "PROP": [
                    "The number of edges is: <b style='color:red;'>nk</b>/2"
                ]
            }
        },
        "Transmission Network": {
            "Granich et al. (2008)": {
                "INF_STATES": ["I1", "I2", "I3", "I4", "A1", "A2", "A3", "A4"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_NS": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state NS at the start of the simulation"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_I1": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I1 at the start of the simulation"
                    },
                    "N_I2": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I2 at the start of the simulation"
                    },
                    "N_I3": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I3 at the start of the simulation"
                    },
                    "N_I4": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I4 at the start of the simulation"
                    },
                    "N_A1": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A1 at the start of the simulation"
                    },
                    "N_A2": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A2 at the start of the simulation"
                    },
                    "N_A3": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A3 at the start of the simulation"
                    },
                    "N_A4": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A4 at the start of the simulation"
                    },
                    "N_D": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state D at the start of the simulation"
                    },
                    "R_NS-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate NS → D (nodal)"
                    },
                    "R_NS-S": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate NS → S (nodal)"
                    },
                    "R_S-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → D (nodal)"
                    },
                    "R_S-I1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 (nodal, e.g. outside infection)"
                    },
                    "R_S-I1_I1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in I1"
                    },
                    "R_S-I1_I2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in I2"
                    },
                    "R_S-I1_I3": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in I3"
                    },
                    "R_S-I1_I4": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in I4"
                    },
                    "R_S-I1_A1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in A1"
                    },
                    "R_S-I1_A2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in A2"
                    },
                    "R_S-I1_A3": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in A3"
                    },
                    "R_S-I1_A4": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I1 induced by neighbors in A4"
                    },
                    "R_I1-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I1 → D (nodal)"
                    },
                    "R_I1-I2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I1 → I2 (nodal)"
                    },
                    "R_I1-A1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I1 → A1 (nodal)"
                    },
                    "R_A1-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A1 → D (nodal)"
                    },
                    "R_A1-A2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A1 → A2 (nodal)"
                    },
                    "R_A1-I1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A1 → I1 (nodal)"
                    },
                    "R_I2-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I2 → D (nodal)"
                    },
                    "R_I2-I3": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I2 → I3 (nodal)"
                    },
                    "R_I2-A2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I2 → A2 (nodal)"
                    },
                    "R_A2-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A2 → D (nodal)"
                    },
                    "R_A2-A3": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A2 → A3 (nodal)"
                    },
                    "R_A2-I2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A1 → I2 (nodal)"
                    },
                    "R_I3-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I3 → D (nodal)"
                    },
                    "R_I3-I4": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I3 → I4 (nodal)"
                    },
                    "R_I3-A3": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I3 → A3 (nodal)"
                    },
                    "R_A3-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A3 → D (nodal)"
                    },
                    "R_A3-A4": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A3 → A4 (nodal)"
                    },
                    "R_A3-I3": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A3 → I3 (nodal)"
                    },
                    "R_I4-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I4 → D (nodal)"
                    },
                    "R_I4-A4": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I4 → A4 (nodal)"
                    },
                    "R_A4-D": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A4 → D (nodal)"
                    },
                    "R_A4-I4": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A4 → I4 (nodal)"
                    }
                },
                "DESC": "The <b><a href='https://doi.org/10.1016/S0140-6736(08)61697-9' target='_blank'>Granich <i>et al</i>. (2008)</a></b> model for HIV has 11 states:<ul><li><b>NS:</b> Non-Susceptible</li><li><b>S:</b> Susceptible</li><li><b>I1, I2, I3, and I4:</b> Untreated HIV stage 1, 2, 3, and 4</li><li><b>A1, A2, A3, and A4:</b> ART-treated HIV stage 1, 2, 3, and 4</li><li><b>D:</b> Deceased</li></ul>The following transitions are possible:<ul><li>NS → S (nodal)</li><li>S → I1 (induced by I1-I4/A1-A4 or outside)</li><li>I1 → A1, I2 → A2, I3 → A3, and I4 → A4 (nodal)</li><li>A1 → I1, A2 → I2, A3 → I3, and A4 → I4 (nodal)</li><li>I1 → I2 → I3 → I4 (nodal)</li><li>A1 → A2 → A3 → A4 (nodal)</li><li>All non-D states → D (nodal)</li></ul>",
                "CITE": "<ul><li>Granich RM, Gilks CF, Dye C, De Cock KM, Williams BG (2008). \"Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model.\" <i>The Lancet</i>. 373(9657):48-57. <a href='https://doi.org/10.1016/S0140-6736(08)61697-9' target='_blank'>doi:10.1016/S0140-6736(08)61697-9</a></li></ul>"
            },
            "Hethcote and Yorke (1984)": {
                "INF_STATES": ["MIS", "MIA", "FIS", "FIA"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_MA": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state MA at the start of the simulation"
                    },
                    "N_FA": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state FA at the start of the simulation"
                    },
                    "N_MS": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state MS at the start of the simulation"
                    },
                    "N_FS": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state FS at the start of the simulation"
                    },
                    "N_MIS": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state MIS at the start of the simulation"
                    },
                    "N_FIS": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state FIS at the start of the simulation"
                    },
                    "N_MIA": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state MIA at the start of the simulation"
                    },
                    "N_FIA": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state FIA at the start of the simulation"
                    },
                    "R_MA-MS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MA → MS (nodal)"
                    },
                    "R_MS-MA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MA (nodal)"
                    },
                    "R_MS-MIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIS (nodal, e.g. outside infection)"
