gwaslab 3.2.0

A collection of handy tools for GWAS

A collection of handy python scripts for GWAS. Just want to make life eaiser and save myself from repetitive work.

For usage, please check GWASLab document at https://cloufield.github.io/gwaslab/ .

What you can do with gwaslab:

Standardization, Normalization & Harmonization

• CHR and POS notation standardization

• Variant POS and allele normalization

• Genome build : Liftover

• Reference allele alignment using a reference genome sequence

• rsID assignment based on CHR, POS, REF and ALT

• CHR POS assignment based on rsID using a reference VCF

• Palindromic SNPs and indels strand inference using a reference VCF

• Check allele frequency discrepancy using a reference VCF

Quality control, Value conversion & Filtering

• Statistics sanity check

• Equivalent statistics conversion

  • BETA/SE , OR/OR_95L/OR_95U

  • P, Z, CHISQ, MLOG10

• Extract/exclude hapmap3 variants

• Extract/exclude MHC variants

• Filtering values.

Visualization

• Mqq plot : Manhattan plot and QQ plot side by side

• Heatmap : ldsc-rg genetic correlation matrix

• Scatter Plot : variant effect size comparison with sumstats

• Scatter Plot : allele frequency comparison

Other Utilities

• Read ldsc h2 or rg outputs directly as DataFrames

• Extract lead SNPs given a window size

• Logging : keep a complete record of manipulations from raw data to munged data

• Formating GWAS sumstats in certain formats

  • LDSC / MAGMA / METAL / MR-MEGA / FUMA ...

Requirements

• Python >= 3
• pyVCF >= 0.6.8
• Biopython >= 1.79
• liftover >= 1.1.13
• pandas >= 1.2.4
• numpy >= 1.21.2
• matplotlib>3.5
• seaborn >= 0.11.1
• scipy >= 1.6.2
• adjustText

Install

pip install gwaslab

Current version: 3.0.0

Usage

For usage, please check GWASLab document at https://cloufield.github.io/gwaslab/ .

Update Log

• 3.0.0 first complete version

• 1.0.0 implemented Sumstats object

• 0.0.5 - 0.0.6

• added compare_effect, read_ldsc

• 0.0.4

  • added mqqplot feature
  • fixed gtesig algorithm
  • recreated mplot and qqplot

For more information: https://gwaslab.com/