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IEU GWAS information

Trait: Frequency of stair climbing in last 4 weeks.

name	value
id	UKB-a-514
trait	Frequency of stair climbing in last 4 weeks
year	2017
author	Neale
population	European
sex	Males and Females
sample_size	334169
units	SD
build	HG19/GRCh37
group_name	public
access	public
nsnp	10894596
mr	1
batch	UKB-a
sd	NULL
priority	1
consortium	Neale Lab

Report information

name	value
gwas_id	ukb-a-514
bcf_file	ukb-a-514.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 11:16 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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    "FORMAT.3": "<ID=AF,Number=A,Type=Float,Description=\"Alternate allele frequency in the association study\">",
    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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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-a-import/processed/ukb-a-514/ukb-a-514.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-a-import/processed/ukb-a-514/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Sun Feb 16 02:49:27 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-514/ukb-a-514.vcf.gz ...
Read summary statistics for 10877936 SNPs.
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, 1281483 SNPs remain.
After merging with regression SNP LD, 1281483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0342 (0.002)
Lambda GC: 1.2062
Mean Chi^2: 1.2428
Intercept: 1.0191 (0.0072)
Ratio: 0.0785 (0.0295)
Analysis finished at Sun Feb 16 02:51:11 2020
Total time elapsed: 1.0m:43.88s

QC metrics

Metrics

{
    "af_correlation": 0.9533,
    "inflation_factor": 1.1234,
    "mean_EFFECT": 0,
    "n": 334169,
    "n_snps": 10877936,
    "n_clumped_hits": 5,
    "n_p_sig": 163,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 356865,
    "n_est": 332684.7709,
    "ratio_se_n": 0.9978,
    "mean_diff": -4.744e-06,
    "ratio_diff": 5.8893,
    "sd_y_est1": 1.3015,
    "sd_y_est2": 1.2986,
    "r2_sum1": 0.0008,
    "r2_sum2": 0.0005,
    "r2_sum3": 0.0005,
    "r2_sum4": 0.0005,
    "ldsc_nsnp_merge_refpanel_ld": 1281483,
    "ldsc_nsnp_merge_regression_ld": 1281483,
    "ldsc_observed_scale_h2_beta": 0.0342,
    "ldsc_observed_scale_h2_se": 0.002,
    "ldsc_intercept_beta": 1.0191,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.2062,
    "ldsc_mean_chisq": 1.2428,
    "ldsc_ratio": 0.0787
}

Flags

name	value
af_correlation	FALSE
inflation_factor	FALSE
n	FALSE
is_snpid_non_unique	FALSE
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	58	0	10877936	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	1	0	4	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	1	0	4	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	8.598638e+00	5.745666e+00	1.00000e+00	4.000000e+00	8.000000e+00	1.300000e+01	2.200000e+01	▇▅▃▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.911383e+07	5.624931e+07	8.28000e+02	3.287294e+07	6.988889e+07	1.148258e+08	2.492251e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	2.410000e-05	1.915440e-02	-2.12681e-01	-5.469000e-03	-7.400000e-06	5.470800e-03	2.264220e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.371160e-02	1.298660e-02	3.14520e-03	3.885200e-03	7.462200e-03	1.993970e-02	7.162850e-02	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.810135e-01	2.944927e-01	0.00000e+00	2.211948e-01	4.746659e-01	7.362834e-01	1.000000e+00	▇▇▇▆▆
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.810131e-01	2.944929e-01	0.00000e+00	2.211941e-01	4.746657e-01	7.362838e-01	1.000000e+00	▇▇▇▆▆
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.820865e-01	2.503832e-01	1.00090e-03	6.878700e-03	5.191440e-02	2.739880e-01	9.989990e-01	▇▂▁▁▁
numeric	AF_reference	356865	0.9671937	NA	NA	NA	NA	NA	1.877709e-01	2.439191e-01	0.00000e+00	5.191700e-03	7.468050e-02	2.873400e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.341690e+05	0.000000e+00	3.34169e+05	3.341690e+05	3.341690e+05	3.341690e+05	3.341690e+05	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	693731	rs12238997	A	G	0.0030384	0.0052492	0.5627014	0.5627008	0.1169260	0.1417730	334169
1	717587	rs144155419	G	A	0.0138496	0.0141049	0.3261497	0.3261492	0.0143862	0.0045926	334169
1	730087	rs148120343	T	C	0.0026806	0.0073142	0.7139947	0.7139950	0.0554733	0.0127796	334169
1	731718	rs142557973	T	C	0.0025091	0.0049798	0.6143643	0.6143643	0.1216580	0.1543530	334169
1	734349	rs141242758	T	C	0.0024597	0.0049827	0.6215571	0.6215569	0.1215130	0.1525560	334169
1	740284	rs61770167	C	T	-0.0072370	0.0226567	0.7494092	0.7494095	0.0058556	0.0023962	334169
1	742813	rs112573343	C	T	0.0154692	0.0427018	0.7171566	0.7171569	0.0015525	0.1030350	334169
1	753405	rs3115860	C	A	-0.0058440	0.0047341	0.2170391	0.2170383	0.8706760	0.7517970	334169
1	753541	rs2073813	G	A	0.0050242	0.0047459	0.2897630	0.2897620	0.1288330	0.3019170	334169
1	754182	rs3131969	A	G	-0.0056637	0.0047291	0.2310649	0.2310629	0.8703180	0.6785140	334169

