Javier Castillo-Arnemann October 12, 2018
suppressPackageStartupMessages(library(tidyverse))
library(cowplot)##
## Attaching package: 'cowplot'
## The following object is masked from 'package:ggplot2':
##
## ggsave
dataset <- read.table("data/df_MASTERTABLE.txt", sep = "\t", header = TRUE)
#Order depth factor for plotting
dataset$DEPTH <- factor(dataset$DEPTH, levels = c("MULTI","MES","DCM","MIX", "SRF"))
n_distinct(dataset$SAMPLE) #total number of samples## [1] 299
#Depth vs region
dataset %>%
ggplot(aes(GEOREGION, as.integer(DEPTHM))) +
geom_point() +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
scale_y_reverse()
#Combine LAT LON
dataset$LOC <- paste(dataset$LAT, dataset$LONG, sep = ", ")
#Find how many samples are in every location
dataset %>%
group_by(LOC) %>%
summarize(samples_per_loc = n_distinct(SAMPLE))## # A tibble: 143 x 2
## LOC samples_per_loc
## <chr> <int>
## 1 -0.6625, 73.161 1
## 2 -1.8902, -84.6141 1
## 3 -1.9002, -84.6265 1
## 4 -12.9723, -96.0122 2
## 5 -12.9794, -96.0232 2
## 6 -13.0023, -95.9759 2
## 7 -15.3379, 43.2948 2
## 8 -15.3424, 43.2965 2
## 9 -16.9486, -100.6715 2
## 10 -16.9534, 53.9601 2
## # ... with 133 more rows
#Play around with one sample
cenf <- filter(dataset, SAMPLE == "cenf")
#Check OMZ depths
depths <- filter(dataset, DEPTH_OMZ == "OMZ") %>% select(DEPTHM, DEPTH_OMZ, DEPTH)
#Depth heatmap
dataset %>%
filter(DEPTH_OMZ != "MULTI") %>%
ggplot(aes(LEVEL1, DEPTH)) +
geom_tile(aes(fill = log(RPKM)),
colour = "white") +
scale_fill_gradient(low = "white",
high = "darkblue") +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
labs(x = "Pathway type",
y = "Ocean Layer")
dataset %>%
filter(DEPTH_OMZ != "MULTI") %>%
ggplot(aes(LEVEL2, DEPTH)) +
geom_tile(aes(fill = log(RPKM)),
colour = "white") +
scale_fill_gradient(low = "white",
high = "darkblue") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
#Comparing pathways in different samples
sample1 <- dataset %>%
filter(SAMPLE == "cenf") %>%
mutate(sample_id = as.factor(1))
sample2 <- dataset %>%
filter(SAMPLE == "ERR599337") %>%
mutate(sample_id = as.factor(2))
samples <- rbind(sample1, sample2) %>%
filter(RPKM != 0) %>%
arrange(RPKM)
#Common pathways
intersect(sample1$PWY_NAME, sample2$PWY_NAME)## [1] "PWY-4921"
## [2] "PWY-6943"
## [3] "PWY-82"
## [4] "PWY-7214"
## [5] "PWY-5461"
## [6] "P641-PWY"
## [7] "PWY-7299"
## [8] "PWY-7097"
## [9] "PWY-1001"
## [10] "PWY-7445"
## [11] "PWY0-1338"
## [12] "PWY-6839"
## [13] "LCYSDEG-PWY"
## [14] "PWY-6756"
## [15] "PWY-2361"
## [16] "IDNCAT-PWY"
## [17] "PWY-7307"
## [18] "CRNFORCAT-PWY"
## [19] "PWY-6837"
## [20] "BSUBPOLYAMSYN-PWY"
## [21] "PWY66-378"
