Input and output sumstats¶

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import gwaslab as gl
import gwaslab as gl

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gl.show_version()
gl.show_version()

2024/12/20 12:45:28 GWASLab v3.5.4 https://cloufield.github.io/gwaslab/
2024/12/20 12:45:28 (C) 2022-2024, Yunye He, Kamatani Lab, MIT License, gwaslab@gmail.com

Input¶

Loading data¶

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mysumstats = gl.Sumstats("../0_sample_data/t2d_bbj.txt.gz",
             snpid="SNP",
             chrom="CHR",
             pos="POS",
             ea="ALT",
             nea="REF",
             neaf="Frq",
             beta="BETA",
             se="SE",
             p="P",
             direction="Dir",
             build="19",
             n="N", verbose=False)

# select just 1000 variants for example
mysumstats.random_variants(n=1000, inplace=True, random_state=123,verbose=False)

# basic_check
mysumstats.basic_check(verbose=False)
mysumstats = gl.Sumstats("../0_sample_data/t2d_bbj.txt.gz",
             snpid="SNP",
             chrom="CHR",
             pos="POS",
             ea="ALT",
             nea="REF",
             neaf="Frq",
             beta="BETA",
             se="SE",
             p="P",
             direction="Dir",
             build="19",
             n="N", verbose=False)

# select just 1000 variants for example
mysumstats.random_variants(n=1000, inplace=True, random_state=123,verbose=False)

# basic_check
mysumstats.basic_check(verbose=False)

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mysumstats.data
mysumstats.data

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	SNPID	CHR	POS	EA	NEA	EAF	BETA	SE	P	N	DIRECTION	STATUS
0	1:2005486_C_T	1	2005486	C	T	0.9863	-0.0969	0.0471	0.039820	191764	+---	1960099
1	1:2247939_AAGG_A	1	2247939	AAGG	A	0.9966	0.0330	0.1249	0.791900	191764	++--	1960399
2	1:3741853_G_A	1	3741853	G	A	0.8849	-0.0375	0.0142	0.008282	191764	----	1960099
3	1:5017526_G_A	1	5017526	G	A	0.9822	0.0126	0.0373	0.736200	191764	+-++	1960099
4	1:5843475_C_T	1	5843475	C	T	0.9857	-0.0011	0.0433	0.980100	191764	--++	1960099
...	...	...	...	...	...	...	...	...	...	...	...	...
995	X:139318378_A_G	23	139318378	G	A	0.5252	-0.0132	0.0071	0.061670	191764	+---	1960099
996	X:144540038_G_T	23	144540038	G	T	0.9866	0.0379	0.0363	0.295800	191764	++++	1960099
997	X:145299627_C_T	23	145299627	C	T	0.9984	-0.0663	0.1671	0.691400	191764	---+	1960099
998	X:146441317_G_A	23	146441317	G	A	0.7345	0.0037	0.0078	0.635100	191764	++-+	1960099
999	X:152025052_A_G	23	152025052	G	A	0.2417	0.0041	0.0082	0.622200	191764	-++-	1960099

1000 rows × 12 columns

Load and filtering by pattern¶

Load and filtering by snp pattern¶

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mysumstats_snp2 = gl.Sumstats("../0_sample_data/t2d_bbj.txt.gz",fmt="auto",
             snpid_pat="^2:123",
             build="19",
             n="N", verbose=True)
mysumstats_snp2.data
mysumstats_snp2 = gl.Sumstats("../0_sample_data/t2d_bbj.txt.gz",fmt="auto",
             snpid_pat="^2:123",
             build="19",
             n="N", verbose=True)
mysumstats_snp2.data

2024/12/20 12:45:56 GWASLab v3.5.4 https://cloufield.github.io/gwaslab/
2024/12/20 12:45:56 (C) 2022-2024, Yunye He, Kamatani Lab, MIT License, gwaslab@gmail.com
2024/12/20 12:45:56 Start to load format from formatbook....
2024/12/20 12:45:56  -auto format meta info:
2024/12/20 12:45:56   - format_name  : auto
2024/12/20 12:45:56   - format_separator  : \t
2024/12/20 12:45:56   - format_na  : #NA
2024/12/20 12:45:56   - format_version  :  20230328
2024/12/20 12:45:56   - Auto-detection mode. Note: auto-detection assumes A1=EA; Alt=EA and Frq=EAF...
2024/12/20 12:45:56   - Header conversion source: https://github.com/Cloufield/formatbook/blob/main/formats/auto.json
2024/12/20 12:45:56 Start to initialize gl.Sumstats from file :../0_sample_data/t2d_bbj.txt.gz
2024/12/20 12:45:56  -Columns used to filter variants: SNP
2024/12/20 12:45:56  -Loading only variants with pattern :  ^2:123 ...
2024/12/20 12:46:09  -Loaded 5722 variants with pattern : ^2:123 ...
2024/12/20 12:46:09  -Reading columns          : BETA,POS,ALT,SNP,N,REF,CHR,Frq,P,SE
2024/12/20 12:46:09  -Renaming columns to      : BETA,POS,EA,SNPID,N,NEA,CHR,EAF,P,SE
2024/12/20 12:46:09  -Current Dataframe shape : 5722  x  10
2024/12/20 12:46:09  -Initiating a status column: STATUS ...
2024/12/20 12:46:09  -Genomic coordinates are based on GRCh37/hg19...
2024/12/20 12:46:10 Start to reorder the columns...v3.5.4
2024/12/20 12:46:10  -Current Dataframe shape : 5722 x 11 ; Memory usage: 21.90 MB
2024/12/20 12:46:10  -Reordering columns to    : SNPID,CHR,POS,EA,NEA,EAF,BETA,SE,P,N,STATUS
2024/12/20 12:46:10 Finished reordering the columns.
2024/12/20 12:46:10  -Column  : SNPID  CHR    POS   EA       NEA      EAF     BETA    SE      P       N     STATUS  
2024/12/20 12:46:10  -DType   : object string int64 category category float64 float64 float64 float64 int64 category
2024/12/20 12:46:10  -Verified: T      F      T     T        T        T       T       T       T       T     T       
2024/12/20 12:46:10  #WARNING! Columns with possibly incompatible dtypes: CHR
2024/12/20 12:46:10  -Current Dataframe memory usage: 21.90 MB
2024/12/20 12:46:10 Finished loading data successfully!