                    },
                    "R_MS-MIS_MIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIS induced by neighbors in MIS"
                    },
                    "R_MS-MIS_MIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIS induced by neighbors in MIA"
                    },
                    "R_MS-MIS_FIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIS induced by neighbors in FIS"
                    },
                    "R_MS-MIS_FIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIS induced by neighbors in FIA"
                    },
                    "R_MS-MIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIA (nodal, e.g. outside infection)"
                    },
                    "R_MS-MIA_MIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIA induced by neighbors in MIS"
                    },
                    "R_MS-MIA_MIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIA induced by neighbors in MIA"
                    },
                    "R_MS-MIA_FIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIA induced by neighbors in FIS"
                    },
                    "R_MS-MIA_FIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MS → MIA induced by neighbors in FIA"
                    },
                    "R_MIS-MA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MIS → MA"
                    },
                    "R_MIS-MS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MIS → MS"
                    },
                    "R_MIA-MA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MIA → MA"
                    },
                    "R_MIA-MS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate MIA → MS"
                    },
                    "R_FA-FS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FA → FS (nodal)"
                    },
                    "R_FS-FA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FA (nodal)"
                    },
                    "R_FS-FIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIS (nodal, e.g. outside infection)"
                    },
                    "R_FS-FIS_MIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIS induced by neighbors in MIS"
                    },
                    "R_FS-FIS_MIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIS induced by neighbors in MIA"
                    },
                    "R_FS-FIS_FIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIS induced by neighbors in FIS"
                    },
                    "R_FS-FIS_FIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIS induced by neighbors in FIA"
                    },
                    "R_FS-FIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIA (nodal, e.g. outside infection)"
                    },
                    "R_FS-FIA_MIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIA induced by neighbors in MIS"
                    },
                    "R_FS-FIA_MIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIA induced by neighbors in MIA"
                    },
                    "R_FS-FIA_FIS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIA induced by neighbors in FIS"
                    },
                    "R_FS-FIA_FIA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FS → FIA induced by neighbors in FIA"
                    },
                    "R_FIS-FA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FIS → FA"
                    },
                    "R_FIS-FS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FIS → FS"
                    },
                    "R_FIA-FA": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FIA → FA"
                    },
                    "R_FIA-FS": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate FIA → FS"
                    }
                },
                "REQS": {
                    "Sample Times": "None",
                    "Viral Phylogeny (Transmissions)": "None",
                    "Viral Phylogeny (Seeds)": "None",
                    "Mutation Rates": "None",
                    "Ancestral Sequence": "None",
                    "Sequence Evolution": "None"
                },
                "DESC": "The <b><a href='https://doi.org/10.1007/978-3-662-07544-9' target='_blank'>Hethcote and Yorke (1984)</a></b> model for gonorrhea has 8 states:<ul><li><b>MA and FA:</b> Male/Female Abstinent</li><li><b>MS and FS:</b> Male/Female Susceptible</li><li><b>MIS and FIS:</b> Male/Female Symptomatic Infected</li><li><b>MIA and FIA:</b> Male/Female Asymptomatic Infected</li></ul>The following transitions are possible:<ul><li>MA → MS and FA → FS (nodal)</li><li>MS → MA and FS → FA (nodal)</li><li>MS → MIA and FS → FIA (induced by MIA/MIS/FIA/FIS or outside)</li><li>MS → MIS and FS → FIS (induced by MIA/MIS/FIA/FIS or outside)</li><li>MIA → MS and FIA → FS (nodal)</li><li>MIS → MS and FIS → FS (nodal)</li></ul>Must select \"None\" for all downstream steps.",
                "CITE": "<ul><li>Hethcote HW, Yorke JA (1984). \"Gonorrhea transmission dynamics and control.\" <i>Lect Notes Math</i>. 56. <a href='https://doi.org/10.1007/978-3-662-07544-9' target='_blank'>doi:10.1007/978-3-662-07544-9</a></li></ul>"
            },
            "None": {
                "INF_STATES": [],
                "PARAM": {},
                "REQS": {
                    "Sample Times": "None",
                    "Viral Phylogeny (Transmissions)": "None",
                    "Viral Phylogeny (Seeds)": "None",
                    "Mutation Rates": "None",
                    "Ancestral Sequence": "None",
                    "Sequence Evolution": "None"
                },
                "DESC": "No transmission network is simulated. Must select \"None\" for all downstream steps."
            },
            "SAPHIRE": {
                "INF_STATES": ["E", "P", "I", "A"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_A": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A at the start of the simulation"
                    },
                    "N_P": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state P at the start of the simulation"
                    },
                    "N_H": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state H at the start of the simulation"
                    },
                    "N_I": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I at the start of the simulation"
                    },
                    "N_R": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state R at the start of the simulation"
                    },
                    "N_E": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state E at the start of the simulation"
                    },
                    "R_S-E": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E (nodal, e.g. outside infection)"
                    },
                    "R_S-E_E": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in E"
                    },
                    "R_S-E_P": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in P"
                    },
                    "R_S-E_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in I"
                    },
                    "R_S-E_A": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in A"
                    },
                    "R_E-P": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate E → P (nodal)"
                    },
                    "R_P-A": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate P → A (nodal)"
                    },
                    "R_P-I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate P → I (nodal)"
                    },
                    "R_A-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A → R (nodal)"
                    },
                    "R_I-H": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I → H (nodal)"
                    },
                    "R_I-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I → R (nodal)"
                    },
                    "R_H-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate H → R (nodal)"
                    }
                },
