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IEU GWAS information

Trait: Job coding: accounts and wages clerk/assistant/supervisor, bookkeeper, cost or ledger clerk, audit assistant, budget officer, student loans officer, paymaster.

name	value
id	ukb-d-22601_41223241
trait	Job coding: accounts and wages clerk/assistant/supervisor, bookkeeper, cost or ledger clerk, audit assistant, budget officer, student loans officer, paymaster
category	Binary
ncase	1922
ncontrol	87944
sample_size	89866
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
mr	1
nsnp	10383547

Report information

name	value
gwas_id	ukb-d-22601_41223241
bcf_file	ukb-d-22601_41223241.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-09 15:08 BST
build_version	run_igd-8f4f4c9-2020-05-09

Summary

Summary {data-width=650}

Manhattan plot

$manhattan_plot$

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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}

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-22601_41223241/ukb-d-22601_41223241.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-22601_41223241/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 14:58:38 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22601_41223241/ukb-d-22601_41223241.vcf.gz ...
Read summary statistics for 10383546 SNPs.
Dropped 8236 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, 1280249 SNPs remain.
After merging with regression SNP LD, 1280249 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.002 (0.0047)
Lambda GC: 1.0022
Mean Chi^2: 0.9999
Intercept: 0.9963 (0.0063)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 15:00:43 2019
Total time elapsed: 2.0m:5.18s

QC metrics

Metrics

{
    "af_correlation": 0.9435,
    "inflation_factor": 0.9912,
    "mean_EFFECT": 2.9764e-07,
    "n": 89866,
    "n_snps": 10383546,
    "n_clumped_hits": 2,
    "n_p_sig": 2,
    "n_mono": 0,
    "n_ns": 1105395,
    "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": 204242,
    "n_est": 89949.525,
    "ratio_se_n": 1.0005,
    "mean_diff": 2.0926e-06,
    "ratio_diff": 6.2891,
    "sd_y_est1": 0.1446,
    "sd_y_est2": 0.1447,
    "r2_sum1": 0,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0007,
    "ldsc_nsnp_merge_refpanel_ld": 1280249,
    "ldsc_nsnp_merge_regression_ld": 1280249,
    "ldsc_observed_scale_h2_beta": 0.002,
    "ldsc_observed_scale_h2_se": 0.0047,
    "ldsc_intercept_beta": 0.9963,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0022,
    "ldsc_mean_chisq": 0.9999,
    "ldsc_ratio": 37
}

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	TRUE
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	10375875	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	49372	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	342	0	30615	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	9.077021e+00	6.178319e+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	7.878319e+07	5.605805e+07	3.02000e+02	3.254588e+07	6.971102e+07	1.147296e+08	2.492297e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	3.000000e-07	1.790700e-03	-1.93929e-02	-7.861000e-04	-7.700000e-06	7.708000e-04	1.936850e-02	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.508000e-03	9.848000e-04	5.64100e-04	7.571000e-04	1.057600e-03	1.974700e-03	5.601300e-03	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	5.011278e-01	2.886251e-01	0.00000e+00	2.506709e-01	5.018905e-01	7.511644e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	5.011260e-01	2.886262e-01	0.00000e+00	2.506676e-01	5.018880e-01	7.511630e-01	9.999998e-01	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	2.459513e-01	2.627429e-01	6.50360e-03	3.239230e-02	1.369280e-01	3.934328e-01	9.934960e-01	▇▂▂▁▁
numeric	AF_reference	204242	0.9803302	NA	NA	NA	NA	NA	2.457891e-01	2.536552e-01	0.00000e+00	3.434500e-02	1.535540e-01	3.901760e-01	1.000000e+00	▇▃▂▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	8.986600e+04	0.000000e+00	8.98660e+04	8.986600e+04	8.986600e+04	8.986600e+04	8.986600e+04	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	-0.0010333	0.0011917	0.3859277	0.3859248	0.1114870	0.1894970	89866
1	693731	rs12238997	A	G	-0.0015737	0.0011289	0.1633180	0.1633135	0.1164980	0.1417730	89866
1	707522	rs371890604	G	C	-0.0015165	0.0012691	0.2321250	0.2321223	0.0978285	0.1293930	89866
1	717587	rs144155419	G	A	-0.0008184	0.0030229	0.7865965	0.7865948	0.0158090	0.0045926	89866
1	730087	rs148120343	T	C	-0.0015684	0.0015654	0.3163749	0.3163716	0.0569661	0.0127796	89866
1	731718	rs142557973	T	C	-0.0013896	0.0010712	0.1945822	0.1945760	0.1223780	0.1543530	89866
1	732032	rs61770163	A	C	-0.0016448	0.0011421	0.1498121	0.1498071	0.1220530	0.1555510	89866
1	734349	rs141242758	T	C	-0.0012980	0.0010720	0.2259868	0.2259850	0.1216170	0.1525560	89866
1	749963	rs529266287	T	TAA	0.0010062	0.0010547	0.3400870	0.3400848	0.8689590	0.7641770	89866
1	751343	rs28544273	T	A	-0.0010749	0.0010456	0.3039338	0.3039305	0.1236780	0.2426120	89866