Out[5]:

	SNPID	CHR	POS	EA	NEA	EAF	BETA	SE	P	N	STATUS
967172	2:12320_AAT_A	2	12320	AAT	A	0.0572	-0.0158	0.0294	0.5907	191764	1999999
967173	2:12371_G_C	2	12371	G	C	0.0350	-0.0190	0.0294	0.5179	191764	1999999
967529	2:123233_G_A	2	123233	G	A	0.8736	0.0191	0.0135	0.1561	191764	1999999
967530	2:123332_C_G	2	123332	G	C	0.1264	-0.0191	0.0135	0.1561	191764	1999999
967531	2:123554_C_A	2	123554	C	A	0.4748	0.0115	0.0088	0.1929	191764	1999999
...	...	...	...	...	...	...	...	...	...	...	...
1490418	2:123998245_G_A	2	123998245	G	A	0.1047	-0.0101	0.0144	0.4834	191764	1999999
1490419	2:123998250_T_C	2	123998250	C	T	0.8355	0.0099	0.0119	0.4062	191764	1999999
1490420	2:123998340_A_G	2	123998340	G	A	0.9566	-0.0082	0.0222	0.7132	191764	1999999
1490421	2:123999824_A_G	2	123999824	G	A	0.8953	0.0103	0.0144	0.4760	191764	1999999
1490422	2:123999965_G_A	2	123999965	G	A	0.0021	-0.1152	0.1654	0.4861	191764	1999999

5722 rows × 11 columns

Load and filtering by chr pattern¶

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mysumstats_chr22 = gl.Sumstats("../0_sample_data/t2d_bbj.txt.gz",fmt="auto",
             chrom_pat="^22",
             build="19",
             n="N", verbose=True)
mysumstats_chr22.data
mysumstats_chr22 = gl.Sumstats("../0_sample_data/t2d_bbj.txt.gz",fmt="auto",
             chrom_pat="^22",
             build="19",
             n="N", verbose=True)
mysumstats_chr22.data

2024/12/20 12:46:10 GWASLab v3.5.4 https://cloufield.github.io/gwaslab/
2024/12/20 12:46:10 (C) 2022-2024, Yunye He, Kamatani Lab, MIT License, gwaslab@gmail.com
2024/12/20 12:46:10 Start to load format from formatbook....
2024/12/20 12:46:10  -auto format meta info:
2024/12/20 12:46:10   - format_name  : auto
2024/12/20 12:46:10   - format_separator  : \t
2024/12/20 12:46:10   - format_na  : #NA
2024/12/20 12:46:10   - format_version  :  20230328
2024/12/20 12:46:10   - Auto-detection mode. Note: auto-detection assumes A1=EA; Alt=EA and Frq=EAF...
2024/12/20 12:46:10   - Header conversion source: https://github.com/Cloufield/formatbook/blob/main/formats/auto.json
2024/12/20 12:46:10 Start to initialize gl.Sumstats from file :../0_sample_data/t2d_bbj.txt.gz
2024/12/20 12:46:10  -Columns used to filter variants: CHR
2024/12/20 12:46:10  -Loading only variants on chromosome with pattern : ^22 ...
2024/12/20 12:46:22  -Loaded 157050 variants on chromosome with pattern :^22 ...
2024/12/20 12:46:22  -Reading columns          : BETA,POS,ALT,SNP,N,REF,CHR,Frq,P,SE
2024/12/20 12:46:22  -Renaming columns to      : BETA,POS,EA,SNPID,N,NEA,CHR,EAF,P,SE
2024/12/20 12:46:22  -Current Dataframe shape : 157050  x  10
2024/12/20 12:46:22  -Initiating a status column: STATUS ...
2024/12/20 12:46:22  -Genomic coordinates are based on GRCh37/hg19...
2024/12/20 12:46:23 Start to reorder the columns...v3.5.4
2024/12/20 12:46:23  -Current Dataframe shape : 157050 x 11 ; Memory usage: 33.55 MB
2024/12/20 12:46:23  -Reordering columns to    : SNPID,CHR,POS,EA,NEA,EAF,BETA,SE,P,N,STATUS
2024/12/20 12:46:23 Finished reordering the columns.
2024/12/20 12:46:23  -Column  : SNPID  CHR    POS   EA       NEA      EAF     BETA    SE      P       N     STATUS  
2024/12/20 12:46:23  -DType   : object string int64 category category float64 float64 float64 float64 int64 category
2024/12/20 12:46:23  -Verified: T      F      T     T        T        T       T       T       T       T     T       
2024/12/20 12:46:23  #WARNING! Columns with possibly incompatible dtypes: CHR
2024/12/20 12:46:23  -Current Dataframe memory usage: 33.55 MB
2024/12/20 12:46:23 Finished loading data successfully!