## [22] "PWY-5905"
## [23] "PWY-6461"
## [24] "SALVPURINE2-PWY"
## [25] "PWY-7536"
## [26] "PWY-6139"
## [27] "PWY-31"
## [28] "PWY-5886"
## [29] "OXIDATIVEPENT-PWY"
## [30] "PROTOCATECHUATE-ORTHO-CLEAVAGE-PWY"
## [31] "PWY-5837"
## [32] "PWY-7183"
## [33] "PWY-7180"
## [34] "PWY0-981"
## [35] "PWY-7346"
## [36] "ENTNER-DOUDOROFF-PWY"
## [37] "PWY-7292"
## [38] "PWY-5138"
## [39] "PWY-5162"
## [40] "PWY-7179"
## [41] "PWY-5148"
## [42] "PWY-6333"
## [43] "PWY-7344"
## [44] "PWY-7417"
## [45] "THREONINE-DEG2-PWY"
## [46] "MANNCAT-PWY"
## [47] "PWY-6620"
## [48] "PWY-6932"
## [49] "ASPARAGINE-BIOSYNTHESIS"
## [50] "PROUT-PWY"
## [51] "PWY-6543"
## [52] "PWY0-1241"
## [53] "PWY-7308"
## [54] "HISDEG-PWY"
## [55] "PWY-6700"
## [56] "PWY-7338"
## [57] "PWY-7337"
## [58] "PWY-7250"
## [59] "PWY0-1479"
## [60] "CITRULLINE-DEG-PWY"
## [61] "PWY-6703"
## [62] "PWY-6453"
## [63] "PWY-6737"
## [64] "PWY-6609"
## [65] "ASPARTATESYN-PWY"
## [66] "ASPARTATE-DEG1-PWY"
## [67] "THIOREDOX-PWY"
## [68] "PWY-66"
## [69] "PWY0-662"
## [70] "SAM-PWY"
## [71] "PWY-5340"
## [72] "PWY-6708"
## [73] "HOMOSER-THRESYN-PWY"
## [74] "PWY-6614"
## [75] "PWY0-1021"
## [76] "PWY-7206"
## [77] "PWY-5078"
## [78] "PWY-5669"
## [79] "PWY-5046"
## [80] "PWY-735"
## [81] "FASYN-ELONG-PWY"
## [82] "PWY-5137"
## [83] "PWY-7291"
## [84] "DETOX1-PWY"
## [85] "PWY-7205"
## [86] "PWY-5384"
## [87] "PWY-5514"
## [88] "PWY-6613"
## [89] "PWY0-1319"
## [90] "PHESYN"
## [91] "PWY490-4"
## [92] "CYSTSYN-PWY"
## [93] "PANTO-PWY"
## [94] "PWY-6936"
## [95] "PWY-6307"
## [96] "PWY-0"
## [97] "TYRFUMCAT-PWY"
## [98] "PWY-7197"
## [99] "PWY-6164"
## [100] "MALATE-ASPARTATE-SHUTTLE-PWY"
## [101] "PWY-6147"
## [102] "NAGLIPASYN-PWY"
## [103] "DTDPRHAMSYN-PWY"
## [104] "PWY-6788"
## [105] "PWY-7199"
## [106] "PWY-1722"
## [107] "PWY66-368"
## [108] "PPGPPMET-PWY"
## [109] "PWY-5659"
## [110] "PWY-5344"
## [111] "PWY-5921"
## [112] "PWY-6000"
## [113] "PWY66-367"
## [114] "PWY-7112"
## [115] "PWY-7269"
## [116] "PWY-5084"
## [117] "PWY-7533"
## [118] "PWY-2161"
## [119] "PWY-5143"
## [120] "NADPHOS-DEPHOS-PWY"
## [121] "PWY0-1264"
## [122] "HOMOSERSYN-PWY"
## [123] "PWY-5041"
## [124] "PWY-6733"
## [125] "PWY-7176"
## [126] "PWY-5188"
## [127] "PWY66-21"
## [128] "GLYCLEAV-PWY"
## [129] "PWY-5989"
## [130] "PWY-7221"
## [131] "PWY-7220"
## [132] "PWY-7222"
## [133] "TRPSYN-PWY"
## [134] "PWY-5971"
## [135] "PWY-7187"
## [136] "1CMET2-PWY"
## [137] "PWY-6124"
## [138] "PWY-7198"
## [139] "VALSYN-PWY"
## [140] "PWY-7210"
## [141] "PWY66-387"
## [142] "HISTSYN-PWY"
## [143] "GLYOXYLATE-BYPASS"
## [144] "PWY-6122"
## [145] "PWY-6121"
## [146] "PWY-6545"
## [147] "PWY-7184"
## [148] "PWY-5686"
## [149] "PWY-5723"
## [150] "CALVIN-PWY"
## [151] "PWY-7219"
## [152] "PWY-3781"
## [153] "FAO-PWY"
## [154] "TRNA-CHARGING-PWY"
#Common pathways level2
