gwaslab 0.0.6

A collection of handy tools for GWAS

gwaslab

A collection of handy python scripts for GWAS. This package is based on matplotlib and seaborn. Just want to save myself from repetitive work.

What you can do with gwaslab:

1. Side-by-side Manhattan and QQ plot
2. Manhattan plot
3. QQ plot
4. Calculate lamda GC
5. [Select top SNPs based on a given window size.]
6. Convert beta/se <-> OR/95%L_U/95%L_L
7. Select hapmap3 SNPs from sumstats
8. Convert Observed scale heritability to liability scale heritability

Requirements:

1. Python>3 2. "scipy" 3. "numpy" 4. "pandas" 5. "matplotlib" 6. "seaborn"

Install:

pip install gwaslab

Current version: 0.0.4

Usage:

Input: pandas dataframe

Create Manhattan plot and QQ plot with just one line

import gwaslab as gl

## creat qqplot and manhattan plot with just one line
## pass a dataframe in, and specify the column name for chromosome, base pair position, and also the p values.
gl.mqqplot(sumstats,"CHR","POS","PVALUE")

## adjust the plot, select top snps and add annotation sutomatically.
gl.mqqplot(sumstats,"CHR","POS","PVALUE",cut=20,cutfactor=10,anno=True,verbose=True,save=True,title="gwaslab")

## all options
gl.mqqplot(insumstats,
          chrom,
          pos,
          p,
          scaled=False,
          cut=0,
          cutfactor=10,
          cut_line_color="#ebebeb",
          windowsizekb=500,
          anno=None,
          sig_level=5e-8,
          sig_line_color="grey",
          suggestive_sig_level=5e-6,
          title =None,
          mtitle=None,
          qtitle=None,
          figsize =(15,5),
          fontsize = 10,
          colors = ["#000042", "#7878BA"],
          verbose=True,
          repel_force=0.03,
          gc=True,
          save=None,
          saveargs={"dpi":300,"facecolor":"white"}
          )

Or you can plot it separately.

Manhattan plot

gl.mplot()

QQ plot

gl.qqplot()

Calculate genomic inflation factor

gc(insumstats{"PVALUE"},mode="p",level=0.5)
gc(insumstats["Z"],mode="z",level=0.5)
gc(insumstats["chi2"],mode="chi2",level=0.5)

Extract top snps given a sliding window size

gl.getsig(insumstats,id,chrom,pos,p)

gl.getsig(insumstats,id,chrom,pos,p,windowsizekb=500,verbose=True,sig_level=5e-8)

Converting observed scale heritability to liability scale heritability

gl.h2_obs_to_liab(h2_obs, P, K)

gl.h2_obs_to_liab(h2_obs, P, K, se_obs=None)

Ref:

---

Log

• 0.0.4
  • added mqqplot feature
  • fixed gtesig algorithm
  • recreated mplot and qqplot

Next

• beta to OR
• OR to beta

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