Out[6]:

	SNPID	CHR	POS	EA	NEA	EAF	BETA	SE	P	N	STATUS
12071920	22:16847963_A_G	22	16847963	G	A	0.5903	0.0115	0.0163	0.4819	166718	1999999
12071921	22:16848015_C_G	22	16848015	G	C	0.6942	0.0110	0.0155	0.4795	166718	1999999
12071922	22:16848470_A_G	22	16848470	G	A	0.5918	0.0118	0.0156	0.4487	166718	1999999
12071923	22:16848520_A_T	22	16848520	T	A	0.5918	0.0116	0.0155	0.4537	166718	1999999
12071924	22:16849105_A_G	22	16849105	G	A	0.5919	0.0109	0.0154	0.4810	166718	1999999
...	...	...	...	...	...	...	...	...	...	...	...
12228965	22:51230048_T_C	22	51230048	C	T	0.9988	-0.0645	0.2269	0.7762	166718	1999999
12228966	22:51230086_A_T	22	51230086	T	A	0.9906	-0.0543	0.0766	0.4780	166718	1999999
12228967	22:51237069_T_C	22	51237069	C	T	0.9883	-0.0356	0.0720	0.6212	191764	1999999
12228968	22:51239678_G_T	22	51239678	G	T	0.0592	-0.0038	0.0331	0.9077	166718	1999999
12228969	22:51239752_G_A	22	51239752	G	A	0.0013	0.2937	0.2318	0.2051	166718	1999999

157050 rows × 11 columns

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Output¶

general output¶

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mysumstats.to_format("./mysumstats",fmt="gwaslab",xymt_number=True)
mysumstats.to_format("./mysumstats",fmt="gwaslab",xymt_number=True)

2024/12/20 12:46:23 Start to convert the output sumstats in:  gwaslab  format
2024/12/20 12:46:23  -Formatting statistics ...
2024/12/20 12:46:23  -Float statistics formats:
2024/12/20 12:46:23   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:23   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:23  -Start outputting sumstats in gwaslab format...
2024/12/20 12:46:23  -gwaslab format will be loaded...
2024/12/20 12:46:23  -gwaslab format meta info:
2024/12/20 12:46:23   - format_name  : gwaslab
2024/12/20 12:46:23   - format_source  : https://cloufield.github.io/gwaslab/
2024/12/20 12:46:23   - format_version  : 20231220_v4
2024/12/20 12:46:23  -Output path: ./mysumstats.gwaslab.tsv.gz
2024/12/20 12:46:23  -Output columns: SNPID,CHR,POS,EA,NEA,EAF,BETA,SE,P,N,DIRECTION,STATUS
2024/12/20 12:46:23  -Writing sumstats to: ./mysumstats.gwaslab.tsv.gz...
2024/12/20 12:46:23   -Fast to csv mode...
2024/12/20 12:46:23  -Saving log file to: ./mysumstats.gwaslab.log
2024/12/20 12:46:23 Finished outputting successfully!

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!zcat mysumstats.gwaslab.tsv.gz | head
!zcat mysumstats.gwaslab.tsv.gz | head

SNPID	CHR	POS	EA	NEA	EAF	BETA	SE	P	N	DIRECTION	STATUS
1:2005486_C_T	1	2005486	C	T	0.9863	-0.0969	0.0471	3.9820e-02	191764	+---	1960099
1:2247939_AAGG_A	1	2247939	AAGG	A	0.9966	0.0330	0.1249	7.9190e-01	191764	++--	1960399
1:3741853_G_A	1	3741853	G	A	0.8849	-0.0375	0.0142	8.2820e-03	191764	----	1960099
1:5017526_G_A	1	5017526	G	A	0.9822	0.0126	0.0373	7.3620e-01	191764	+-++	1960099
1:5843475_C_T	1	5843475	C	T	0.9857	-0.0011	0.0433	9.8010e-01	191764	--++	1960099
1:9405103_T_C	1	9405103	C	T	0.0021	-0.0729	0.1516	6.3050e-01	191764	+---	1960099
1:9443411_G_A	1	9443411	G	A	0.9916	0.0362	0.0532	4.9690e-01	191764	+-++	1960099
1:12866348_G_C	1	12866348	G	C	0.9728	-0.0352	0.0431	4.1450e-01	191764	---+	1960099
1:14466316_A_G	1	14466316	G	A	0.6942	-0.0042	0.0096	6.6360e-01	191764	--+-	1960099

gzip: stdout: Broken pipe

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!zcat mysumstats.gwaslab.tsv.gz | tail
!zcat mysumstats.gwaslab.tsv.gz | tail

X:121023171_A_ACTT	23	121023171	ACTT	A	0.5117	0.0096	0.0071	1.7390e-01	191764	++++	1960399
X:134838698_C_CTA	23	134838698	C	CTA	0.9355	0.0060	0.0145	6.8080e-01	191764	++-+	1960399
X:135939006_G_T	23	135939006	G	T	0.2068	-0.0037	0.0085	6.6300e-01	191764	-+-+	1960099
X:136020644_C_T	23	136020644	C	T	0.8756	0.0103	0.0106	3.3370e-01	191764	+++-	1960099
X:138148816_C_T	23	138148816	C	T	0.7842	0.0089	0.0088	3.1330e-01	191764	++++	1960099
X:139318378_A_G	23	139318378	G	A	0.5252	-0.0132	0.0071	6.1670e-02	191764	+---	1960099
X:144540038_G_T	23	144540038	G	T	0.9866	0.0379	0.0363	2.9580e-01	191764	++++	1960099
X:145299627_C_T	23	145299627	C	T	0.9984	-0.0663	0.1671	6.9140e-01	191764	---+	1960099
X:146441317_G_A	23	146441317	G	A	0.7345	0.0037	0.0078	6.3510e-01	191764	++-+	1960099
X:152025052_A_G	23	152025052	G	A	0.2417	0.0041	0.0082	6.2220e-01	191764	-++-	1960099

output each chromosome to a single file¶

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mysumstats.to_format("./mysumstats.@",fmt="gwaslab",xymt_number=True)
mysumstats.to_format("./mysumstats.@",fmt="gwaslab",xymt_number=True)

