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IEU GWAS information

Trait: Major dietary changes in the last 5 years: Yes, because of illness.

name	value
id	ukb-d-1538_1
trait	Major dietary changes in the last 5 years: Yes, because of illness
category	Binary
ncase	38051
ncontrol	322243
sample_size	360294
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
mr	1
nsnp	13586569

Report information

name	value
gwas_id	ukb-d-1538_1
bcf_file	ukb-d-1538_1.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 23:26 BST
build_version	run_igd-8f4f4c9-2020-05-09

Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_plot

beta_std plot

beta_std_plot

Metadata

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}

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1538_1/ukb-d-1538_1.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1538_1/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 17:06:38 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1538_1/ukb-d-1538_1.vcf.gz ...
Read summary statistics for 13586568 SNPs.
Dropped 12711 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0275 (0.0018)
Lambda GC: 1.1786
Mean Chi^2: 1.1983
Intercept: 1.0107 (0.0067)
Ratio: 0.054 (0.0339)
Analysis finished at Mon Nov 25 17:08:55 2019
Total time elapsed: 2.0m:17.12s

QC metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1118,
    "mean_EFFECT": 0,
    "n": 360294,
    "n_snps": 13586568,
    "n_clumped_hits": 8,
    "n_p_sig": 816,
    "n_mono": 0,
    "n_ns": 1251802,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 569298,
    "n_est": 361677.1315,
    "ratio_se_n": 1.0019,
    "mean_diff": 0,
    "ratio_diff": 92.8885,
    "sd_y_est1": 0.3076,
    "sd_y_est2": 0.3082,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.001,
    "r2_sum3": 0.001,
    "r2_sum4": 0.001,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0275,
    "ldsc_observed_scale_h2_se": 0.0018,
    "ldsc_intercept_beta": 1.0107,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.1786,
    "ldsc_mean_chisq": 1.1983,
    "ldsc_ratio": 0.054
}

Flags

name	value
af_correlation	FALSE
inflation_factor	FALSE
n	FALSE
is_snpid_non_unique	TRUE
mean_EFFECT_nonfinite	FALSE
mean_EFFECT_05	FALSE
mean_EFFECT_01	FALSE
mean_chisq	FALSE
n_p_sig	FALSE
miss_EFFECT	FALSE
miss_SE	FALSE
miss_PVAL	FALSE
ldsc_ratio	FALSE
ldsc_intercept_beta	FALSE
n_clumped_hits	FALSE
r2_sum1	FALSE
r2_sum2	FALSE
r2_sum3	FALSE
r2_sum4	FALSE

Definitions

General metrics

af_correlation: Correlation coefficient between AF and AF_reference.
inflation_factor (lambda): Genomic inflation factor.
mean_EFFECT: Mean of EFFECT size.
n: Maximum value of reported sample size across all SNPs, \(n\).
n_clumped_hits: Number of clumped hits.
n_snps: Number of SNPs
n_p_sig: Number of SNPs with pvalue below 5e-8.
n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
n_ns: Number of SNPs with nonsense values:
- alleles other than A, C, G or T.
- P-values < 0 or > 1.
- negative or infinite standard errors (<= 0 or = Infinity).
- infinite beta estimates or allele frequencies < 0 or > 1.
n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

n_est: Estimated sample size value, \(\widehat{n}\).
ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

r2_sum<*>: r2 statistics under various assumptions
- 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
- 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
- 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
- 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
ldsc_lambda_gc: Lambda GC statistics.
ldsc_mean_chisq: Mean \(\chi^2\) statistics.
ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

af_correlation: abs(af_correlation) < 0.7.
inflation_factor: inflation_factor > 1.2.
n: n (max reported sample size) < 10000.
is_snpid_non_unique: NOT is_snpid_unique.
mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
n_p_sig: n_p_sig > 1000.
miss_<*>: n_miss_<*> / n_snps > 0.01.
ldsc_ratio: ldsc_ratio > 0.5
ldsc_intercept_beta: ldsc_intercept_beta > 1.5
n_clumped_hits: n_clumped_hits > 1000
r2_sum<*>: r2_sum<*> > 0.5