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
22	51219387	rs9616832	T	C	0.0030743	0.0060996	0.6142455	0.6142456	0.0729806	0.0654952	334169
22	51219704	rs147475742	G	A	-0.0007774	0.0081784	0.9242680	0.9242680	0.0418225	0.0473243	334169
22	51219766	rs182321900	C	T	0.0303150	0.0420781	0.4712496	0.4712504	0.0014546	NA	334169
22	51220088	rs566371895	G	A	-0.0348386	0.0275560	0.2061299	0.2061282	0.0039843	0.0003994	334169
22	51220146	rs868950473	C	T	0.0189272	0.0414583	0.6480060	0.6480047	0.0015139	NA	334169
22	51221731	rs115055839	T	C	0.0025491	0.0061033	0.6761997	0.6761984	0.0728101	0.0625000	334169
22	51223637	rs375798137	G	A	0.0077335	0.0071868	0.2818961	0.2818955	0.0540289	0.0788738	334169
22	51226692	rs150189434	G	A	0.0348415	0.0430398	0.4182183	0.4182172	0.0013983	0.0155751	334169
22	51229805	rs9616985	T	C	0.0014558	0.0061264	0.8121660	0.8121649	0.0727671	0.0730831	334169
22	51237063	rs3896457	T	C	-0.0024263	0.0037284	0.5152014	0.5152015	0.2968410	0.2050720	334169