2024/12/20 12:46:23 Start to convert the output sumstats in:  gwaslab  format
2024/12/20 12:46:23  -Formatting statistics ...
2024/12/20 12:46:23  -Float statistics formats:
2024/12/20 12:46:23   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:23   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:23  -Start outputting sumstats in gwaslab format...
2024/12/20 12:46:23  -gwaslab format will be loaded...
2024/12/20 12:46:23  -gwaslab format meta info:
2024/12/20 12:46:23   - format_name  : gwaslab
2024/12/20 12:46:23   - format_source  : https://cloufield.github.io/gwaslab/
2024/12/20 12:46:23   - format_version  : 20231220_v4
2024/12/20 12:46:23  -Output path: ./mysumstats.@.gwaslab.tsv.gz
2024/12/20 12:46:23  -Output columns: SNPID,CHR,POS,EA,NEA,EAF,BETA,SE,P,N,DIRECTION,STATUS
2024/12/20 12:46:23  -Writing sumstats to: ./mysumstats.@.gwaslab.tsv.gz...
2024/12/20 12:46:23   -Fast to csv mode...
2024/12/20 12:46:23   -@ detected: writing each chromosome to a single file...
2024/12/20 12:46:23   -Chromosomes:['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23']...
2024/12/20 12:46:24  -Saving log file to: ./mysumstats.@.gwaslab.log
2024/12/20 12:46:24 Finished outputting successfully!

load sumstats for each chromosome¶

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mysumstats = gl.Sumstats("./mysumstats.@.gwaslab.tsv.gz",
             fmt="gwaslab", verbose=True)
mysumstats = gl.Sumstats("./mysumstats.@.gwaslab.tsv.gz",
             fmt="gwaslab", verbose=True)

2024/12/20 12:46:24 GWASLab v3.5.4 https://cloufield.github.io/gwaslab/
2024/12/20 12:46:24 (C) 2022-2024, Yunye He, Kamatani Lab, MIT License, gwaslab@gmail.com
2024/12/20 12:46:24 Start to load format from formatbook....
2024/12/20 12:46:24  -gwaslab format meta info:
2024/12/20 12:46:24   - format_name  : gwaslab
2024/12/20 12:46:24   - format_source  : https://cloufield.github.io/gwaslab/
2024/12/20 12:46:24   - format_version  : 20231220_v4
2024/12/20 12:46:24  -Detected @ in path: load sumstats by each chromosome...
2024/12/20 12:46:24  -Chromosomes detected: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23
2024/12/20 12:46:24 Start to initialize gl.Sumstats from files with pattern :./mysumstats.@.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.1.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.2.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.3.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.4.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.5.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.6.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.7.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.8.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.9.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.10.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.11.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.12.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.13.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.14.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.15.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.16.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.17.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.18.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.19.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.20.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.21.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.22.gwaslab.tsv.gz
2024/12/20 12:46:24  -Loading:./mysumstats.23.gwaslab.tsv.gz
2024/12/20 12:46:24  -Merging sumstats for chromosomes: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23
2024/12/20 12:46:24  -Reading columns          : BETA,SNPID,POS,EAF,N,CHR,NEA,P,EA,STATUS,SE,DIRECTION
2024/12/20 12:46:24  -Renaming columns to      : BETA,SNPID,POS,EAF,N,CHR,NEA,P,EA,STATUS,SE,DIRECTION
2024/12/20 12:46:24  -Current Dataframe shape : 1000  x  12
2024/12/20 12:46:24  -Initiating a status column: STATUS ...
2024/12/20 12:46:24  #WARNING! Version of genomic coordinates is unknown...
2024/12/20 12:46:24 Start to reorder the columns...v3.5.4
2024/12/20 12:46:24  -Current Dataframe shape : 1000 x 12 ; Memory usage: 21.54 MB
2024/12/20 12:46:24  -Reordering columns to    : SNPID,CHR,POS,EA,NEA,EAF,BETA,SE,P,N,DIRECTION,STATUS
2024/12/20 12:46:24 Finished reordering the columns.
2024/12/20 12:46:24  -Column  : SNPID  CHR    POS   EA       NEA      EAF     BETA    SE      P       N     DIRECTION STATUS  
2024/12/20 12:46:24  -DType   : object string int64 category category float64 float64 float64 float64 int64 object    category
2024/12/20 12:46:24  -Verified: T      F      T     T        T        T       T       T       T       T     T         T       
2024/12/20 12:46:24  #WARNING! Columns with possibly incompatible dtypes: CHR
2024/12/20 12:46:24  -Current Dataframe memory usage: 21.54 MB
2024/12/20 12:46:24 Finished loading data successfully!

Check available formats¶

List the formats that GWASLab supports

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gl.list_formats()
gl.list_formats()

2024/12/20 12:46:24 Available formats: auto,bolt_lmm,cojo,fastgwa,gwascatalog,gwascatalog_hm,gwaslab,ldsc,metal,mrmega,mtag,pgscatalog,pgscatalog_hm,pheweb,plink,plink2,plink2_firth,plink2_linear,plink2_logistic,plink_assoc,plink_bim,plink_dosage,plink_fam,plink_fisher,plink_linear,plink_logistic,plink_psam,plink_pvar,popcorn,regenie,regenie_gene,saige,ssf,template,vcf

Check the contents of the specified format

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gl.check_format("ssf")
gl.check_format("ssf")

2024/12/20 12:46:24 Available formats:2024/12/20 12:46:24 meta_data2024/12/20 12:46:24 format_dict2024/12/20 12:46:24 
2024/12/20 12:46:24 {'format_name': 'ssf', 'format_source': 'https://www.biorxiv.org/content/10.1101/2022.07.15.500230v1.full', 'format_cite_name': 'GWAS-SSF v0.1', 'format_separator': '\t', 'format_na': '#NA', 'format_comment': None, 'format_col_order': ['chromosome', 'base_pair_location', 'effect_allele', 'other_allele', 'beta', 'odds_ratio', 'hazard_ratio', 'standard_error', 'effect_allele_frequency', 'p_value', 'neg_log_10_p_value', 'ci_upper', 'ci_lower', 'rsid', 'variant_id', 'info', 'ref_allele', 'n'], 'format_version': 20230328}2024/12/20 12:46:24 {'variant_id': 'SNPID', 'rsid': 'rsID', 'chromosome': 'CHR', 'base_pair_location': 'POS', 'other_allele': 'NEA', 'effect_allele': 'EA', 'effect_allele_frequency': 'EAF', 'n': 'N', 'beta': 'BETA', 'standard_error': 'SE', 'p_value': 'P', 'neg_log_10_p_value': 'MLOG10P', 'info': 'INFO', 'odds_ratio': 'OR', 'hazard_ratio': 'HR', 'ci_lower': 'OR_95L', 'ci_upper': 'OR_95U'}

