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IEU GWAS information

Trait: Gap coding: Paid work for less than 15 hours per week on average or lasting less than 6 months.

name	value
id	ukb-d-22660_101
trait	Gap coding: Paid work for less than 15 hours per week on average or lasting less than 6 months
category	Binary
ncase	15086
ncontrol	53665
sample_size	68751
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
mr	1
nsnp	13560222

Report information

name	value
gwas_id	ukb-d-22660_101
bcf_file	ukb-d-22660_101.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 23:11 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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    "FORMAT.2": "<ID=LP,Number=A,Type=Float,Description=\"-log10 p-value for effect estimate\">",
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    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
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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-22660_101/ukb-d-22660_101.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-22660_101/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 14:53:51 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22660_101/ukb-d-22660_101.vcf.gz ...
Read summary statistics for 13560221 SNPs.
Dropped 12671 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0062 (0.0065)
Lambda GC: 1.0073
Mean Chi^2: 1.0057
Intercept: 0.9973 (0.0063)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 14:56:08 2019
Total time elapsed: 2.0m:16.75s

QC metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 0.9975,
    "mean_EFFECT": 0,
    "n": 67655,
    "n_snps": 13560221,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250997,
    "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": 561552,
    "n_est": 67875.582,
    "ratio_se_n": 1.0016,
    "mean_diff": 0,
    "ratio_diff": 11.6475,
    "sd_y_est1": 0.3983,
    "sd_y_est2": 0.3989,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0062,
    "ldsc_observed_scale_h2_se": 0.0065,
    "ldsc_intercept_beta": 0.9973,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0073,
    "ldsc_mean_chisq": 1.0057,
    "ldsc_ratio": -0.4737
}

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	13548214	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	57036	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	342	0	33331	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	9.051468e+00	6.185045e+00	1.000000	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.902618e+07	5.591720e+07	302.000000	3.292798e+07	7.013588e+07	1.148646e+08	2.492309e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	1.860000e-05	1.255360e-02	-0.157741	-3.334500e-03	-2.210000e-05	3.296700e-03	1.699600e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	9.051400e-03	8.719900e-03	0.001805	2.588400e-03	4.757500e-03	1.299340e-02	4.464180e-02	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	5.004898e-01	2.887557e-01	0.000000	2.507420e-01	5.005425e-01	7.507909e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	5.004874e-01	2.887572e-01	0.000000	2.507378e-01	5.005401e-01	7.507897e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.911551e-01	2.544950e-01	0.001000	7.523000e-03	6.040290e-02	2.959440e-01	9.990000e-01	▇▂▁▁▁
numeric	AF_reference	561552	0.9585883	NA	NA	NA	NA	NA	1.965910e-01	2.471619e-01	0.000000	5.790700e-03	8.466450e-02	3.086090e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	6.765500e+04	0.000000e+00	67655.000000	6.765500e+04	6.765500e+04	6.765500e+04	6.765500e+04	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	0.0012258	0.0037810	0.7457787	0.7457787	0.1113330	0.1894970	67655
1	693731	rs12238997	A	G	0.0036998	0.0035818	0.3016289	0.3016246	0.1164250	0.1417730	67655
1	707522	rs371890604	G	C	0.0009056	0.0040270	0.8220791	0.8220788	0.0978617	0.1293930	67655
1	717587	rs144155419	G	A	0.0026936	0.0095893	0.7787947	0.7787936	0.0157910	0.0045926	67655
1	723329	rs189787166	A	T	0.0131813	0.0275084	0.6318180	0.6318151	0.0018352	0.0003994	67655
1	730087	rs148120343	T	C	-0.0035319	0.0049677	0.4771050	0.4771021	0.0569430	0.0127796	67655
1	731718	rs142557973	T	C	0.0025811	0.0033994	0.4476762	0.4476743	0.1223980	0.1543530	67655
1	732032	rs61770163	A	C	0.0010243	0.0036255	0.7775333	0.7775317	0.1220450	0.1555510	67655
1	734349	rs141242758	T	C	0.0023836	0.0034019	0.4835095	0.4835052	0.1216050	0.1525560	67655
1	740284	rs61770167	C	T	0.0013241	0.0157189	0.9328691	0.9328682	0.0056852	0.0023962	67655

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	0.0029457	0.0040549	0.4675585	0.4675565	0.0547784	0.0309934	67655
23	154923374	rs111332691	T	A	0.0031045	0.0044125	0.4816982	0.4816956	0.0442687	0.0116556	67655
23	154925045	rs509981	C	T	-0.0017766	0.0021064	0.3989707	0.3989683	0.2448950	0.3634440	67655
23	154925895	rs538470	C	T	-0.0022390	0.0021539	0.2985603	0.2985547	0.2412550	0.3634440	67655
23	154927581	rs644138	G	A	-0.0008433	0.0019841	0.6708123	0.6708116	0.3000720	0.4635760	67655
23	154929412	rs557132	C	T	-0.0018063	0.0021070	0.3912938	0.3912895	0.2447530	0.3568210	67655
23	154929637	rs35185538	CT	C	-0.0013172	0.0022010	0.5495485	0.5495477	0.2291340	0.3011920	67655
23	154929952	rs4012982	CAA	C	-0.0012366	0.0022180	0.5771584	0.5771545	0.2385660	0.3165560	67655
23	154930230	rs781880	A	G	-0.0018460	0.0021065	0.3808658	0.3808624	0.2451600	0.3618540	67655
23	154930487	rs781879	T	A	-0.0054007	0.0072100	0.4538267	0.4538242	0.0193551	0.1263580	67655

