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szhan committed Jun 19, 2024
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# lshmm
This is a Python library for prototyping and testing implementations of algorithms using the Li & Stephens (2003) HMM.
**lshmm** is a Python library for prototyping, experimenting, and testing implementations of algorithms using the Li & Stephens (2003) Hidden Markov Model.

## Usage

### Inputs
Reference panel contains sample and/or (partial) ancestral haplotypes.
#### Data
* Sample and/or ancestral haplotypes comprising a reference panel.
* Query haplotypes.

### Demo
Forwards algorithm
Backwards algorithm
In the haploid mode, the alleles in haplotypes can be represented by any integer value (besides `-1` and `-2`, which are special values). In the diploid mode, the genotypes (encoded as allele dosages) can be `0` (homozygous for the reference allele), `1` (heterozygous for the alternative allele), or `2` (homozygous for the alternative allele). Currently, multiallelic sites are supported only in the haploid mode, but not the diploid mode.

Note that there are two special values `NONCOPY` and `MISSING`. `NONCOPY` (or `-2`) represent non-copiable states, and can only be found in partial ancestral haplotypes in the reference panel. `MISSING` (or `-1`) representing missing data, and can be found only in query haplotypes.

#### Parameters
* Per-site recombination probabilities.
* Per-site mutation probabilities.

### Algorithms
Viterbi algorithm
Log-likelihood evaluation of a copying path

### Features
* Scaling of mutation rate by the number of distinct alleles per site.
* Non-copiable allelic state in the reference panel (`NONCOPY`).
* Missing allelic state in the query (`MISSING`).
* Non-copiable state in the reference panel (`NONCOPY`).
* Missing state in the query (`MISSING`).
* Multiallelic sites.

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