Plots

Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
QQ plot
AF plot
P-Z plot
beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type	skim_variable	n_missing	complete_rate	character.min	character.max	character.empty	character.n_unique	character.whitespace	numeric.mean	numeric.sd	numeric.p0	numeric.p25	numeric.p50	numeric.p75	numeric.p100	numeric.hist
character	ID	0	1.0000000	3	94	0	13574521	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	57084	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	342	0	33337	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	9.051328e+00	6.184966e+00	1.00000e+00	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.902497e+07	5.591474e+07	3.02000e+02	3.293093e+07	7.013838e+07	1.148587e+08	2.492309e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	2.100000e-05	4.268800e-03	-5.15396e-02	-1.188100e-03	4.200000e-06	1.201800e-03	6.353290e-02	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	3.045400e-03	2.937700e-03	5.95800e-04	8.670000e-04	1.597700e-03	4.376600e-03	1.477260e-02	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.827034e-01	2.934474e-01	0.00000e+00	2.243701e-01	4.769557e-01	7.367548e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.827030e-01	2.934477e-01	0.00000e+00	2.243687e-01	4.769556e-01	7.367537e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.908019e-01	2.544021e-01	1.00000e-03	7.428900e-03	6.002970e-02	2.953050e-01	9.989990e-01	▇▂▁▁▁
numeric	AF_reference	569298	0.9580985	NA	NA	NA	NA	NA	1.963333e-01	2.471007e-01	0.00000e+00	5.591000e-03	8.426520e-02	3.081070e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.602940e+05	0.000000e+00	3.60294e+05	3.602940e+05	3.602940e+05	3.602940e+05	3.602940e+05	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	-0.0001344	0.0012692	0.9156719	0.9156720	0.1106260	0.1894970	360294
1	693731	rs12238997	A	G	0.0001801	0.0011992	0.8806021	0.8806015	0.1158160	0.1417730	360294
1	707522	rs371890604	G	C	0.0001525	0.0013483	0.9099250	0.9099243	0.0972904	0.1293930	360294
1	717587	rs144155419	G	A	-0.0006485	0.0032171	0.8402521	0.8402516	0.0156859	0.0045926	360294
1	723329	rs189787166	A	T	-0.0049520	0.0094869	0.6016834	0.6016830	0.0017348	0.0003994	360294
1	730087	rs148120343	T	C	0.0010314	0.0016706	0.5369724	0.5369722	0.0564633	0.0127796	360294
1	731718	rs142557973	T	C	-0.0001414	0.0011373	0.9010799	0.9010804	0.1217220	0.1543530	360294
1	732032	rs61770163	A	C	0.0000388	0.0012132	0.9745051	0.9745051	0.1211580	0.1555510	360294
1	734349	rs141242758	T	C	-0.0000963	0.0011379	0.9325540	0.9325542	0.1209490	0.1525560	360294
1	740284	rs61770167	C	T	-0.0108693	0.0052046	0.0367638	0.0367630	0.0057877	0.0023962	360294

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	0.0004375	0.0013137	0.7391082	0.7391089	0.0561742	0.0309934	360294
23	154923374	rs111332691	T	A	0.0021131	0.0014438	0.1433069	0.1433045	0.0447940	0.0116556	360294
23	154925045	rs509981	C	T	-0.0014564	0.0006947	0.0360512	0.0360508	0.2455970	0.3634440	360294
23	154925895	rs538470	C	T	-0.0016528	0.0007107	0.0200364	0.0200360	0.2419100	0.3634440	360294
23	154927581	rs644138	G	A	-0.0011179	0.0006534	0.0870783	0.0870770	0.3021590	0.4635760	360294
23	154929412	rs557132	C	T	-0.0014500	0.0006950	0.0369343	0.0369336	0.2454490	0.3568210	360294
23	154929637	rs35185538	CT	C	-0.0011824	0.0007253	0.1030680	0.1030668	0.2296860	0.3011920	360294
23	154929952	rs4012982	CAA	C	-0.0014763	0.0007309	0.0434110	0.0434096	0.2394100	0.3165560	360294
23	154930230	rs781880	A	G	-0.0015231	0.0006948	0.0283831	0.0283822	0.2458580	0.3618540	360294
23	154930487	rs781879	T	A	0.0003773	0.0023840	0.8742451	0.8742446	0.0195564	0.1263580	360294