                "DESC": "The <b><a href='https://doi.org/10.1038/s41586-020-2554-8' target='_blank'>SAPHIRE</a></b> model (<a href='https://doi.org/10.1038/s41586-020-2554-8' target='_blank'>Hao <i>et al</i>., Nature 2020</a>) has 7 states:<ul><li><b>S:</b> Susceptible</li><li><b>A:</b> Unascertained Case</li><li><b>P:</b> Presymptomatic Infectious Case</li><li><b>H:</b> Hospitalized Case</li><li><b>I:</b> Ascertained Infectious Case</li><li><b>R:</b> Removed</li><li><b>E:</b> Exposed</li></ul>The following transitions are possible:<ul><li>S → E (induced by E/P/I/A or outside)</li><li>E → P (nodal)</li><li>P → A and P → I (nodal)</li><li>I → H and I → R (nodal)</li><li>A → R (nodal)</li><li>H → R (nodal)</li></ul>",
                "CITE": "<ul><li>Hao X, Cheng S, Wu D, Wu T, Lin X, Wang C (2020). \"Reconstruction of the full transmission dynamics of COVID-19 in Wuhan.\" <i>Nature</i>. 584:420-424. <a href='https://doi.org/10.1038/s41586-020-2554-8' target='_blank'>doi:10.1038/s41586-020-2554-8</a></li></ul>"
            },
            "SAAPPHIIRE": {
                "INF_STATES": ["E", "P1", "P2", "I1", "I2", "A1", "A2"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_A1": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A1 at the start of the simulation"
                    },
                    "N_A2": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A2 at the start of the simulation"
                    },
                    "N_P1": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state P1 at the start of the simulation"
                    },
                    "N_P2": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state P2 at the start of the simulation"
                    },
                    "N_H": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state H at the start of the simulation"
                    },
                    "N_I1": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I1 at the start of the simulation"
                    },
                    "N_I2": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I2 at the start of the simulation"
                    },
                    "N_R": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state R at the start of the simulation"
                    },
                    "N_E": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state E at the start of the simulation"
                    },
                    "R_S-E": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E (nodal, e.g. outside infection)"
                    },
                    "R_S-E_E": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in E"
                    },
                    "R_S-E_P1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in P1"
                    },
                    "R_S-E_P2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in P2"
                    },
                    "R_S-E_I1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in I1"
                    },
                    "R_S-E_I2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in I2"
                    },
                    "R_S-E_A1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in A1"
                    },
                    "R_S-E_A2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in A2"
                    },
                    "R_E-P1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate E → P1 (nodal)"
                    },
                    "R_P1-P2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate P1 → P2 (nodal)"
                    },
                    "R_P2-I1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate P2 → I1 (nodal)"
                    },
                    "R_P2-A1": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate P2 → A1 (nodal)"
                    },
                    "R_I1-I2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I1 → I2 (nodal)"
                    },
                    "R_I1-H": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I1 → H (nodal)"
                    },
                    "R_I2-H": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I2 → H (nodal)"
                    },
                    "R_I2-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I2 → R (nodal)"
                    },
                    "R_A1-A2": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A1 → A2 (nodal)"
                    },
                    "R_A2-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A2 → R (nodal)"
                    },
                    "R_H-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate H → R (nodal)"
                    }
                },
                "DESC": "The <b><a href='https://doi.org/10.1126/science.abp8337' target='_blank'>SAAPPHIIRE</a></b> model (<a href='https://doi.org/10.1126/science.abp8337' target='_blank'>Pekar <i>et al</i>., Science 2022</a>) has 10 states:<ul><li><b>S:</b> Susceptible</li><li><b>A1 and A2:</b> Unascertained Case (Stage 1 and Stage 2)</li><li><b>P1 and P2:</b> Presymptomatic Infectious Case (Stage 1 and Stage 2)</li><li><b>H:</b> Hospitalized Case</li><li><b>I1 and I2:</b> Ascertained Infectious Case (Stage 1 and Stage 2)</li><li><b>R:</b> Removed</li><li><b>E:</b> Exposed</li></ul>The following transitions are possible:<ul><li>S → E (induced by E/P1/P2/I1/I2/A1/A2 or outside)</li><li>E → P1 (nodal)</li><li>P1 → P2 (nodal)</li><li>P2 → A1 and P2 → I1 (nodal)</li><li>I1 → I2 and I1 → H(nodal)</li><li>I2 → H and I2 → R (nodal)</li><li>A1 → A2 (nodal)</li><li>A2 → R (nodal)</li><li>H → R (nodal)</li></ul>",
                "CITE": "<ul><li>Pekar JE, Magee A, Parker E, Moshiri N, Izhikevich K, Havens JL, Gangavarapu K, Malpica Serrano LM, Crits-Christoph A, Matteson NL, Zeller M, Levy JI, Wang JC, Hughes S, Lee J, Park H, Park MS, Ching Zi Yan K, Tzer Pin Lin R, Mat Isa MN, Muhammad Noor Y, Vasylyeva TI, Garry RF, Holmes EC, Rambaut A, Suchard MA, Andersen KG, Worobey M, Wertheim JO (2022). \"The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2.\" <i>Science</i>. 377(6609):960-966. <a href='https://doi.org/10.1126/science.abp8337' target='_blank'>doi:10.1126/science.abp8337</a></li></ul>"
            },
            "Susceptible-Alert-Infected-Susceptible (SAIS)": {
                "INF_STATES": ["I"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_A": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state A at the start of the simulation"
                    },
                    "N_I": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I at the start of the simulation"
                    },
                    "R_S-A": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → A (nodal)"
                    },
                    "R_S-A_A": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → A induced by neighbors in A"
                    },
                    "R_S-A_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → A induced by neighbors in I"
                    },
                    "R_S-I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I (nodal, e.g. outside infection)"
                    },
                    "R_S-I_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I induced by neighbors in I"
                    },
                    "R_A-I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A → I (nodal, e.g. outside infection)"
                    },
                    "R_A-I_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate A → I induced by neighbors in I"
                    },
                    "R_I-S": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I → S (nodal)"
                    }
                },
                "DESC": "The <b><a href='https://doi.org/10.1080/17513758.2011.621452' target='_blank'>Susceptible-Alert-Infected-Susceptible (SAIS)</a></b> model has three states:<ul><li><b>S:</b> Susceptible</li><li><b>A:</b> Alert</li><li><b>I:</b> Infected</li></ul>The following transitions are possible:<ul><li>S → A (nodal or induced by A or I)</li><li>S → I (induced by I or outside)</li><li>A → I (induced by I or outside)</li><li>I → S (nodal)</li></ul>"
            },
            "Susceptible-Exposed-Infected-Removed (SEIR)": {
                "INF_STATES": ["E", "I"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_E": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state E at the start of the simulation"
                    },
                    "N_I": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I at the start of the simulation"
                    },
                    "N_R": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state R at the start of the simulation"
                    },
                    "R_S-E": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E (nodal, e.g. outside infection)"