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	-0.0012406	0.0012539	0.3224698	0.3224670	0.0553576	0.0309934	89866
23	154923374	rs111332691	T	A	0.0000159	0.0013650	0.9907060	0.9907059	0.0449113	0.0116556	89866
23	154925045	rs509981	C	T	0.0000131	0.0006583	0.9840730	0.9840733	0.2444280	0.3634440	89866
23	154925895	rs538470	C	T	-0.0001110	0.0006732	0.8690131	0.8690125	0.2408760	0.3634440	89866
23	154927581	rs644138	G	A	-0.0002773	0.0006193	0.6543031	0.6543023	0.3001910	0.4635760	89866
23	154929412	rs557132	C	T	-0.0000270	0.0006585	0.9673060	0.9673061	0.2442750	0.3568210	89866
23	154929637	rs35185538	CT	C	-0.0000108	0.0006876	0.9875160	0.9875160	0.2286930	0.3011920	89866
23	154929952	rs4012982	CAA	C	-0.0002842	0.0006930	0.6817765	0.6817746	0.2381980	0.3165560	89866
23	154930230	rs781880	A	G	-0.0000225	0.0006583	0.9727819	0.9727819	0.2447120	0.3618540	89866
23	154930487	rs781879	T	A	-0.0006473	0.0022332	0.7719355	0.7719353	0.0196791	0.1263580	89866