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110626 ES:SE:LP:AF:SS:ID   -0.000134396:0.00126924:0.0382601:0.110626:360294:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115816 ES:SE:LP:AF:SS:ID   0.000180125:0.00119918:0.0552203:0.115816:360294:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972904    ES:SE:LP:AF:SS:ID   0.000152534:0.00134826:0.0409944:0.0972904:360294:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156859    ES:SE:LP:AF:SS:ID   -0.000648472:0.00321708:0.0755904:0.0156859:360294:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173485   ES:SE:LP:AF:SS:ID   -0.004952:0.00948692:0.220632:0.00173485:360294:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564633    ES:SE:LP:AF:SS:ID   0.00103145:0.00167064:0.270048:0.0564633:360294:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121722 ES:SE:LP:AF:SS:ID   -0.000141365:0.00113732:0.0452367:0.121722:360294:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121158 ES:SE:LP:AF:SS:ID   3.87731e-05:0.00121323:0.0112159:0.121158:360294:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120949 ES:SE:LP:AF:SS:ID   -9.63049e-05:0.00113793:0.030326:0.120949:360294:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578766   ES:SE:LP:AF:SS:ID   -0.0108693:0.00520464:1.43458:0.00578766:360294:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187451   ES:SE:LP:AF:SS:ID   -0.00845085:0.00984421:0.408223:0.00187451:360294:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86976  ES:SE:LP:AF:SS:ID   0.000117123:0.00112183:0.0377022:0.86976:360294:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152812   ES:SE:LP:AF:SS:ID   -0.0112573:0.0101646:0.571744:0.00152812:360294:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122907 ES:SE:LP:AF:SS:ID   -0.000105125:0.00111102:0.0340381:0.122907:360294:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142703 ES:SE:LP:AF:SS:ID   9.88309e-05:0.00109818:0.0323159:0.142703:360294:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123023 ES:SE:LP:AF:SS:ID   -7.25361e-05:0.00110947:0.0232503:0.123023:360294:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870904 ES:SE:LP:AF:SS:ID   6.31011e-05:0.00108118:0.020698:0.870904:360294:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875481 ES:SE:LP:AF:SS:ID   9.65012e-06:0.00109908:0.00305294:0.875481:360294:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128619 ES:SE:LP:AF:SS:ID   -3.07952e-05:0.00108386:0.00995744:0.128619:360294:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363703    ES:SE:LP:AF:SS:ID   -0.00113912:0.00196613:0.250002:0.0363703:360294:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870499 ES:SE:LP:AF:SS:ID   2.47566e-05:0.00108006:0.00801546:0.870499:360294:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870604 ES:SE:LP:AF:SS:ID   2.67857e-05:0.00108055:0.00867511:0.870604:360294:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870496 ES:SE:LP:AF:SS:ID   5.06357e-06:0.00108002:0.00162774:0.870496:360294:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504167   ES:SE:LP:AF:SS:ID   0.00221216:0.00554567:0.161171:0.00504167:360294:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500863   ES:SE:LP:AF:SS:ID   0.002287:0.00556052:0.166943:0.00500863:360294:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558826   ES:SE:LP:AF:SS:ID   0.00708595:0.0053686:0.728453:0.00558826:360294:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870578 ES:SE:LP:AF:SS:ID   4.95197e-05:0.00107812:0.0162091:0.870578:360294:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125973 ES:SE:LP:AF:SS:ID   -0.000125448:0.00110004:0.0413372:0.125973:360294:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870141 ES:SE:LP:AF:SS:ID   4.1253e-05:0.00107552:0.0134952:0.870141:360294:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869429 ES:SE:LP:AF:SS:ID   -9.05035e-05:0.00107454:0.0301756:0.869429:360294:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870295 ES:SE:LP:AF:SS:ID   8.32071e-06:0.00107645:0.00268659:0.870295:360294:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870301 ES:SE:LP:AF:SS:ID   6.9981e-06:0.00107653:0.00225855:0.870301:360294:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87031  ES:SE:LP:AF:SS:ID   1.03544e-05:0.00107656:0.00334563:0.87031:360294:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870754 ES:SE:LP:AF:SS:ID   6.4291e-05:0.0010793:0.021135:0.870754:360294:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988389    ES:SE:LP:AF:SS:ID   -0.00017506:0.00125423:0.0511002:0.0988389:360294:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647783   ES:SE:LP:AF:SS:ID   0.00566891:0.00485034:0.61529:0.00647783:360294:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874646 ES:SE:LP:AF:SS:ID   0.000117401:0.00109537:0.0387465:0.874646:360294:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864042 ES:SE:LP:AF:SS:ID   0.000233021:0.00107418:0.0818307:0.864042:360294:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   9.65656e-05:0.00108459:0.0319586:0.869437:360294:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86638  ES:SE:LP:AF:SS:ID   0.000128716:0.0010848:0.043088:0.86638:360294:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987644    ES:SE:LP:AF:SS:ID   0.000454144:0.00129879:0.138712:0.0987644:360294:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871565 ES:SE:LP:AF:SS:ID   0.000149286:0.00109717:0.0497471:0.871565:360294:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871565 ES:SE:LP:AF:SS:ID   0.000149336:0.00109717:0.0497647:0.871565:360294:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871564 ES:SE:LP:AF:SS:ID   0.000147681:0.00109719:0.0491831:0.871564:360294:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871939 ES:SE:LP:AF:SS:ID   0.000117588:0.00109782:0.0387208:0.871939:360294:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125553 ES:SE:LP:AF:SS:ID   -5.28566e-05:0.00109866:0.0169924:0.125553:360294:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10542  ES:SE:LP:AF:SS:ID   0.000162482:0.0011961:0.0496619:0.10542:360294:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855389 ES:SE:LP:AF:SS:ID   0.000280602:0.00107374:0.100269:0.855389:360294:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165572   ES:SE:LP:AF:SS:ID   -0.00403135:0.00950731:0.172924:0.00165572:360294:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838365 ES:SE:LP:AF:SS:ID   -0.000225059:0.00105788:0.0801247:0.838365:360294:rs376645387