                    },
                    "R_S-E_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → E induced by neighbors in I"
                    },
                    "R_E-I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate E → I (nodal)"
                    },
                    "R_I-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I → R (nodal)"
                    }
                },
                "DESC": "The <b><a href='https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology#The_SEIR_model' target='_blank'>Susceptible-Exposed-Infected-Removed (SEIR)</a></b> model has four states:<ul><li><b>S:</b> Susceptible</li><li><b>E:</b> Exposed</li><li><b>I:</b> Infected</li><li><b>R:</b> Removed</li></ul>The following transitions are possible:<ul><li>S → E (induced by I or outside)</li><li>E → I (nodal)</li><li>I → R (nodal)</li></ul>"
            },
            "Susceptible-Infected (SI)": {
                "INF_STATES": ["I"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_I": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I at the start of the simulation"
                    },
                    "R_S-I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I (nodal, e.g. outside infection)"
                    },
                    "R_S-I_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I induced by neighbors in I"
                    }
                },
                "DESC": "The <b><a href='https://math.libretexts.org/Bookshelves/Applied_Mathematics/Mathematical_Biology_(Chasnov)/04%3A_Infectious_Disease_Modeling/4.01%3A_The_SI_Model' target='_blank'>Susceptible-Infected (SI)</a></b> model has two states:<ul><li><b>S:</b> Susceptible</li><li><b>I:</b> Infected</li></ul>The following transition is possible:<ul><li>S → I (induced by I or outside)</li></ul>"
            },
            "Susceptible-Infected-Removed (SIR)": {
                "INF_STATES": ["I"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_I": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I at the start of the simulation"
                    },
                    "N_R": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state R at the start of the simulation"
                    },
                    "R_S-I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I (nodal, e.g. outside infection)"
                    },
                    "R_S-I_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I induced by neighbors in I"
                    },
                    "R_I-R": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I → R (nodal)"
                    }
                },
                "DESC": "The <b><a href='https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology#The_SIR_model' target='_blank'>Susceptible-Infected-Removed (SIR)</a></b> model has three states:<ul><li><b>S:</b> Susceptible</li><li><b>I:</b> Infected</li><li><b>R:</b> Removed</li></ul>The following transitions are possible:<ul><li>S → I (induced by I or outside)</li><li>I → R (nodal)</li></ul>"
            },
            "Susceptible-Infected-Susceptible (SIS)": {
                "INF_STATES": ["I"],
                "PARAM": {
                    "duration": {
                        "TYPE": "positive float",
                        "DESC": "The duration of the epidemic"
                    },
                    "N_S": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state S at the start of the simulation"
                    },
                    "N_I": {
                        "TYPE": "non-negative integer",
                        "DESC": "The number of individuals in state I at the start of the simulation"
                    },
                    "R_S-I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I (nodal, e.g. outside infection)"
                    },
                    "R_S-I_I": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate S → I induced by neighbors in I"
                    },
                    "R_I-S": {
                        "TYPE": "non-negative float",
                        "DESC": "The transition rate I → S (nodal)"
                    }
                },
                "DESC": "The <b><a href='https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology#The_SIS_model' target='_blank'>Susceptible-Infected-Susceptible (SIS)</a></b> model has two states:<ul><li><b>S:</b> Susceptible</li><li><b>I:</b> Infected</li></ul>The following transitions are possible:<ul><li>S → I (induced by I or outside)</li><li>I → S (nodal)</li></ul>"
            }
        },
        "Sample Times": {
            "End": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    },
                    "num_samples": {
                        "TYPE": "positive integer",
                        "DESC": "The number of times every individual is sampled"
                    }
                },
                "DESC": "All individuals who are in any of the specified states at the end time of the simulation will be sampled the specified number of times."
            },
            "None": {
                "PARAM": {},
                "REQS": {
                    "Viral Phylogeny (Transmissions)": "None",
                    "Viral Phylogeny (Seeds)": "None",
                    "Mutation Rates": "None",
                    "Ancestral Sequence": "None",
                    "Sequence Evolution": "None"
                },
                "DESC": "No individuals are sampled. Must select \"None\" for all downstream steps."
            },
            "Specific Time": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    },
                    "sample_time": {
                        "TYPE": "positive float",
                        "DESC": "The time at which individuals are sampled"
                    },
                    "num_samples": {
                        "TYPE": "positive integer",
                        "DESC": "The number of times every individual is sampled"
                    }
                },
                "DESC": "All individuals who are in any of the specified states at a specified time will be sampled the specified number of times."
            },
            "State Entry (All)": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    }
                },
                "DESC": "Individuals are sampled every time they enter any of the specified states. Individuals who never enter any of the specified states are never sampled."
            },
            "State Entry (Initial)": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    }
                },
                "DESC": "Individuals are sampled the first time they enter any of the specified states. Individuals who never enter any of the specified states are never sampled."
            },
            "Truncated Exponential": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    },
                    "num_samples": {
                        "TYPE": "positive integer",
                        "DESC": "The number of times every individual is sampled"
                    }
                },
                "DESC": "Each sample time of a given individual is sampled from a \"standardized form\" <b><a href='https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.truncexpon.html' target='_blank'>Truncated Exponential</a></b> distribution of the individual's infection time window. If the individual has multiple time windows, a single time window is chosen randomly with equal probability."
            },
            "Truncated Gamma": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    },
                    "num_samples": {
                        "TYPE": "positive integer",
                        "DESC": "The number of times every individual is sampled"
                    },
                    "k": {
                        "TYPE": "positive float",
                        "DESC": "Shape parameter of the Gamma distribution"
                    },
                    "theta": {
                        "TYPE": "positive float",
                        "DESC": "Scale parameter of the Gamma distribution"
                    }
                },
                "DESC": "Each sample time of a given individual is sampled from a <b style='color:red;'>Truncated Gamma</b> distribution of the individual's time window of specified states. If the individual has multiple time windows, a single time window is chosen randomly with equal probability."
