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keithmp's Projects

ancestry_pipeline icon ancestry_pipeline

Provides helper scripts for inferring local ancestry, performing ancestry-specific PCA, etc

angsd icon angsd

Program for analysing NGS data.

biomi609spring2022 icon biomi609spring2022

This repository contains curricular material, lecture notes, labs, assignments, exams, code, solutions from the Spring 2022 version of BIOMI 609 Computational Genomics and Bioinformatics offered at San Diego State University.

dadi_pipeline icon dadi_pipeline

An accessible and flexible tool for fitting demographic models with dadi, using custom or published models for one to three populations.

deepvariant icon deepvariant

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

dsuite icon dsuite

Fast calculation of Paterson's D (ABBA-BABA) and the f4-ratio statistics across many populations/species

easysfs icon easysfs

Effective selection of population size projection for construction of the site frequency spectrum. Convert VCF to dadi/fastsimcoal style SFS for demographic analysis

ejaghamcoptodon icon ejaghamcoptodon

Scripts used for the paper "Speciation in sympatry with ongoing secondary gene flow and an olfactory trigger in a radiation of Cameroon cichlids".

embopopgen2017 icon embopopgen2017

EMBO Practical Course: Population Genomics: background and tools

fastp icon fastp

An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting...)

grenepipe icon grenepipe

Snakemake pipeline for variant calling from raw sequences

ic_selection icon ic_selection

Code for model selection via five information criteria: Akaike's information criterion (AIC), the corrected AIC for finite length observations (AICc), Bayesian information criterion (BIC), two-stage Minimum Description Length (MDL) and normalized Minimum Description Length (nMDL). The dictionaries are the Frequency (Fourier) dictionary and the Frequency + Spike dictionary. Model selection is performed with Orthogonal Matching Pursuit or the simple Threshold method.

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