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IEU GWAS information

Trait: Which eye(s) affected by presbyopia: Both eyes.

name	value
id	ukb-d-5610_3
trait	Which eye(s) affected by presbyopia: Both eyes
category	Binary
ncase	28009
ncontrol	3485
sample_size	31494
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
mr	1
nsnp	13535065

Report information

name	value
gwas_id	ukb-d-5610_3
bcf_file	ukb-d-5610_3.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 23:22 BST
build_version	run_igd-8f4f4c9-2020-05-09

Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ 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-5610_3/ukb-d-5610_3.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-5610_3/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 17:12:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5610_3/ukb-d-5610_3.vcf.gz ...
Read summary statistics for 13535064 SNPs.
Dropped 12637 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, 1283498 SNPs remain.
After merging with regression SNP LD, 1283498 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0121 (0.0146)
Lambda GC: 1.0033
Mean Chi^2: 1.0097
Intercept: 1.0022 (0.006)
Ratio: 0.2263 (0.6229)
Analysis finished at Mon Nov 25 17:14:57 2019
Total time elapsed: 2.0m:44.7s

QC metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0079,
    "mean_EFFECT": -3.2175e-06,
    "n": 31494,
    "n_snps": 13535064,
    "n_clumped_hits": 0,
    "n_p_sig": 7,
    "n_mono": 0,
    "n_ns": 1250075,
    "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": 555267,
    "n_est": 31656.1042,
    "ratio_se_n": 1.0026,
    "mean_diff": -4.1282e-06,
    "ratio_diff": 1.4406,
    "sd_y_est1": 0.3143,
    "sd_y_est2": 0.3151,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283498,
    "ldsc_nsnp_merge_regression_ld": 1283498,
    "ldsc_observed_scale_h2_beta": 0.0121,
    "ldsc_observed_scale_h2_se": 0.0146,
    "ldsc_intercept_beta": 1.0022,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0033,
    "ldsc_mean_chisq": 1.0097,
    "ldsc_ratio": 0.2268
}

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	13523091	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	56981	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	342	0	33315	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	9.051529e+00	6.184573e+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	7.901914e+07	5.591731e+07	3.02000e+02	3.292155e+07	7.012662e+07	1.148464e+08	2.492309e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-3.200000e-06	1.446570e-02	-2.05907e-01	-3.769500e-03	5.130000e-05	3.931900e-03	1.603220e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.041550e-02	1.002230e-02	2.05980e-03	2.991600e-03	5.484400e-03	1.493540e-02	5.477160e-02	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.989082e-01	2.888645e-01	0.00000e+00	2.485049e-01	4.983139e-01	7.489193e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.989031e-01	2.888675e-01	0.00000e+00	2.484962e-01	4.983087e-01	7.489173e-01	9.999998e-01	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.915026e-01	2.545776e-01	1.00000e-03	7.621900e-03	6.084820e-02	2.966760e-01	9.990000e-01	▇▂▁▁▁
numeric	AF_reference	555267	0.9589757	NA	NA	NA	NA	NA	1.968475e-01	2.472181e-01	0.00000e+00	5.790700e-03	8.506390e-02	3.091050e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.149400e+04	0.000000e+00	3.14940e+04	3.149400e+04	3.149400e+04	3.149400e+04	3.149400e+04	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	0.0019271	0.0043794	0.6599074	0.6599056	0.1116860	0.1894970	31494
1	693731	rs12238997	A	G	-0.0006369	0.0041401	0.8777350	0.8777344	0.1175430	0.1417730	31494
1	707522	rs371890604	G	C	0.0020750	0.0046578	0.6559746	0.6559714	0.0978470	0.1293930	31494
1	717587	rs144155419	G	A	-0.0087226	0.0111096	0.4323814	0.4323726	0.0158964	0.0045926	31494
1	723329	rs189787166	A	T	0.0266364	0.0335210	0.4268419	0.4268356	0.0016232	0.0003994	31494
1	730087	rs148120343	T	C	0.0072466	0.0057449	0.2071772	0.2071672	0.0574672	0.0127796	31494
1	731718	rs142557973	T	C	0.0000197	0.0039223	0.9959980	0.9959976	0.1232790	0.1543530	31494
1	732032	rs61770163	A	C	-0.0007985	0.0041764	0.8483850	0.8483833	0.1228850	0.1555510	31494
1	734349	rs141242758	T	C	0.0001183	0.0039260	0.9759579	0.9759582	0.1224210	0.1525560	31494
1	740284	rs61770167	C	T	0.0097964	0.0174191	0.5738548	0.5738495	0.0061427	0.0023962	31494