Formatting and saving¶

get ready for submission to gwas catalog (GWAS-ssf format)¶

fmt: specify the output format
ssfmeta: if True, output the meta file
md5sum: if True, create a file with the md5sum of the output sumstats

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mysumstats.to_format("./mysumstats", fmt="ssf", ssfmeta=True, md5sum=True)
mysumstats.to_format("./mysumstats", fmt="ssf", ssfmeta=True, md5sum=True)

2024/12/20 12:46:24 Start to convert the output sumstats in:  ssf  format
2024/12/20 12:46:24  -Formatting statistics ...
2024/12/20 12:46:24  -Float statistics formats:
2024/12/20 12:46:24   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:24   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:24  -Replacing SNPID separator from ":" to "_"...
2024/12/20 12:46:24  -Start outputting sumstats in ssf format...
2024/12/20 12:46:24  -ssf format will be loaded...
2024/12/20 12:46:24  -ssf format meta info:
2024/12/20 12:46:24   - format_name  : ssf
2024/12/20 12:46:24   - format_source  : https://www.biorxiv.org/content/10.1101/2022.07.15.500230v1.full
2024/12/20 12:46:24   - format_cite_name  : GWAS-SSF v0.1
2024/12/20 12:46:24   - format_separator  : \t
2024/12/20 12:46:24   - format_na  : #NA
2024/12/20 12:46:24   - format_col_order  : chromosome,base_pair_location,effect_allele,other_allele,beta,odds_ratio,hazard_ratio,standard_error,effect_allele_frequency,p_value,neg_log_10_p_value,ci_upper,ci_lower,rsid,variant_id,info,ref_allele,n
2024/12/20 12:46:24   - format_version  :  20230328
2024/12/20 12:46:24  -gwaslab to ssf format dictionary:
2024/12/20 12:46:24   - gwaslab keys: SNPID,rsID,CHR,POS,NEA,EA,EAF,N,BETA,SE,P,MLOG10P,INFO,OR,HR,OR_95L,OR_95U
2024/12/20 12:46:24   - ssf values: variant_id,rsid,chromosome,base_pair_location,other_allele,effect_allele,effect_allele_frequency,n,beta,standard_error,p_value,neg_log_10_p_value,info,odds_ratio,hazard_ratio,ci_lower,ci_upper
2024/12/20 12:46:24  -Output path: ./mysumstats.ssf.tsv.gz
2024/12/20 12:46:24  -Output columns: chromosome,base_pair_location,effect_allele,other_allele,beta,standard_error,effect_allele_frequency,p_value,variant_id,n
2024/12/20 12:46:24  -Writing sumstats to: ./mysumstats.ssf.tsv.gz...
2024/12/20 12:46:24   -Fast to csv mode...
2024/12/20 12:46:24  -md5sum hashing for the file: ./mysumstats.ssf.tsv.gz
2024/12/20 12:46:24  -md5sum path: ./mysumstats.ssf.tsv.gz.md5sum
2024/12/20 12:46:24  -md5sum: 26a0577baadfee588c6bcf695295e483
2024/12/20 12:46:24  -Exporting SSF-style meta data to ./mysumstats.ssf.tsv.gz.ssf.tsv-meta.yaml
2024/12/20 12:46:24  -Saving log file to: ./mysumstats.ssf.log
2024/12/20 12:46:24 Finished outputting successfully!

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!zcat mysumstats.ssf.tsv.gz | head
!zcat mysumstats.ssf.tsv.gz | head

chromosome	base_pair_location	effect_allele	other_allele	beta	standard_error	effect_allele_frequency	p_value	variant_id	n
1	2005486	C	T	-0.0969	0.0471	0.9863	3.9820e-02	1_2005486_C_T	191764
1	2247939	AAGG	A	0.0330	0.1249	0.9966	7.9190e-01	1_2247939_AAGG_A	191764
1	3741853	G	A	-0.0375	0.0142	0.8849	8.2820e-03	1_3741853_G_A	191764
1	5017526	G	A	0.0126	0.0373	0.9822	7.3620e-01	1_5017526_G_A	191764
1	5843475	C	T	-0.0011	0.0433	0.9857	9.8010e-01	1_5843475_C_T	191764
1	9405103	C	T	-0.0729	0.1516	0.0021	6.3050e-01	1_9405103_T_C	191764
1	9443411	G	A	0.0362	0.0532	0.9916	4.9690e-01	1_9443411_G_A	191764
1	12866348	G	C	-0.0352	0.0431	0.9728	4.1450e-01	1_12866348_G_C	191764
1	14466316	G	A	-0.0042	0.0096	0.6942	6.6360e-01	1_14466316_A_G	191764

gzip: stdout: Broken pipe

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!head mysumstats.ssf.tsv.gz.md5sum
!head mysumstats.ssf.tsv.gz.md5sum

26a0577baadfee588c6bcf695295e483

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!head ./mysumstats.ssf.tsv-meta.ymal
!head ./mysumstats.ssf.tsv-meta.ymal

head: cannot open './mysumstats.ssf.tsv-meta.ymal' for reading: No such file or directory

ldsc default format¶

hapmap3: if True, only output hapmap3 SNPs
exclude_hla: if True, exclude variants in HLA region from output

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mysumstats.to_format("./mysumstats",fmt="ldsc",hapmap3=True,exclude_hla=True,build="19")
mysumstats.to_format("./mysumstats",fmt="ldsc",hapmap3=True,exclude_hla=True,build="19")

