There are 6 repositories under whole-genome-sequencing topic.
Whole Genome Sequencing analysis, WGS analysis
Pipeline for calling structural variations in whole genomes sequencing Oxford Nanopore data
A handy variant calling pipeline generator for whole-genome sequencing (WGS) and whole exom sequencing data (WES) analysis. 一个简易且全面的 WGS/WES 分析流程生成器.
Detect novel (and reference) STR expansions from short-read data
An R package for performing association analysis of whole-genome/whole-exome sequencing (WGS/WES) studies using STAARpipeline
Whole Exome/Whole Genome Sequencing alignment pipeline
JARVIS: a comprehensive deep learning framework to prioritise non-coding variants in whole genomes
The tutorial for performing association analysis of whole-genome/whole-exome sequencing (WGS/WES) studies using FAVORannotator, STAARpipeline and STAARpipelineSummary
Clinical Whole Genome and Exome Sequencing Pipeline
Assembly of Phylogenomic Datasets from High-Throughput Sequencing data
Workspace for data science projects and NGS pipelines. Contains RStudio, Jupyter Notebook, VSCode and file manager. Can connect to Tailscale network to bypass firewalls.
A complete Snakemake pipeline for detecting allele specific expression in RNA-seq
Bacterial whole genome sequencing (WGS) analysis
An R package for summarizing and visualizing association analysis results of whole-genome/whole-exome sequencing (WGS/WES) studies generated by STAARpipeline
PRAWNS: A fast and scalable bioinformatics tool that generates an efficient pan-genome representation of closely related whole genomes to provide a concise list of genomic features
a SGE, python, implementation of the ENCODE consortium whole genome bisulfite sequencing pipeline.
SARS-CoV-2 analysis pipeline for short-read, paired-end illumina sequencing
Accurate and robust inference of genetic ancestry from cancer-derived molecular data across genomic platforms
A SnakeMake workflow to analyse whole genome bisulfite sequencing data from allopolyploids.
Bioinformatics pipeline to process whole genome resequencing data and perform genotype likelihood based population genomic analyses. Flexible to datasets that combine high/low coverage and historical/fresh samples.