intersect(sample1$LEVEL2, sample2$LEVEL2)## [1] "SECONDARY-METABOLITE-BIOSYNTHESIS"
## [2] "Noncarbon-Nutrients"
## [3] "AROMATIC-COMPOUNDS-DEGRADATION"
## [4] "Nucleosides and Nucleotides Biosynthesis"
## [5] "AMINE-DEG"
## [6] "SECONDARY-METABOLITE-DEGRADATION"
## [7] "CARBOXYLATES-DEG"
## [8] "Detoxification-None"
## [9] "Other-biosynthesis"
## [10] "Alcohol-Degradation"
## [11] "Polyamine-Biosynthesis"
## [12] "HORMONE-SYN"
## [13] "Cofactor-Biosynthesis"
## [14] "Amino-Acid-Biosynthesis"
## [15] "HORMONE-DEG"
## [16] "Carbohydrates-Biosynthesis"
## [17] "Cell-Structure-Biosynthesis"
## [18] "Carbohydrates-Degradation"
## [19] "AROMATIC-COMPOUNDS-BIOSYN"
## [20] "Mercury-Detoxification"
## [21] "Amino-Acid-Degradation"
## [22] "Fatty-Acid-and-Lipid-Biosynthesis"
## [23] "C1-COMPOUNDS"
## [24] "NUCLEO-DEG"
## [25] "Energy-Metabolism-None"
## [26] "Metabolic Regulators Biosynthesis "
## [27] "Other-Degradation"
## [28] "Fatty-Acid-and-Lipid-Degradation"
## [29] "Photosynthesis"
## [30] "Pentose-Phosphate-Cycle"
## [31] "OTHER-ENERGY"
## [32] "Degradation-None"
## [33] "Respiration"
## [34] "Aminoacyl-tRNAs-Charging"
## [35] "GLYCOLYSIS-VARIANTS"
## [36] "Metabolic-Clusters-None"
#common pathways level1
intersect(sample1$LEVEL1, sample2$LEVEL1)## [1] "Biosynthesis" "Energy-Metabolism" "Degradation"
## [4] "Detoxification" "Metabolic-Clusters"
#plot pathway comparison
theme_set(theme_cowplot(font_size=12)) # reduce default font size
level1_p <- samples %>%
ggplot(aes(fct_reorder(LEVEL1, RPKM, .desc = TRUE), as.character(sample_id))) +
geom_tile(aes(fill = log(RPKM)), colour = "white") +
scale_fill_gradient(low = "white", high = "steelblue") +
labs(x = "Pathway", y = "Group") +
theme_classic() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
level2_p <- samples %>%
ggplot(aes(fct_reorder(LEVEL2, RPKM, .desc = TRUE), as.character(sample_id))) +
geom_tile(aes(fill = log(RPKM)), colour = "white") +
scale_fill_gradient(low = "white", high = "steelblue") +
labs(x = "Pathway", y = "Group") +
theme_classic() +
theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 10))
level3_p <- samples %>%
ggplot(aes(fct_reorder(LEVEL3, RPKM, .desc = TRUE), as.character(sample_id))) +
geom_tile(aes(fill = log(RPKM)), colour = "white") +
scale_fill_gradient(low = "white", high = "steelblue") +
labs(x = "Pathway", y = "Group") +
theme_classic() +
theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 5))
level1_p
level2_p
level3_p