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	-0.0059158	0.0045507	0.1936208	0.1936113	0.0562109	0.0309934	31494
23	154923374	rs111332691	T	A	0.0008903	0.0050088	0.8589200	0.8589194	0.0442783	0.0116556	31494
23	154925045	rs509981	C	T	-0.0010521	0.0024152	0.6631045	0.6631023	0.2440420	0.3634440	31494
23	154925895	rs538470	C	T	-0.0006911	0.0024699	0.7796183	0.7796160	0.2407340	0.3634440	31494
23	154927581	rs644138	G	A	-0.0022828	0.0022650	0.3135357	0.3135266	0.3007300	0.4635760	31494
23	154929412	rs557132	C	T	-0.0009549	0.0024161	0.6926726	0.6926689	0.2439040	0.3568210	31494
23	154929637	rs35185538	CT	C	-0.0016006	0.0025175	0.5249126	0.5249068	0.2286140	0.3011920	31494
23	154929952	rs4012982	CAA	C	-0.0003699	0.0025417	0.8842969	0.8842958	0.2378770	0.3165560	31494
23	154930230	rs781880	A	G	-0.0009116	0.0024156	0.7058965	0.7058944	0.2443960	0.3618540	31494
23	154930487	rs781879	T	A	0.0035240	0.0085766	0.6811582	0.6811555	0.0182666	0.1263580	31494