2024/12/20 12:46:25 Start to convert the output sumstats in:  ldsc  format
2024/12/20 12:46:25  -Excluded 3 variants in HLA region (chr6: 25000000-34000000 )...
2024/12/20 12:46:25 Start to extract HapMap3 SNPs...v3.5.4
2024/12/20 12:46:25  -Current Dataframe shape : 997 x 12 ; Memory usage: 21.55 MB
2024/12/20 12:46:25  -Loading Hapmap3 variants from built-in datasets...
2024/12/20 12:46:25  -Since rsID not in sumstats, CHR:POS( build 19) will be used for matching...
2024/12/20 12:46:26  -Checking if alleles are same...
2024/12/20 12:46:26  -Variants with macthed alleles: 81
2024/12/20 12:46:26  -Raw input contains 81 Hapmap3 variants based on CHR:POS...
2024/12/20 12:46:26 Finished extracting HapMap3 SNPs.
2024/12/20 12:46:26  -Extract 81 variants in Hapmap3 datasets for build 19.
2024/12/20 12:46:26  -Formatting statistics ...
2024/12/20 12:46:26  -Float statistics formats:
2024/12/20 12:46:26   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:26   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:26  -Start outputting sumstats in ldsc format...
2024/12/20 12:46:26  -ldsc format will be loaded...
2024/12/20 12:46:26  -ldsc format meta info:
2024/12/20 12:46:26   - format_name  : ldsc
2024/12/20 12:46:26   - format_source  : https://github.com/bulik/ldsc/wiki/Summary-Statistics-File-Format
2024/12/20 12:46:26   - format_source2  : https://github.com/bulik/ldsc/blob/master/munge_sumstats.py
2024/12/20 12:46:26   - format_version  :  20150306
2024/12/20 12:46:26  -gwaslab to ldsc format dictionary:
2024/12/20 12:46:26   - gwaslab keys: rsID,NEA,EA,EAF,N,BETA,P,Z,INFO,OR,CHR,POS
2024/12/20 12:46:26   - ldsc values: SNP,A2,A1,Frq,N,Beta,P,Z,INFO,OR,CHR,POS
2024/12/20 12:46:26  -Output path: ./mysumstats.hapmap3.noMHC.ldsc.tsv.gz
2024/12/20 12:46:26  -Output columns: CHR,POS,A1,A2,Frq,Beta,P,N,SNP
2024/12/20 12:46:26  -Writing sumstats to: ./mysumstats.hapmap3.noMHC.ldsc.tsv.gz...
2024/12/20 12:46:26   -Fast to csv mode...
2024/12/20 12:46:26  -Saving log file to: ./mysumstats.hapmap3.noMHC.ldsc.log
2024/12/20 12:46:26 Finished outputting successfully!

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!zcat ./mysumstats.hapmap3.noMHC.ldsc.tsv.gz | head
!zcat ./mysumstats.hapmap3.noMHC.ldsc.tsv.gz | head

CHR	POS	A1	A2	Frq	Beta	P	N	SNP
1	14900419	G	A	0.3952	0.0144	1.3750e-01	191764	rs6703840
1	19593199	C	T	0.1323	-0.0127	3.2570e-01	191764	rs7527253
1	35282297	G	A	0.5434	0.0041	6.4190e-01	191764	rs1407135
1	66001402	C	T	0.2103	-0.0148	1.7720e-01	191764	rs1171261
1	83510491	G	A	0.0025	0.0378	6.9800e-01	191764	rs2022427
1	166110693	C	T	0.8627	0.0286	2.5250e-02	191764	rs4656480
1	175886511	G	A	0.1828	-0.0141	2.2480e-01	191764	rs6656281
1	181612041	C	T	0.9603	0.0135	5.5050e-01	191764	rs199955
1	196329362	C	T	0.0301	0.0300	2.5060e-01	191764	rs11801881

vcf¶

bgzip : if True, bgzip the output vcf/bed
tabix : if True, index the bgzipped file with tabix

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mysumstats.to_format("./mysumstats",fmt="vcf",bgzip=True,tabix=True,build="19")
mysumstats.to_format("./mysumstats",fmt="vcf",bgzip=True,tabix=True,build="19")

2024/12/20 12:46:26 Start to convert the output sumstats in:  vcf  format
2024/12/20 12:46:26  -Formatting statistics ...
2024/12/20 12:46:26  -Float statistics formats:
2024/12/20 12:46:26   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:26   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:26  -Start outputting sumstats in vcf format...
2024/12/20 12:46:26  -vcf format will be loaded...
2024/12/20 12:46:26  -vcf format meta info:
2024/12/20 12:46:26   - format_name  : vcf
2024/12/20 12:46:26   - format_source  : https://github.com/MRCIEU/gwas-vcf-specification/tree/1.0.0
2024/12/20 12:46:26   - format_version  :  20220923
2024/12/20 12:46:26   - format_citation  : Lyon, M.S., Andrews, S.J., Elsworth, B. et al. The variant call format provides efficient and robust storage of GWAS summary statistics. Genome Biol 22, 32 (2021). https://doi.org/10.1186/s13059-020-02248-0
2024/12/20 12:46:26   - format_fixed  : #CHROM,POS,ID,REF,ALT,QUAL,FILTER,INFO,FORMAT
2024/12/20 12:46:26   - format_format  : ID,SS,ES,SE,LP,SI,EZ
2024/12/20 12:46:26  -gwaslab to vcf format dictionary:
2024/12/20 12:46:26   - gwaslab keys: rsID,CHR,POS,NEA,EA,N,EAF,BETA,SE,MLOG10P,INFO,Z
2024/12/20 12:46:26   - vcf values: ID,#CHROM,POS,REF,ALT,SS,AF,ES,SE,LP,SI,EZ
2024/12/20 12:46:26  -Creating VCF file header...
2024/12/20 12:46:26   -VCF header contig build:19
2024/12/20 12:46:27   -ID:Study_1
2024/12/20 12:46:27   -StudyType:Unknown
2024/12/20 12:46:27   -TotalVariants:1000
2024/12/20 12:46:27   -HarmonisedVariants:0
2024/12/20 12:46:27   -VariantsNotHarmonised:1000
2024/12/20 12:46:27   -SwitchedAlleles:0
2024/12/20 12:46:27  -Writing sumstats to: ./mysumstats.vcf...
2024/12/20 12:46:27  -bgzip compressing : ./mysumstats.vcf.gz...
2024/12/20 12:46:27  -tabix indexing : : ./mysumstats.vcf.gz.tbi...
2024/12/20 12:46:27  -Saving log file to: ./mysumstats.vcf.log
2024/12/20 12:46:27 Finished outputting successfully!