            },
            "Truncated Normal": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    },
                    "num_samples": {
                        "TYPE": "positive integer",
                        "DESC": "The number of times every individual is sampled"
                    },
                    "mu": {
                        "TYPE": "float",
                        "DESC": "Location parameter (i.e., mode) of the Truncated Normal distribution"
                    },
                    "sigma": {
                        "TYPE": "positive float",
                        "DESC": "Scale parameter of the Truncated Normal distribution"
                    }
                },
                "DESC": "Each sample time of a given individual is sampled from a <b><a href='https://en.wikipedia.org/wiki/Truncated_normal_distribution' target='_blank'>Truncated Normal</a></b> distribution of the individual's infection time window. If the individual has multiple time windows, a single time window is chosen randomly with equal probability.",
                "PROP": [
                    "To center the underlying Normal at the center of the [0,1] window: <b style='color:red;'>mu</b> = 0.5",
                    "To center the underlying Normal at the left of the [0,1] window: <b style='color:red;'>mu</b> = 0",
                    "To center the underlying Normal at the right of the [0,1] window: <b style='color:red;'>mu</b> = 1"
                ]
            },
            "Uniform": {
                "PARAM": {
                    "sampled_states": {
                        "TYPE": "comma-separated list",
                        "DESC": "Comma-separated list of states in which individuals are sampled"
                    },
                    "num_samples": {
                        "TYPE": "positive integer",
                        "DESC": "The number of times every individual is sampled"
                    }
                },
                "DESC": "Each sample time of a given individual is sampled from a <b><a href='https://en.wikipedia.org/wiki/Continuous_uniform_distribution' target='_blank'>Uniform</a></b> distribution of the individual's infection time window. If the individual has multiple time windows, a single time window is chosen randomly with equal probability."
            }
        },
        "Viral Phylogeny (Transmissions)": {
            "Constant Effective Population Size": {
                "PARAM": {
                    "N": {
                        "TYPE": "positive float",
                        "DESC": "Effective intra-host viral population size"
                    }
                },
                "DESC": "The effective intra-host viral population size is constant."
            },
            "Infection Time": {
                "PARAM": {},
                "DESC": "Coalescent events occur as early in time as possible."
            },
            "None": {
                "PARAM": {},
                "REQS": {
                    "Viral Phylogeny (Seeds)": "None",
                    "Mutation Rates": "None",
                    "Ancestral Sequence": "None",
                    "Sequence Evolution": "None"
                },
                "DESC": "No phylogeny is simulated. Must select \"None\" for all downstream steps."
            },
            "Transmission Tree": {
                "PARAM": {},
                "DESC": "Coalescent events occur as late in time as possible."
            }
        },
        "Viral Phylogeny (Seeds)": {
            "Coalescent (Neutral)": {
                "PARAM": {
                    "height": {
                        "TYPE": "positive float",
                        "DESC": "Height of the resulting tree"
                    }
                },
                "DESC": "The seed tree is sampled from a <b><a href='https://en.wikipedia.org/wiki/Coalescent_theory' target='_blank'>Neutral Coalescent</a></b> model and is scaled to the specified <b style='color:red;'>height</b>."
            },
            "Dual-Birth": {
                "PARAM": {
                    "r": {
                        "TYPE": "positive float",
                        "DESC": "The ratio lambda_a / lambda_b (i.e., activation rate / birth rate)"
                    },
                    "height": {
                        "TYPE": "positive float",
                        "DESC": "Height of the resulting tree"
                    }
                },
                "DESC": "The seed tree is sampled from a <b><a href='https://doi.org/10.1093/sysbio/syx088' target='_blank'>Dual-Birth</a></b> model (<a href='https://doi.org/10.1093/sysbio/syx088' target='_blank'>Moshiri & Mirarab, Syst Biol 2018</a>) and is scaled to the specified <b style='color:red;'>height</b>.",
                "CITE": "Moshiri N, Mirarab S (2018). \"A Two-State Model of Tree Evolution and Its Applications to <i>Alu</i> Retrotransposition.\" <i>Syst Biol</i>. 67(3):475-489. <a href='https://doi.org/10.1093/sysbio/syx088' target='_blank'>doi:10.1093/sysbio/syx088</a>"
            },
            "Non-Homogeneous Yule": {
                "PARAM": {
                    "rate_func": {
                        "TYPE": "function",
                        "DESC": "The rate function <i>f</i>(<i>t</i>) of the initial Non-Homogeneous Yule tree"
                    },
                    "height": {
                        "TYPE": "positive float",
                        "DESC": "Height of the resulting tree"
                    }
                },
                "DESC": "The seed tree is sampled from a <b style='color:red;'>Non-Homogeneous Yule</b> model with <b style='color:red;'>rate_func</b> <i>f</i>(<i>t</i>) and is scaled to the specified <b style='color:red;'>height</b>.<br><br>Must select \"None\" for all downstream steps.<br><br><b style='color:red;'>WARNING: This plugin uses eval() to execute <i>f</i>(<i>t</i>), which is unsafe!!! Don't use a config file that uses this plugin without verifying!</b>"
            },
            "None": {
                "PARAM": {},
                "REQS": {
                    "Mutation Rates": "None",
                    "Ancestral Sequence": "None",
                    "Sequence Evolution": "None"
                },
                "DESC": "No phylogeny is simulated. Must select \"None\" for all downstream steps."
            },
            "Single Introduction": {
                "PARAM": {},
                "REQS": {},
                "DESC": "Assumes that there is only 1 introduction (and thus 1 transmission chain) in the transmission model, so no seed phylogeny is simulated."
