WGS的在遗传病检测中的临床应用专家共识已经发布一段时间了，但如果只是用WGS来分析SNV、CNV、SV和mtDNA变异就有点太吃亏了，WGS可分析挖掘的内容是在太多了，本人从github上随意找了些，列举如下：
代码语言：javascript复制Inference of ploidy and heterozygosity structure using whole genome sequencing data
https://github.com/KamilSJaron/smudgeplot
STR
https://github.com/tfwillems/HipSTR
https://github.com/gymreklab/GangSTR
https://github.com/mgymrek/lobstr-code
HLA
https://github.com/DiltheyLab/HLA-LA
https://github.com/FRED-2/OptiType
https://github.com/warrenlr/HLAminer
fetal trisomies and smaller CNV
https://github.com/VUmcCGP/wisecondor
Somatic copy number analysis
https://github.com/cancerit/ascatNgs
Complex structural variant detection
https://github.com/SUwonglab/arcsv
uses Read Pair and Split Read methods to identify structural variants in paired-end WGS data
https://github.com/njdbickhart/RAPTR-SV
detection of copy number variants (CNVs) on human genomes from next generation sequence data, utilizing information from read depth of short reads and SNV heterozygosity.
https://github.com/igm-team/ERDS
Estimating tumor fraction in cell-free DNA from ultra-low-pass whole genome sequencing.
https://github.com/broadinstitute/ichorCNA
analysis of structural variation in genomes
https://github.com/nhansen/SVanalyzer
Analysis of subclonal copy number alterations (CNA) and loss of heterozygosity (LOH) in cancer
https://github.com/gavinha/TitanCNA
Allele-Specific Quantification of Structural Variations in Cancer Genomes
https://github.com/ma-compbio/Weaver
fast and accurate SNP genotyping from whole genome sequencing data for bedside diagnostics
https://github.com/medvedevgroup/vargeno
A bioinformatics pipeline to analyze mtDNA from NGS data
https://github.com/mitoNGS/MToolBox
calculating telomere length
https://github.com/zd1/telseq
Functions and methods for working with VCFs in the ploidyverse
https://github.com/ploidyverse/ploidyverseVcf
Deconvolving tumor purity and ploidy by integrating copy number alterations and loss of heterozygosity
https://github.com/uci-cbcl/PyLOH注：以上分析工具绝大部分用于科研，不保证用于临床的稳定性与准确性。
本人再给几个WGS的建议：
1. PCR free建库，保证在基因组分布的均一性。
2. Trio WGS模式测序，先证者测50x or higher，父母可根据经济条件选择性地降低测序深度（测20-30x？）或者不测。
3. insert size理论值应在300左右，保证最大限度获取有效reads。
4. WGS有可能因为测序的不均一性，存在在部分编码区测序深度不足的情况，导致分析SNV时出现假阴性的情况。
