Shuhua-Group/CVETool

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Created about 3 years ago
Updated about 3 years ago

Shuhua-Group/CVETool

Shuhua-Group

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Composite variant expression tool

Chinese-Pangenome-Consortium-Phase-I

ArchaicSeeker2.0

ArchaicSeeker is a series of software for detecting archaic introgression sequences and reconstructing introgression history. The latest version of this series, ArchaicSeeker 2.0, has the following three notable improvements compared with the original version of this software. First, it can automatically determine the boundary of each introgressed sequence. Next, it is capable of tracing both known and unknown ancestral sources of a given introgressed sequence. Finally, it has the ability to reconstruct the introgression history with more sophisticated introgression models.

CPC-graph-based-NGS-pipeline

A graph-based pipeline used to call/genotype snvs/indels/SVs from NGS data

PGGSVpipeline

Y-LineageTracker

A high-throughput analysis framework for Y-chromosomal next-generation sequencing data

Theta_D_H.Est

Calculator for statictics including Theta, D, H, and so on, based on the VCF input.

AdmixSim2

forward-time simulator of population genetic data

Construct-ancestral-genome

PanGenome_VCF_PostProcess

A simple pipeline to process the VCF deconstructed from the VG pangenome graph

HierarchyMix

reconstruct the 4-way complex admixture history

AdmixInfer

Length Distribution of Ancestral Tracks under a General Admixture Model and Its Applications in Population History Inference

TMRCA

time to the most recent common ancestor

ASEkit

A tool applied to detect allelic expression sites

ADMIXTURE.merge

To merge the replicates of ADMIXTURE analysis and provide summary report.

MultiWaver2.0

MultiWaver series software was designed to infer population admixture history in case of various and complex scenarios. The earlier version of MultiWaver considered only the discrete admixture models. In the newly developed version MultiWaver 2.0, we implemented a more flexible framework to automatically select an optimal admixture model among discrete models and continuous models.

SVanalysis_STARProtocols

A protocol for applying low-coverage whole-genome sequencing data in structure variation studies

RNA-Seq

PGG.MHC

MultiWaver

Inference of multiple-wave admixtures by length distribution of ancestral tracks

TJ1

MultiWaverX

Inference on the sex-biased admixture history

NGS.PRSS1-2caller

NGS.PRSS1-2caller is a toolkit for calling genetic variants at PRSS1-PRSS2 locus, which enables detecting SNV, INDEL and CNV with high accuracy and sensitivity.

AdmixSim

Java Version for the AdmixSim: A Forward-Time Simulator for Various and Complex Scenarios of Population Admixture

SC-sample

SC-sample is a computer simulation tool for modeling spatial coalescent with recombination process, which generates ARGs directly consistent with the given sample. It attempts to uniformly select ARG from the sample-consistent ARG space. The algorithm is modified version of SC. -----------Related Publication: BMC Bioinformatics. 15:273. Link:http://www.biomedcentral.com/1471-2105/15/273

CHIP-mutation-calling-NGS-pipeline

This pipeline based on snakemake calls CHIP variants from next-generation whole-exome/genome sequencing of human samples and produces a purely filtered VCF file containing high confident CHIP mutations.

AncestryPainter

AncestryPainter is a graphic program used to illuminate the ancestry compositions of populations and individuals.

SC-Spatial_Coalescent_simulator

SC (Spatial Coalescent simulator) is a computer simulation tool for modeling spatial coalescent with recombination process. The algorithm implemented in SC is an improvement of the Wiuf and Hein algorithm (Wiuf and Hein, 1999). SC is proven to be the only precise ancestral recombination graph (ARG) simulator (Wiuf and Hein’s has some redundant and MaCS misses some information) such as the distribution of ARG generated by SC is identical to that generated by a typical back-in-time model adopted by ms. SC is developed based on Macs-0.4e, all macs options are not changed. Thanks to Gary Chen to provide support.