            },
            "Yule": {
                "PARAM": {
                    "height": {
                        "TYPE": "positive float",
                        "DESC": "Height of the resulting tree"
                    }
                },
                "DESC": "The seed tree is sampled from a <b><a href='https://doi.org/10.1098/rstb.1925.0002' target='_blank'>Yule</a></b> model (<a href='https://doi.org/10.1098/rstb.1925.0002' target='_blank'>Yule, Phil Trans Royal Soc London 1925</a>) and is scaled to the specified <b style='color:red;'>height</b>.",
                "CITE": "Yule (1925). \"II.—A mathematical theory of evolution, based on the conclusions of Dr. J. C. Willis, F. R. S.\" <i>Phil Trans Royal Soc London</i>. 213:21-87. <a href='https://doi.org/10.1098/rstb.1925.0002' target='_blank'>doi:10.1098/rstb.1925.0002</a>"
            }
        },
        "Mutation Rates": {
            "Autocorrelated Constant Increment": {
                "PARAM": {
                    "R0": {
                        "TYPE": "positive float",
                        "DESC": "The mutation rate of the root edge"
                    },
                    "R_min": {
                        "TYPE": "positive float",
                        "DESC": "The minimum possible mutation rate"
                    },
                    "R_max": {
                        "TYPE": "positive float",
                        "DESC": "The maximum possible mutation rate"
                    },
                    "delta": {
                        "TYPE": "positive float",
                        "DESC": "The amount a rate can change from parent to child"
                    },
                    "p": {
                        "TYPE": "probability",
                        "DESC": "The probability that a child branch will have a different rate than its parent"
                    }
                },
                "DESC": "Each branch's length is multiplied by one of the following rates:<ul><li>The rate of its parent, with probability 1-<b style='color:red;'>p</b></li><li>The rate of its parent + <b style='color:red;'>delta</b>, with probability <b style='color:red;'>p</b>/2</li><li>The rate of its parent - <b style='color:red;'>delta</b>, with probability <b style='color:red;'>p</b>/2</li><li>The root edge has rate <b style='color:red;'>R0</b></li><li>All rates must be in the range [<b style='color:red;'>R_min</b>, <b style='color:red;'>R_max</b>]</li></ul>",
                "CITE": "Sanderson MJ (1997). \"A Nonparametric Approach to Estimating Divergence Times in the Absence of Rate Constancy.\" <i>Mol Biol Evol</i>. 14(12):1218. <a href='https://doi.org/10.1093/oxfordjournals.molbev.a025731' target='_blank'>doi:10.1093/oxfordjournals.molbev.a025731</a>"
            },
            "Autocorrelated Exponential": {
                "PARAM": {
                    "R0": {
                        "TYPE": "positive float",
                        "DESC": "The mutation rate of the root edge"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from an <b><a href='https://en.wikipedia.org/wiki/Exponential_distribution' target='_blank'>Exponential</a></b> distribution whose mean is the rate of the parent branch.",
                "CITE": "Aris-Brosou S, Yang Z (2002). \"Effects of Models of Rate Evolution on Estimation of Divergence Dates with Special Reference to the Metazoan 18S Ribosomal RNA Phylogeny.\" <i>Syst Biol</i>. 51(5):703-714. <a href='https://doi.org/10.1080/10635150290102375' target='_blank'>doi:10.1080/10635150290102375</a>"
            },
            "Autocorrelated Gamma": {
                "PARAM": {
                    "R0": {
                        "TYPE": "positive float",
                        "DESC": "The mutation rate of the root edge"
                    },
                    "v": {
                        "TYPE": "positive float",
                        "DESC": "Scaling factor of the Gamma distribution's variance"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Gamma_distribution' target='_blank'>Gamma</a></b> distribution whose mean is the rate of the parent branch and whose variance is the branch length multiplied by <b style='color:red;'>v</b>.",
                "CITE": "Aris-Brosou S, Yang Z (2002). \"Effects of Models of Rate Evolution on Estimation of Divergence Dates with Special Reference to the Metazoan 18S Ribosomal RNA Phylogeny.\" <i>Syst Biol</i>. 51(5):703-714. <a href='https://doi.org/10.1080/10635150290102375' target='_blank'>doi:10.1080/10635150290102375</a>"
            },
            "Autocorrelated Log-Normal": {
                "PARAM": {
                    "R0": {
                        "TYPE": "positive float",
                        "DESC": "The mutation rate of the root edge"
                    },
                    "v": {
                        "TYPE": "positive float",
                        "DESC": "Scaling factor of the Log-Normal distribution's variance"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Log-normal_distribution' target='_blank'>Log-Normal</a></b> distribution whose mean is the rate of the parent branch and whose variance is the branch length multiplied by <b style='color:red;'>v</b>.",
                "CITE": "Aris-Brosou S, Yang Z (2002). \"Effects of Models of Rate Evolution on Estimation of Divergence Dates with Special Reference to the Metazoan 18S Ribosomal RNA Phylogeny.\" <i>Syst Biol</i>. 51(5):703-714. <a href='https://doi.org/10.1080/10635150290102375' target='_blank'>doi:10.1080/10635150290102375</a>"
            },
            "Chi-Squared": {
                "PARAM": {
                    "k": {
                        "TYPE": "positive integer",
                        "DESC": "Degrees of freedom of the Chi-Squared distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Chi-squared_distribution' target='_blank'>Chi-Squared</a></b> distribution with <b style='color:red;'>k</b> degrees of freedom."
            },
            "Constant": {
                "PARAM": {
                    "rate": {
                        "TYPE": "positive float",
                        "DESC": "The constant mutation rate"
                    }
                },
                "DESC": "Each branch's length is multiplied by a constant rate."
            },
            "Exponential": {
                "PARAM": {
                    "beta": {
                        "TYPE": "positive float",
                        "DESC": "Scale parameter of the Exponential distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from an <b><a href='https://en.wikipedia.org/wiki/Exponential_distribution' target='_blank'>Exponential</a></b> distribution with scale parameter <b style='color:red;'>beta</b>."
            },
            "F": {
                "PARAM": {
                    "d1": {
                        "TYPE": "positive integer",
                        "DESC": "Degrees of freedom in the F distribution's numerator"
                    },
                    "d2": {
                        "TYPE": "positive integer",
                        "DESC": "Degrees of freedom in the F distribution's denominator"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from an <b><a href='https://en.wikipedia.org/wiki/F-distribution' target='_blank'>F</a></b> distribution with degrees of freedom parameters <b style='color:red;'>d1</b> and <b style='color:red;'>d2</b>."
            },
            "Gamma": {
                "PARAM": {
                    "k": {
                        "TYPE": "positive float",
                        "DESC": "Shape parameter of the Gamma distribution"
                    },
                    "theta": {
                        "TYPE": "positive float",
                        "DESC": "Scale parameter of the Gamma distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Gamma_distribution' target='_blank'>Gamma</a></b> distribution with shape parameter <b style='color:red;'>k</b> and scale parameter <b style='color:red;'>theta</b>."
            },
            "Inverse Gaussian (Wald)": {
                "PARAM": {
                    "mu": {
                        "TYPE": "positive float",
                        "DESC": "Mean of the Inverse Gaussian (Wald) distribution"
                    },
                    "lambda": {
                        "TYPE": "positive float",
                        "DESC": "Shape parameter of the Inverse Gaussian (Wald) distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from an <b><a href='https://en.wikipedia.org/wiki/Inverse_Gaussian_distribution' target='_blank'>Inverse Gaussian (Wald)</a></b> distribution with mean <b style='color:red;'>mu</b> and shape parameter <b style='color:red;'>lambda</b>."
