Miami plot

Miami Plot

gl.plot_miami2() creates a Miami plot by comparing two GWAS summary statistics. Both inputs must be gl.Sumstats objects - file paths are not supported.

Function signature

gl.plot_miami2(
    path1=None,      # gl.Sumstats object (required) - Sumstats object for top plot
    path2=None,      # gl.Sumstats object (required) - Sumstats object for bottom plot
    ...
)

Input Type Requirement

path1 and path2 must be gl.Sumstats objects
File paths (strings) are not supported
You must load your sumstats files into Sumstats objects first using gl.Sumstats()

Example

#!wget -O ../0_sample_data/bmi_male_bbj.txt.gz http://jenger.riken.jp/2analysisresult_qtl_download/
#!wget -O ../0_sample_data/bmi_female_bbj.txt.gz http://jenger.riken.jp/4analysisresult_qtl_download/

Load gwaslab and sample data

Example

import gwaslab as gl

Example

gl.show_version()

stdout:

2024/12/23 13:00:30 GWASLab v4.0.0 https://cloufield.github.io/gwaslab/
2024/12/23 13:00:30 (C) 2022-2026, Yunye He, Kamatani Lab, GPL-3.0 license, gwaslab@gmail.com

Load sumstats as Sumstats objects

# First, load your sumstats files into Sumstats objects
gl1 = gl.Sumstats("../0_sample_data/bbj_bmi_female.txt.gz",fmt="gwaslab",snpid="SNP",ea="REF",nea="ALT",sep="\t",build="19",verbose=False)
gl2 = gl.Sumstats("../0_sample_data/bbj_bmi_male.txt.gz",fmt="gwaslab",snpid="SNP",ea="REF",nea="ALT",sep="\t",build="19",verbose=False)

Example

gl1.get_lead()

stdout:

2024/12/23 13:00:43 Start to extract lead variants...v4.0.0
2024/12/23 13:00:43  -Current Dataframe shape : 5961600 x 9 ; Memory usage: 328.48 MB
2024/12/23 13:00:43  -Processing 5961600 variants...
2024/12/23 13:00:43  -Significance threshold : 5e-08
2024/12/23 13:00:43  -Sliding window size: 500  kb
2024/12/23 13:00:45  -Using P for extracting lead variants...
2024/12/23 13:00:45  -Found 948 significant variants in total...
2024/12/23 13:00:45  -Identified 20 lead variants!
2024/12/23 13:00:45 Finished extracting lead variants.

SNPID	CHR	POS	EA	NEA	BETA	SE	P	STATUS
rs860295	1	155767708	A	G	0.04005	0.006973	9.221000e-09	1999999
rs532504	1	177878933	G	A	0.06024	0.006294	1.062000e-21	1999999
rs939584	2	621558	C	T	0.05446	0.008828	6.897000e-10	1999999
rs713586	2	25158008	T	C	0.03073	0.005345	9.015000e-09	1999999
rs1846974	5	87969927	G	A	0.02988	0.005307	1.808000e-08	1999999
...	...	...	...	...	...	...	...	...
rs75766425	14	52511911	G	C	0.05405	0.008145	3.222000e-11	1999999
rs11642015	16	53802494	C	T	0.07912	0.006551	1.375000e-33	1999999
rs8098510	18	40773435	A	C	-0.03211	0.005647	1.296000e-08	1999999
rs6567160	18	57829135	T	C	0.05420	0.006344	1.299000e-17	1999999
rs35560038	19	46175046	A	T	-0.05872	0.005473	7.421000e-27	1999999

Most options in plot_mqq() are available for plot_miami2()

Input Requirements

path1: Must be a gl.Sumstats object for the top plot
path2: Must be a gl.Sumstats object for the bottom plot
File paths are not supported - you must load your data into Sumstats objects first

Create Miami plot with Sumstats objects

# Simply add 1 or 2 after the option for plot_mqq() to customize the top or bottom figure in miami plot
# Both path1 and path2 must be Sumstats objects
a = gl.plot_miami2(path1=gl1,
                   path2=gl2,
                   skip=2,
                   cut1=20,
                   cut2=15,
                   anno1=True,
                   anno2="GENENAME",
                   anno_set1=["rs3798519"],
                   pinpoint1=[["rs3798519","rs35560038"],["rs7933262","rs8098510"]],
                   pinpoint_color1=["purple","black"],
                   highlight1=["rs8098510"],
                   highlight2=[["rs8098510","rs3798519"], ["rs1491850"]],
                   highlight_color2=["red","yellow"],
                   verbose1=False,
                   verbose2=False
)

stdout:

2024/12/23 13:00:45 Start to create miami plot v4.0.0:
2024/12/23 13:00:45  -Obtaining Sumstats1 CHR, POS, P and annotation from: ['CHR', 'POS', 'P', 'SNPID']
2024/12/23 13:00:45  -Loading Sumstats1 from gwaslab.Sumstats Object
2024/12/23 13:00:46  -Obtaining Sumstats2 CHR, POS, P and annotation from: ['CHR', 'POS', 'P', 'SNPID']
2024/12/23 13:00:46  -Loading Sumstats2 from gwaslab.Sumstats Object
2024/12/23 13:00:47  -Sanity check after conversion: 0 variants with P value outside of (0,1] will be removed...
2024/12/23 13:00:47  -Sumstats P values are being converted to -log10(P)...
2024/12/23 13:00:48  -Sanity check: 0 na/inf/-inf variants will be removed...
2024/12/23 13:00:49  -Sanity check after conversion: 0 variants with P value outside of (0,1] will be removed...
2024/12/23 13:00:49  -Sumstats P values are being converted to -log10(P)...
2024/12/23 13:00:49  -Sanity check: 0 na/inf/-inf variants will be removed...
2024/12/23 13:00:50  -Merging sumstats using chr and pos...
2024/12/23 13:00:59  -Columns in merged sumstats: P_1,SNPID_1,scaled_P_1,TCHR+POS,P_2,SNPID_2,scaled_P_2,CHR,POS,_ADD,i
2024/12/23 13:00:59 Start to create Manhattan plot for sumstats1...
2024/12/23 13:01:03 Finished creating Manhattan plot for sumstats1
2024/12/23 13:01:03 Start to create Manhattan plot for sumstats2...
2024/12/23 13:01:08 Finished creating Manhattan plot for sumstats2
2024/12/23 13:01:08 Start to save figure...
2024/12/23 13:01:08  -Skip saving figure!
2024/12/23 13:01:08 Finished saving figure...
2024/12/23 13:01:08 Finished creating miami plot successfully

Output image