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111487 ES:SE:LP:AF:SS:ID   -0.00103325:0.00119171:0.413494:0.111487:89866:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116498 ES:SE:LP:AF:SS:ID   -0.00157366:0.00112887:0.786966:0.116498:89866:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978285    ES:SE:LP:AF:SS:ID   -0.00151646:0.0012691:0.634278:0.0978285:89866:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015809 ES:SE:LP:AF:SS:ID   -0.000818416:0.00302294:0.104248:0.015809:89866:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569661    ES:SE:LP:AF:SS:ID   -0.00156839:0.00156535:0.499798:0.0569661:89866:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122378 ES:SE:LP:AF:SS:ID   -0.00138957:0.00107124:0.710897:0.122378:89866:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122053 ES:SE:LP:AF:SS:ID   -0.00164481:0.00114206:0.824453:0.122053:89866:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121617 ES:SE:LP:AF:SS:ID   -0.00129799:0.00107204:0.645917:0.121617:89866:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868959 ES:SE:LP:AF:SS:ID   0.00100621:0.00105473:0.46841:0.868959:89866:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123678 ES:SE:LP:AF:SS:ID   -0.00107493:0.00104561:0.517221:0.123678:89866:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143191 ES:SE:LP:AF:SS:ID   -0.000533502:0.00103522:0.217306:0.143191:89866:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123813 ES:SE:LP:AF:SS:ID   -0.00107701:0.0010441:0.519562:0.123813:89866:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869927 ES:SE:LP:AF:SS:ID   0.00111096:0.00101733:0.560948:0.869927:89866:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87461  ES:SE:LP:AF:SS:ID   0.00118818:0.00103392:0.601232:0.87461:89866:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12951  ES:SE:LP:AF:SS:ID   -0.00103809:0.00102044:0.51002:0.12951:89866:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0357365    ES:SE:LP:AF:SS:ID   0.000251996:0.00186692:0.0493295:0.0357365:89866:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869574 ES:SE:LP:AF:SS:ID   0.00116496:0.00101643:0.599034:0.869574:89866:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869652 ES:SE:LP:AF:SS:ID   0.00115557:0.00101689:0.592096:0.869652:89866:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   0.00116749:0.00101639:0.600851:0.86957:89866:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869566 ES:SE:LP:AF:SS:ID   0.00120325:0.00101438:0.627921:0.869566:89866:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126879 ES:SE:LP:AF:SS:ID   -0.00105058:0.00103552:0.508179:0.126879:89866:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869094 ES:SE:LP:AF:SS:ID   0.00118858:0.00101175:0.61963:0.869094:89866:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868498 ES:SE:LP:AF:SS:ID   0.00131726:0.00101113:0.715211:0.868498:89866:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869245 ES:SE:LP:AF:SS:ID   0.00124483:0.00101267:0.659594:0.869245:89866:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869251 ES:SE:LP:AF:SS:ID   0.00124524:0.00101274:0.659832:0.869251:89866:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869252 ES:SE:LP:AF:SS:ID   0.00124369:0.00101275:0.658694:0.869252:89866:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869724 ES:SE:LP:AF:SS:ID   0.00120721:0.00101544:0.629855:0.869724:89866:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991203    ES:SE:LP:AF:SS:ID   -0.00176599:0.00118214:0.869007:0.0991203:89866:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873732 ES:SE:LP:AF:SS:ID   0.00122422:0.00103052:0.6292:0.873732:89866:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863116 ES:SE:LP:AF:SS:ID   0.00109907:0.00101079:0.557696:0.863116:89866:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868511 ES:SE:LP:AF:SS:ID   0.00116189:0.00102089:0.593334:0.868511:89866:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86539  ES:SE:LP:AF:SS:ID   0.00108142:0.00102104:0.538291:0.86539:89866:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994301    ES:SE:LP:AF:SS:ID   -0.00173038:0.00122269:0.804081:0.0994301:89866:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870696 ES:SE:LP:AF:SS:ID   0.00105113:0.00103278:0.510333:0.870696:89866:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870695 ES:SE:LP:AF:SS:ID   0.00105096:0.00103278:0.510221:0.870695:89866:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870693 ES:SE:LP:AF:SS:ID   0.00105091:0.00103279:0.510191:0.870693:89866:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871061 ES:SE:LP:AF:SS:ID   0.00103536:0.00103327:0.499847:0.871061:89866:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126484 ES:SE:LP:AF:SS:ID   -0.00105085:0.00103432:0.509144:0.126484:89866:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106022 ES:SE:LP:AF:SS:ID   -0.0017482:0.00112438:0.92084:0.106022:89866:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854451 ES:SE:LP:AF:SS:ID   0.00131077:0.00101054:0.710853:0.854451:89866:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839008 ES:SE:LP:AF:SS:ID   -0.00231964:0.000998292:1.69576:0.839008:89866:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.76317  ES:SE:LP:AF:SS:ID   -0.000239038:0.000802644:0.115859:0.76317:89866:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.10519  ES:SE:LP:AF:SS:ID   0.00199201:0.00110615:1.1443:0.10519:89866:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00773441   ES:SE:LP:AF:SS:ID   0.00282076:0.00409813:0.308685:0.00773441:89866:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129876 ES:SE:LP:AF:SS:ID   -0.00105368:0.00101983:0.520688:0.129876:89866:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129602 ES:SE:LP:AF:SS:ID   -0.00112184:0.00101849:0.567517:0.129602:89866:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104469 ES:SE:LP:AF:SS:ID   0.00203935:0.00111468:1.17185:0.104469:89866:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00900456   ES:SE:LP:AF:SS:ID   0.00234945:0.00393357:0.259384:0.00900456:89866:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00774975   ES:SE:LP:AF:SS:ID   0.00274241:0.0041155:0.296551:0.00774975:89866:rs112563271
1   770886  rs371458725 G   A   .   PASS    AF=0.103468 ES:SE:LP:AF:SS:ID   0.0020306:0.00112435:1.14925:0.103468:89866:rs371458725