            },
            "Log-Normal": {
                "PARAM": {
                    "mu": {
                        "TYPE": "positive float",
                        "DESC": "Mean of the underlying Normal distribution"
                    },
                    "sigma": {
                        "TYPE": "positive float",
                        "DESC": "Standard deviation of the underlying Normal distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Log-normal_distribution' target='_blank'>Log-Normal</a></b> distribution with mean <b style='color:red;'>mu</b> and standard deviation <b style='color:red;'>sigma</b>."
            },
            "Noncentral Chi-Squared": {
                "PARAM": {
                    "k": {
                        "TYPE": "positive integer",
                        "DESC": "Degrees of freedom of the Noncentral Chi-Squared distribution"
                    },
                    "lambda": {
                        "TYPE": "positive float",
                        "DESC": "Non-centrality parameter of the Noncentral Chi-Squared distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Noncentral_chi-squared_distribution' target='_blank'>Noncentral Chi-Squared</a></b> distribution with <b style='color:red;'>k</b> degrees of freedom and non-centrality parameter <b style='color:red;'>lambda</b>."
            },
            "Noncentral F": {
                "PARAM": {
                    "d1": {
                        "TYPE": "positive integer",
                        "DESC": "Degrees of freedom in the Noncentral F distribution's numerator"
                    },
                    "d2": {
                        "TYPE": "positive integer",
                        "DESC": "Degrees of freedom in the Noncentral F distribution's denominator"
                    },
                    "lambda": {
                        "TYPE": "positive float",
                        "DESC": "Non-centrality parameter of the Noncentral F distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Noncentral_F-distribution' target='_blank'>Noncentral F</a></b> distribution with degrees of freedom parameters <b style='color:red;'>d1</b> and <b style='color:red;'>d2</b>, and with non-centrality parameter <b style='color:red;'>lambda</b>."
            },
            "None": {
                "PARAM": {},
                "REQS": {
                    "Ancestral Sequence": "None",
                    "Sequence Evolution": "None"
                },
                "DESC": "No mutation rates are sampled (i.e., no mutation tree is output). Must select \"None\" for all downstream steps."
            },
            "Pareto": {
                "PARAM": {
                    "alpha": {
                        "TYPE": "positive float",
                        "DESC": "Shape parameter of the Pareto distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Pareto_distribution' target='_blank'>Pareto</a></b> distribution with shape parameter <b style='color:red;'>alpha</b>."
            },
            "Power": {
                "PARAM": {
                    "c": {
                        "TYPE": "positive float",
                        "DESC": "Shape parameter of the Power distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://numpy.org/doc/stable/reference/random/generated/numpy.random.power.html' target='_blank'>Power</a></b> distribution with shape parameter <b style='color:red;'>c</b>."
            },
            "Rayleigh": {
                "PARAM": {
                    "sigma": {
                        "TYPE": "positive float",
                        "DESC": "Scale parameter of the Rayleigh distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Rayleigh_distribution' target='_blank'>Rayleigh</a></b> distribution with scale parameter <b style='color:red;'>sigma</b>."
            },
            "Triangular": {
                "PARAM": {
                    "a": {
                        "TYPE": "positive float",
                        "DESC": "Lower-limit of the Triangular distribution"
                    },
                    "b": {
                        "TYPE": "positive float",
                        "DESC": "Upper-limit of the Triangular distribution"
                    },
                    "c": {
                        "TYPE": "positive float",
                        "DESC": "Mode of the Triangular distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Triangular_distribution' target='_blank'>Triangular</a></b> distribution with lower-limit <b style='color:red;'>a</b>, upper-limit <b style='color:red;'>b</b>, and mode <b style='color:red;'>c</b>."
            },
            "Truncated Normal": {
                "PARAM": {
                    "mu": {
                        "TYPE": "positive float",
                        "DESC": "Location parameter of the Truncated Normal distribution"
                    },
                    "sigma": {
                        "TYPE": "positive float",
                        "DESC": "Scale parameter of the Truncated Normal distribution"
                    },
                    "a": {
                        "TYPE": "positive float",
                        "DESC": "Minimum of the Truncated Normal distribution"
                    },
                    "b": {
                        "TYPE": "positive float",
                        "DESC": "Maximum of the Truncated Normal distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Truncated_normal_distribution' target='_blank'>Truncated Normal</a></b> distribution with location parameter <b style='color:red;'>mu</b>, scale parameter <b style='color:red;'>sigma</b>, minimum <b style='color:red;'>a</b>, and maximum <b style='color:red;'>b</b>."
            },
            "Uniform": {
                "PARAM": {
                    "a": {
                        "TYPE": "positive float",
                        "DESC": "Minimum of the Uniform distribution"
                    },
                    "b": {
                        "TYPE": "positive float",
                        "DESC": "Maximum of the Uniform distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Continuous_uniform_distribution' target='_blank'>Uniform</a></b> distribution with minimum <b style='color:red;'>a</b> and maximum <b style='color:red;'>b</b>."
            },
            "Weibull": {
                "PARAM": {
                    "shape": {
                        "TYPE": "positive float",
                        "DESC": "Shape parameter of the Weibull distribution"
                    },
                    "scale": {
                        "TYPE": "positive float",
                        "DESC": "Scale parameter of the Weibull distribution"
                    }
                },
                "DESC": "Each branch's length is multiplied by a rate that is sampled from a <b><a href='https://en.wikipedia.org/wiki/Weibull_distribution' target='_blank'>Weibull</a></b> distribution with shape parameter <b style='color:red;'>shape</b> and scale parameter <b style='color:red;'>scale</b>."
            }
        },
        "Ancestral Sequence": {
            "Exact Base Frequencies": {
                "PARAM": {
                    "k": {
                        "TYPE": "positive integer",
                        "DESC": "Length of ancestral sequence"
                    },
                    "p_A": {
                        "TYPE": "probability",
                        "DESC": "Frequency of A"
                    },
                    "p_C": {
                        "TYPE": "probability",
                        "DESC": "Frequency of C"
                    },
                    "p_G": {
                        "TYPE": "probability",
                        "DESC": "Frequency of G"
                    },
                    "p_T": {
                        "TYPE": "probability",
                        "DESC": "Frequency of T"
                    }
                },
                "DESC": "The ancestral sequence is randomly generated with the exact user-provided base frequencies (as proportions)."