parquet¶

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mysumstats.to_format("./mysumstats",fmt="gwaslab",tab_fmt="parquet",to_tabular_kwargs={"partition_cols":["CHR"]})
mysumstats.to_format("./mysumstats",fmt="gwaslab",tab_fmt="parquet",to_tabular_kwargs={"partition_cols":["CHR"]})

2024/12/20 12:46:27 Start to convert the output sumstats in:  gwaslab  format
2024/12/20 12:46:27  -Formatting statistics ...
2024/12/20 12:46:27  -Float statistics formats:
2024/12/20 12:46:27   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:27   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:27  -Start outputting sumstats in gwaslab format...
2024/12/20 12:46:27  -gwaslab format will be loaded...
2024/12/20 12:46:27  -gwaslab format meta info:
2024/12/20 12:46:27   - format_name  : gwaslab
2024/12/20 12:46:27   - format_source  : https://cloufield.github.io/gwaslab/
2024/12/20 12:46:27   - format_version  : 20231220_v4
2024/12/20 12:46:27  -Output path: ./mysumstats.gwaslab.parquet
2024/12/20 12:46:27  -Output columns: SNPID,CHR,POS,EA,NEA,EAF,BETA,SE,P,N,DIRECTION,STATUS
2024/12/20 12:46:27  -Writing sumstats to: ./mysumstats.gwaslab.parquet...
2024/12/20 12:46:27  -Saving log file to: ./mysumstats.gwaslab.log
2024/12/20 12:46:27 Finished outputting successfully!

For annotation¶

convert to bed format¶

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mysumstats.to_format("./mysumstats",fmt="bed")
mysumstats.to_format("./mysumstats",fmt="bed")

2024/12/20 12:46:27 Start to convert the output sumstats in:  bed  format
2024/12/20 12:46:27  -Formatting statistics ...
2024/12/20 12:46:27  -Float statistics formats:
2024/12/20 12:46:27   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:27   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:27  -Start outputting sumstats in bed format...
2024/12/20 12:46:27  -Number of SNPs : 920
2024/12/20 12:46:27  -Number of Insertions : 52
2024/12/20 12:46:27  -Number of Deletions : 28
2024/12/20 12:46:27  -formatting to 0-based bed-like file...
2024/12/20 12:46:27  -format description: https://genome.ucsc.edu/FAQ/FAQformat.html#format1
2024/12/20 12:46:27  -Adjusting positions in format-specific manner..
2024/12/20 12:46:27  -Output columns: CHR,START,END,NEA/EA,STRAND,SNPID
2024/12/20 12:46:27  -Writing sumstats to: ./mysumstats.bed...
2024/12/20 12:46:27  -Saving log file to: ./mysumstats.bed.log
2024/12/20 12:46:27 Finished outputting successfully!

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!cat mysumstats.bed | head
!cat mysumstats.bed | head

1	2005485	2005486	T/C	+	1:2005486_C_T
1	2247939	2247939	-/AGG	+	1:2247939_AAGG_A
1	3741852	3741853	A/G	+	1:3741853_G_A
1	5017525	5017526	A/G	+	1:5017526_G_A
1	5843474	5843475	T/C	+	1:5843475_C_T
1	9405102	9405103	T/C	+	1:9405103_T_C
1	9443410	9443411	A/G	+	1:9443411_G_A
1	12866347	12866348	C/G	+	1:12866348_G_C
1	14466315	14466316	A/G	+	1:14466316_A_G
1	14900418	14900419	A/G	+	1:14900419_A_G

convert to vep default format¶

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mysumstats.to_format("./mysumstats",fmt="vep")
mysumstats.to_format("./mysumstats",fmt="vep")

2024/12/20 12:46:28 Start to convert the output sumstats in:  vep  format
2024/12/20 12:46:28  -Formatting statistics ...
2024/12/20 12:46:28  -Float statistics formats:
2024/12/20 12:46:28   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:28   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:28  -Start outputting sumstats in vep format...
2024/12/20 12:46:28  -Number of SNPs : 920
2024/12/20 12:46:28  -Number of Insertions : 52
2024/12/20 12:46:28  -Number of Deletions : 28
2024/12/20 12:46:28  -formatting to 1-based bed-like file (for vep)...
2024/12/20 12:46:28  -format description: http://asia.ensembl.org/info/docs/tools/vep/vep_formats.html
2024/12/20 12:46:28  -Adjusting positions in format-specific manner..
2024/12/20 12:46:28  -Output columns: CHR,START,END,NEA/EA,STRAND,SNPID
2024/12/20 12:46:28  -Writing sumstats to: ./mysumstats.vep...
2024/12/20 12:46:28  -Saving log file to: ./mysumstats.vep.log
2024/12/20 12:46:28 Finished outputting successfully!