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111686 ES:SE:LP:AF:SS:ID   0.00192714:0.00437943:0.180517:0.111686:31494:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117543 ES:SE:LP:AF:SS:ID   -0.000636921:0.0041401:0.0566366:0.117543:31494:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097847 ES:SE:LP:AF:SS:ID   0.00207498:0.00465783:0.183113:0.097847:31494:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158964    ES:SE:LP:AF:SS:ID   -0.00872257:0.0111096:0.364133:0.0158964:31494:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00162322   ES:SE:LP:AF:SS:ID   0.0266364:0.033521:0.369733:0.00162322:31494:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0574672    ES:SE:LP:AF:SS:ID   0.00724659:0.00574491:0.683658:0.0574672:31494:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123279 ES:SE:LP:AF:SS:ID   1.96753e-05:0.00392227:0.00174153:0.123279:31494:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122885 ES:SE:LP:AF:SS:ID   -0.000798451:0.0041764:0.071407:0.122885:31494:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122421 ES:SE:LP:AF:SS:ID   0.000118316:0.003926:0.0105689:0.122421:31494:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00614266   ES:SE:LP:AF:SS:ID   0.00979635:0.0174191:0.241198:0.00614266:31494:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00176573   ES:SE:LP:AF:SS:ID   -0.0227418:0.0358926:0.278731:0.00176573:31494:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868616 ES:SE:LP:AF:SS:ID   -0.000249055:0.00387264:0.0228606:0.868616:31494:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00149179   ES:SE:LP:AF:SS:ID   -0.0157881:0.0352862:0.184045:0.00149179:31494:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123751 ES:SE:LP:AF:SS:ID   7.32988e-05:0.00383922:0.00666607:0.123751:31494:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142984 ES:SE:LP:AF:SS:ID   0.000514288:0.00381149:0.0493105:0.142984:31494:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12384  ES:SE:LP:AF:SS:ID   -7.6885e-05:0.0038336:0.00700534:0.12384:31494:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869898 ES:SE:LP:AF:SS:ID   -0.000372054:0.00373375:0.0359168:0.869898:31494:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874802 ES:SE:LP:AF:SS:ID   -0.000599935:0.00379799:0.0582461:0.874802:31494:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129805 ES:SE:LP:AF:SS:ID   0.000439701:0.00374145:0.0426571:0.129805:31494:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363244    ES:SE:LP:AF:SS:ID   -0.00620023:0.00679601:0.441772:0.0363244:31494:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869435 ES:SE:LP:AF:SS:ID   -0.000471975:0.0037296:0.0460959:0.869435:31494:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869579 ES:SE:LP:AF:SS:ID   -0.000331877:0.00373308:0.031909:0.869579:31494:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869431 ES:SE:LP:AF:SS:ID   -0.000473544:0.00372947:0.0462587:0.869431:31494:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00458892   ES:SE:LP:AF:SS:ID   -0.0237443:0.0204821:0.60844:0.00458892:31494:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00455088   ES:SE:LP:AF:SS:ID   -0.0238435:0.0205465:0.609298:0.00455088:31494:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00559596   ES:SE:LP:AF:SS:ID   -0.0119112:0.0183563:0.286999:0.00559596:31494:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869571 ES:SE:LP:AF:SS:ID   5.14362e-05:0.00372241:0.00481469:0.869571:31494:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126925 ES:SE:LP:AF:SS:ID   -0.000308212:0.00380132:0.0290124:0.126925:31494:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869197 ES:SE:LP:AF:SS:ID   6.47072e-05:0.00371449:0.0060786:0.869197:31494:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868317 ES:SE:LP:AF:SS:ID   0.000396226:0.00370923:0.0386117:0.868317:31494:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869302 ES:SE:LP:AF:SS:ID   0.000163549:0.00371653:0.0155177:0.869302:31494:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869309 ES:SE:LP:AF:SS:ID   0.000168023:0.00371679:0.0159486:0.869309:31494:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869319 ES:SE:LP:AF:SS:ID   0.000174137:0.00371694:0.0165393:0.869319:31494:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869749 ES:SE:LP:AF:SS:ID   -1.94292e-05:0.00372715:0.00181:0.869749:31494:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0993643    ES:SE:LP:AF:SS:ID   0.00148791:0.00433838:0.13571:0.0993643:31494:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00644262   ES:SE:LP:AF:SS:ID   -0.000404444:0.016699:0.00847357:0.00644262:31494:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873989 ES:SE:LP:AF:SS:ID   -0.00034586:0.00378664:0.0328149:0.873989:31494:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862883 ES:SE:LP:AF:SS:ID   0.000718393:0.00370742:0.0724469:0.862883:31494:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868517 ES:SE:LP:AF:SS:ID   0.000180706:0.00374638:0.0170376:0.868517:31494:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86524  ES:SE:LP:AF:SS:ID   0.000698025:0.00374508:0.069487:0.86524:31494:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0996428    ES:SE:LP:AF:SS:ID   0.000164826:0.00449652:0.0128886:0.0996428:31494:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870703 ES:SE:LP:AF:SS:ID   -9.27244e-05:0.00379149:0.00855727:0.870703:31494:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870703 ES:SE:LP:AF:SS:ID   -9.26643e-05:0.00379149:0.00855152:0.870703:31494:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870699 ES:SE:LP:AF:SS:ID   -9.3374e-05:0.00379151:0.00861752:0.870699:31494:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871086 ES:SE:LP:AF:SS:ID   -0.000351688:0.00379322:0.0333276:0.871086:31494:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126451 ES:SE:LP:AF:SS:ID   -0.000465948:0.00379608:0.0446442:0.126451:31494:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106419 ES:SE:LP:AF:SS:ID   0.00191357:0.00412669:0.191882:0.106419:31494:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854426 ES:SE:LP:AF:SS:ID   0.000225753:0.0037105:0.0215976:0.854426:31494:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00154446   ES:SE:LP:AF:SS:ID   0.026257:0.0335629:0.36248:0.00154446:31494:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838692 ES:SE:LP:AF:SS:ID   0.000684567:0.00366168:0.0697144:0.838692:31494:rs376645387