            },
            "Base Probabilities": {
                "PARAM": {
                    "k": {
                        "TYPE": "positive integer",
                        "DESC": "Length of ancestral sequence"
                    },
                    "p_A": {
                        "TYPE": "probability",
                        "DESC": "Probability of A"
                    },
                    "p_C": {
                        "TYPE": "probability",
                        "DESC": "Probability of C"
                    },
                    "p_G": {
                        "TYPE": "probability",
                        "DESC": "Probability of G"
                    },
                    "p_T": {
                        "TYPE": "probability",
                        "DESC": "Probability of T"
                    }
                },
                "DESC": "Each letter of the ancestral sequence is randomly selected according to the user-provided base probabilities."
            },
            "None": {
                "PARAM": {},
                "REQS": {
                    "Sequence Evolution": "None"
                },
                "DESC": "No ancestral sequence is simulated. Must select \"None\" for all downstream steps."
            }
        },
        "Sequence Evolution": {
            "General Time-Reversible (GTR)": {
                "PARAM": {
                    "p_A": {
                        "TYPE": "probability",
                        "DESC": "Frequency of A"
                    },
                    "p_C": {
                        "TYPE": "probability",
                        "DESC": "Frequency of C"
                    },
                    "p_G": {
                        "TYPE": "probability",
                        "DESC": "Frequency of G"
                    },
                    "p_T": {
                        "TYPE": "probability",
                        "DESC": "Frequency of T"
                    },
                    "r_A-C": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and C"
                    },
                    "r_A-G": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and G"
                    },
                    "r_A-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and T"
                    },
                    "r_C-G": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between C and G"
                    },
                    "r_C-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between C and T"
                    },
                    "r_G-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between G and T"
                    },
                    "prop_invariable": {
                        "TYPE": "probability",
                        "DESC": "Proportion of invariable sites"
                    }
                },
                "DESC": "Sequences evolve according to a <b><a href='https://en.wikipedia.org/wiki/Models_of_DNA_evolution#GTR_model_(Tavar%C3%A9_1986)' target='_blank'>General Time-Reversible (GTR)</a></b> substitution model.",
                "CITE": "Tavaré S (1986). \"Some Probabilistic and Statistical Problems in the Analysis of DNA Sequences.\" <i>Lect Math Life Sci</i>. 17:57–86."
            },
            "General Time-Reversible (GTR) + Codon": {
                "PARAM": {
                    "p_A": {
                        "TYPE": "probability",
                        "DESC": "Frequency of A"
                    },
                    "p_C": {
                        "TYPE": "probability",
                        "DESC": "Frequency of C"
                    },
                    "p_G": {
                        "TYPE": "probability",
                        "DESC": "Frequency of G"
                    },
                    "p_T": {
                        "TYPE": "probability",
                        "DESC": "Frequency of T"
                    },
                    "r_A-C": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and C"
                    },
                    "r_A-G": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and G"
                    },
                    "r_A-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and T"
                    },
                    "r_C-G": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between C and G"
                    },
                    "r_C-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between C and T"
                    },
                    "r_G-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between G and T"
                    },
                    "r_site1": {
                        "TYPE": "non-negative float",
                        "DESC": "Relative rate of substitution at codon site 1"
                    },
                    "r_site2": {
                        "TYPE": "non-negative float",
                        "DESC": "Relative rate of substitution at codon site 2"
                    },
                    "r_site3": {
                        "TYPE": "non-negative float",
                        "DESC": "Relative rate of substitution at codon site 3"
                    }
                },
                "DESC": "Sequences evolve according to a <b><a href='https://en.wikipedia.org/wiki/Models_of_DNA_evolution#GTR_model_(Tavar%C3%A9_1986)' target='_blank'>General Time-Reversible (GTR)</a></b> substitution model with <b style='color:red;'>codon</b>-specific rate heterogeneity.",
                "CITE": "Tavaré S (1986). \"Some Probabilistic and Statistical Problems in the Analysis of DNA Sequences.\" <i>Lect Math Life Sci</i>. 17:57–86."
            },
            "General Time-Reversible (GTR) + Gamma": {
                "PARAM": {
                    "p_A": {
                        "TYPE": "probability",
                        "DESC": "Frequency of A"
                    },
                    "p_C": {
                        "TYPE": "probability",
                        "DESC": "Frequency of C"
                    },
                    "p_G": {
                        "TYPE": "probability",
                        "DESC": "Frequency of G"
                    },
                    "p_T": {
                        "TYPE": "probability",
                        "DESC": "Frequency of T"
                    },
                    "r_A-C": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and C"
                    },
                    "r_A-G": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and G"
                    },
                    "r_A-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between A and T"
                    },
                    "r_C-G": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between C and G"
                    },
                    "r_C-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between C and T"
                    },
                    "r_G-T": {
                        "TYPE": "non-negative float",
                        "DESC": "Transition rate between G and T"
                    },
                    "alpha": {
                        "TYPE": "positive float",
                        "DESC": "Shape parameter of Gamma model of rate heterogeneity"
                    },
                    "num_cats": {
                        "TYPE": "non-negative integer",
                        "DESC": "Number of categories in discrete Gamma model (or 0 for continuous)"
                    },
                    "prop_invariable": {
                        "TYPE": "probability",
                        "DESC": "Proportion of invariable sites"
                    }
                },
                "DESC": "Sequences evolve according to a <b><a href='https://en.wikipedia.org/wiki/Models_of_DNA_evolution#GTR_model_(Tavar%C3%A9_1986)' target='_blank'>General Time-Reversible (GTR)</a></b> substitution model with <b style='color:red;'>Gamma</b>-distributed rate heterogeneity.",
                "CITE": "Tavaré S (1986). \"Some Probabilistic and Statistical Problems in the Analysis of DNA Sequences.\" <i>Lect Math Life Sci</i>. 17:57–86."
            },
            "None": {
                "PARAM": {},
                "DESC": "No sequences are simulated."
            }
        }
    }
}