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111333 ES:SE:LP:AF:SS:ID   0.00122583:0.00378097:0.12739:0.111333:67655:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116425 ES:SE:LP:AF:SS:ID   0.00369982:0.00358178:0.520527:0.116425:67655:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978617    ES:SE:LP:AF:SS:ID   0.000905569:0.00402704:0.0850864:0.0978617:67655:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015791 ES:SE:LP:AF:SS:ID   0.00269355:0.00958929:0.108577:0.015791:67655:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00183518   ES:SE:LP:AF:SS:ID   0.0131813:0.0275084:0.199408:0.00183518:67655:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056943 ES:SE:LP:AF:SS:ID   -0.00353192:0.00496774:0.321386:0.056943:67655:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122398 ES:SE:LP:AF:SS:ID   0.00258112:0.00339935:0.349036:0.122398:67655:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122045 ES:SE:LP:AF:SS:ID   0.00102433:0.00362547:0.109281:0.122045:67655:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121605 ES:SE:LP:AF:SS:ID   0.00238363:0.0034019:0.315595:0.121605:67655:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00568516   ES:SE:LP:AF:SS:ID   0.00132411:0.0157189:0.0301793:0.00568516:67655:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00185636   ES:SE:LP:AF:SS:ID   -0.0408126:0.029526:0.777551:0.00185636:67655:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86888  ES:SE:LP:AF:SS:ID   0.000301271:0.00334526:0.0323393:0.86888:67655:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00154315   ES:SE:LP:AF:SS:ID   -0.0426256:0.0303273:0.796228:0.00154315:67655:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123646 ES:SE:LP:AF:SS:ID   -0.000304511:0.00331793:0.0329788:0.123646:67655:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143073 ES:SE:LP:AF:SS:ID   0.000111351:0.00328388:0.0119095:0.143073:67655:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123779 ES:SE:LP:AF:SS:ID   -0.000237747:0.00331307:0.0255837:0.123779:67655:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869863 ES:SE:LP:AF:SS:ID   -8.19128e-05:0.00322778:0.00888295:0.869863:67655:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874632 ES:SE:LP:AF:SS:ID   0.000409396:0.00328158:0.0454116:0.874632:67655:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129534 ES:SE:LP:AF:SS:ID   0.000444559:0.00323748:0.0502291:0.129534:67655:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358436    ES:SE:LP:AF:SS:ID   -0.00480659:0.00590964:0.380885:0.0358436:67655:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869516 ES:SE:LP:AF:SS:ID   8.48976e-06:0.00322492:0.000912977:0.869516:67655:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869601 ES:SE:LP:AF:SS:ID   0.000145519:0.00322657:0.0159104:0.869601:67655:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86951  ES:SE:LP:AF:SS:ID   2.41673e-05:0.00322477:0.00260444:0.86951:67655:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00535705   ES:SE:LP:AF:SS:ID   -0.0140481:0.0160629:0.41815:0.00535705:67655:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00532268   ES:SE:LP:AF:SS:ID   -0.0139109:0.0161034:0.411532:0.00532268:67655:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00587606   ES:SE:LP:AF:SS:ID   0.0108041:0.0155146:0.313192:0.00587606:67655:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869521 ES:SE:LP:AF:SS:ID   0.000222204:0.00321863:0.0245861:0.869521:67655:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126879 ES:SE:LP:AF:SS:ID   -0.000215962:0.00328525:0.0233809:0.126879:67655:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869086 ES:SE:LP:AF:SS:ID   0.000217579:0.00321047:0.0241236:0.869086:67655:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86843  ES:SE:LP:AF:SS:ID   -0.000132542:0.00320707:0.0145583:0.86843:67655:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   0.000165041:0.00321308:0.018166:0.869213:67655:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869219 ES:SE:LP:AF:SS:ID   0.000163662:0.0032133:0.0180098:0.869219:67655:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:SS:ID   0.000166767:0.00321332:0.018358:0.869221:67655:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869661 ES:SE:LP:AF:SS:ID   0.000280968:0.00322168:0.0312822:0.869661:67655:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991549    ES:SE:LP:AF:SS:ID   0.00071154:0.00375054:0.0708203:0.0991549:67655:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00672466   ES:SE:LP:AF:SS:ID   0.00831514:0.0141446:0.254438:0.00672466:67655:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873693 ES:SE:LP:AF:SS:ID   0.000729624:0.00326918:0.0843923:0.873693:67655:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86311  ES:SE:LP:AF:SS:ID   0.00100872:0.00320645:0.123162:0.86311:67655:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868459 ES:SE:LP:AF:SS:ID   0.00057141:0.00323885:0.0655212:0.868459:67655:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865449 ES:SE:LP:AF:SS:ID   0.000430827:0.00323906:0.0485721:0.865449:67655:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0996966    ES:SE:LP:AF:SS:ID   -0.000962802:0.00387301:0.094919:0.0996966:67655:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   0.000378668:0.0032761:0.0419228:0.870704:67655:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870704 ES:SE:LP:AF:SS:ID   0.000379464:0.0032761:0.0420151:0.870704:67655:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870702 ES:SE:LP:AF:SS:ID   0.000377117:0.00327611:0.0417434:0.870702:67655:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871042 ES:SE:LP:AF:SS:ID   0.000106847:0.00327768:0.0114433:0.871042:67655:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126524 ES:SE:LP:AF:SS:ID   -0.000562055:0.00328098:0.0634948:0.126524:67655:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105925 ES:SE:LP:AF:SS:ID   0.000898137:0.00357067:0.0961485:0.105925:67655:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854403 ES:SE:LP:AF:SS:ID   -0.000442281:0.00320503:0.0504909:0.854403:67655:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00175177   ES:SE:LP:AF:SS:ID   0.00460944:0.0275478:0.0619233:0.00175177:67655:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839355 ES:SE:LP:AF:SS:ID   0.00125179:0.00316573:0.159558:0.839355:67655:rs376645387