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!cat mysumstats.vep | head
!cat mysumstats.vep | head

1	2005486	2005486	T/C	+	1:2005486_C_T
1	2247940	2247939	-/AGG	+	1:2247939_AAGG_A
1	3741853	3741853	A/G	+	1:3741853_G_A
1	5017526	5017526	A/G	+	1:5017526_G_A
1	5843475	5843475	T/C	+	1:5843475_C_T
1	9405103	9405103	T/C	+	1:9405103_T_C
1	9443411	9443411	A/G	+	1:9443411_G_A
1	12866348	12866348	C/G	+	1:12866348_G_C
1	14466316	14466316	A/G	+	1:14466316_A_G
1	14900419	14900419	A/G	+	1:14900419_A_G

convert to annovar default input format¶

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mysumstats.to_format("./mysumstats",fmt="annovar")
mysumstats.to_format("./mysumstats",fmt="annovar")

2024/12/20 12:46:28 Start to convert the output sumstats in:  annovar  format
2024/12/20 12:46:28  -Formatting statistics ...
2024/12/20 12:46:28  -Float statistics formats:
2024/12/20 12:46:28   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:28   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:28  -Start outputting sumstats in annovar format...
2024/12/20 12:46:28  -Number of SNPs : 920
2024/12/20 12:46:28  -Number of Insertions : 52
2024/12/20 12:46:28  -Number of Deletions : 28
2024/12/20 12:46:28  -formatting to 1-based bed-like file...
2024/12/20 12:46:28  -format description: https://annovar.openbioinformatics.org/en/latest/user-guide/input/
2024/12/20 12:46:28  -Adjusting positions in format-specific manner..
2024/12/20 12:46:28  -Output columns: CHR,START,END,NEA_out,EA_out,SNPID
2024/12/20 12:46:28  -Writing sumstats to: ./mysumstats.annovar...
2024/12/20 12:46:28  -Saving log file to: ./mysumstats.annovar.log
2024/12/20 12:46:28 Finished outputting successfully!

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!cat mysumstats.annovar | head
!cat mysumstats.annovar | head

1	2005486	2005486	T	C	1:2005486_C_T
1	2247940	2247940	-	AGG	1:2247939_AAGG_A
1	3741853	3741853	A	G	1:3741853_G_A
1	5017526	5017526	A	G	1:5017526_G_A
1	5843475	5843475	T	C	1:5843475_C_T
1	9405103	9405103	T	C	1:9405103_T_C
1	9443411	9443411	A	G	1:9443411_G_A
1	12866348	12866348	C	G	1:12866348_G_C
1	14466316	14466316	A	G	1:14466316_A_G
1	14900419	14900419	A	G	1:14900419_A_G

Filter and then output¶

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mysumstats.filter_value("EAF >0.05 and EAF < 0.95").to_format("./mysumstats_maf005", fmt="ssf", ssfmeta=True, md5sum=True)
mysumstats.filter_value("EAF >0.05 and EAF < 0.95").to_format("./mysumstats_maf005", fmt="ssf", ssfmeta=True, md5sum=True)

2024/12/20 12:46:28 Start filtering values by condition: EAF >0.05 and EAF < 0.95
2024/12/20 12:46:28  -Removing 483 variants not meeting the conditions: EAF >0.05 and EAF < 0.95
2024/12/20 12:46:28 Finished filtering values.
2024/12/20 12:46:28 Start to convert the output sumstats in:  ssf  format
2024/12/20 12:46:28  -Formatting statistics ...
2024/12/20 12:46:28  -Float statistics formats:
2024/12/20 12:46:28   - Columns       : ['EAF', 'BETA', 'SE', 'P']
2024/12/20 12:46:28   - Output formats: ['{:.4g}', '{:.4f}', '{:.4f}', '{:.4e}']
2024/12/20 12:46:28  -Replacing SNPID separator from ":" to "_"...
2024/12/20 12:46:28  -Start outputting sumstats in ssf format...
2024/12/20 12:46:28  -ssf format will be loaded...
2024/12/20 12:46:28  -ssf format meta info:
2024/12/20 12:46:28   - format_name  : ssf
2024/12/20 12:46:28   - format_source  : https://www.biorxiv.org/content/10.1101/2022.07.15.500230v1.full
2024/12/20 12:46:28   - format_cite_name  : GWAS-SSF v0.1
2024/12/20 12:46:28   - format_separator  : \t
2024/12/20 12:46:28   - format_na  : #NA
2024/12/20 12:46:28   - format_col_order  : chromosome,base_pair_location,effect_allele,other_allele,beta,odds_ratio,hazard_ratio,standard_error,effect_allele_frequency,p_value,neg_log_10_p_value,ci_upper,ci_lower,rsid,variant_id,info,ref_allele,n
2024/12/20 12:46:28   - format_version  :  20230328
2024/12/20 12:46:28  -gwaslab to ssf format dictionary:
2024/12/20 12:46:28   - gwaslab keys: SNPID,rsID,CHR,POS,NEA,EA,EAF,N,BETA,SE,P,MLOG10P,INFO,OR,HR,OR_95L,OR_95U
2024/12/20 12:46:28   - ssf values: variant_id,rsid,chromosome,base_pair_location,other_allele,effect_allele,effect_allele_frequency,n,beta,standard_error,p_value,neg_log_10_p_value,info,odds_ratio,hazard_ratio,ci_lower,ci_upper
2024/12/20 12:46:28  -Output path: ./mysumstats_maf005.ssf.tsv.gz
2024/12/20 12:46:28  -Output columns: chromosome,base_pair_location,effect_allele,other_allele,beta,standard_error,effect_allele_frequency,p_value,variant_id,n
2024/12/20 12:46:28  -Writing sumstats to: ./mysumstats_maf005.ssf.tsv.gz...
2024/12/20 12:46:28   -Fast to csv mode...
2024/12/20 12:46:28  -md5sum hashing for the file: ./mysumstats_maf005.ssf.tsv.gz
2024/12/20 12:46:28  -md5sum path: ./mysumstats_maf005.ssf.tsv.gz.md5sum
2024/12/20 12:46:28  -md5sum: 76c4dd440eec447fbeae45a22b75f3e2
2024/12/20 12:46:28  -Exporting SSF-style meta data to ./mysumstats_maf005.ssf.tsv.gz.ssf.tsv-meta.yaml
2024/12/20 12:46:28  -Saving log file to: ./mysumstats_maf005.ssf.log
2024/12/20 12:46:28 Finished outputting successfully!