bcf preview

1   693731  rs12238997  A   G   .   PASS    AF=0.116926 ES:SE:LP:AF:SS:ID   0.00303843:0.00524922:0.249722:0.116926:334169:rs12238997
1   717587  rs144155419 G   A   .   PASS    AF=0.0143862    ES:SE:LP:AF:SS:ID   0.0138496:0.0141049:0.486583:0.0143862:334169:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0554733    ES:SE:LP:AF:SS:ID   0.00268064:0.00731424:0.146305:0.0554733:334169:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121658 ES:SE:LP:AF:SS:ID   0.00250911:0.00497984:0.211574:0.121658:334169:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121513 ES:SE:LP:AF:SS:ID   0.00245967:0.00498267:0.206519:0.121513:334169:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00585559   ES:SE:LP:AF:SS:ID   -0.00723696:0.0226567:0.125281:0.00585559:334169:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0015525    ES:SE:LP:AF:SS:ID   0.0154692:0.0427018:0.144386:0.0015525:334169:rs112573343
1   753405  rs3115860   C   A   .   PASS    AF=0.870676 ES:SE:LP:AF:SS:ID   -0.00584402:0.00473414:0.663462:0.870676:334169:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.128833 ES:SE:LP:AF:SS:ID   0.00502425:0.00474593:0.537957:0.128833:334169:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.870318 ES:SE:LP:AF:SS:ID   -0.00566369:0.0047291:0.636266:0.870318:334169:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870409 ES:SE:LP:AF:SS:ID   -0.00569759:0.00473134:0.641104:0.870409:334169:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870037 ES:SE:LP:AF:SS:ID   -0.00554624:0.00472891:0.61823:0.870037:334169:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00465304   ES:SE:LP:AF:SS:ID   0.0232907:0.0241148:0.476081:0.00465304:334169:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00464711   ES:SE:LP:AF:SS:ID   0.024393:0.0241806:0.504345:0.00464711:334169:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00590897   ES:SE:LP:AF:SS:ID   -0.0305473:0.0235555:0.710652:0.00590897:334169:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870329 ES:SE:LP:AF:SS:ID   -0.00538723:0.0047207:0.595526:0.870329:334169:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.87002  ES:SE:LP:AF:SS:ID   -0.00533766:0.00470935:0.589999:0.87002:334169:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869421 ES:SE:LP:AF:SS:ID   -0.00513302:0.00470485:0.56024:0.869421:334169:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   -0.00546163:0.00471327:0.6081:0.870219:334169:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   -0.00546639:0.0047136:0.608767:0.870219:334169:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870222 ES:SE:LP:AF:SS:ID   -0.00542697:0.00471375:0.602741:0.870222:334169:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870396 ES:SE:LP:AF:SS:ID   -0.00543333:0.00472584:0.601598:0.870396:334169:rs3131954
1   761732  rs2286139   C   T   .   PASS    AF=0.867743 ES:SE:LP:AF:SS:ID   -0.00395027:0.00470329:0.396891:0.867743:334169:rs2286139
1   766007  rs61768174  A   C   .   PASS    AF=0.106958 ES:SE:LP:AF:SS:ID   0.0028136:0.00523661:0.228365:0.106958:334169:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.763932 ES:SE:LP:AF:SS:ID   -0.000143625:0.0037328:0.0135382:0.763932:334169:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105257 ES:SE:LP:AF:SS:ID   -0.00477828:0.00515271:0.451299:0.105257:334169:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00692766   ES:SE:LP:AF:SS:ID   0.0129165:0.0191455:0.301117:0.00692766:334169:rs12562811
1   769223  rs60320384  C   G   .   PASS    AF=0.128651 ES:SE:LP:AF:SS:ID   0.00445035:0.00473885:0.458833:0.128651:334169:rs60320384
1   769224  rs141644775 G   A   .   PASS    AF=0.00143239   ES:SE:LP:AF:SS:ID   -0.0385024:0.0445426:0.411873:0.00143239:334169:rs141644775
1   770181  rs146076599 A   G   .   PASS    AF=0.00907328   ES:SE:LP:AF:SS:ID   0.0061806:0.0181546:0.134586:0.00907328:334169:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00692321   ES:SE:LP:AF:SS:ID   0.0140825:0.019228:0.333549:0.00692321:334169:rs112563271
1   771823  rs2977605   T   C   .   PASS    AF=0.869934 ES:SE:LP:AF:SS:ID   -0.00490839:0.00471784:0.525551:0.869934:334169:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.128709 ES:SE:LP:AF:SS:ID   0.00443589:0.00473668:0.457152:0.128709:334169:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.870112 ES:SE:LP:AF:SS:ID   -0.00477063:0.00471806:0.505916:0.870112:334169:rs2905039
1   774736  rs28830877  A   C   .   PASS    AF=0.998797 ES:SE:LP:AF:SS:ID   -0.0344844:0.0489712:0.317562:0.998797:334169:rs28830877
1   776556  rs151160018 C   T   .   PASS    AF=0.00851871   ES:SE:LP:AF:SS:ID   -0.00479785:0.0176974:0.104406:0.00851871:334169:rs151160018
1   777122  rs2980319   A   T   .   PASS    AF=0.871122 ES:SE:LP:AF:SS:ID   -0.00349184:0.00472608:0.337241:0.871122:334169:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.0961319    ES:SE:LP:AF:SS:ID   -0.0061701:0.00545715:0.588035:0.0961319:334169:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.127871 ES:SE:LP:AF:SS:ID   0.00326943:0.00474158:0.309365:0.127871:334169:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.127984 ES:SE:LP:AF:SS:ID   0.00331542:0.00473517:0.315313:0.127984:334169:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.870455 ES:SE:LP:AF:SS:ID   -0.00295634:0.00471827:0.274955:0.870455:334169:rs2977612
1   781367  rs149821290 A   C   .   PASS    AF=0.00989772   ES:SE:LP:AF:SS:ID   0.0179269:0.016794:0.543991:0.00989772:334169:rs149821290
1   781845  rs61768199  A   G   .   PASS    AF=0.1044   ES:SE:LP:AF:SS:ID   0.00131322:0.00530543:0.0944723:0.1044:334169:rs61768199
1   782721  rs185280546 G   A   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   -0.0165048:0.0143657:0.601022:0.0143713:334169:rs185280546
1   782981  rs6594026   C   T   .   PASS    AF=0.128338 ES:SE:LP:AF:SS:ID   0.00230491:0.00473772:0.203001:0.128338:334169:rs6594026
1   783193  rs145767270 G   C   .   PASS    AF=0.0143639    ES:SE:LP:AF:SS:ID   -0.0157009:0.0144271:0.558355:0.0143639:334169:rs145767270
1   783194  rs138555831 G   T   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   -0.0158057:0.0144254:0.563492:0.0143713:334169:rs138555831
1   783711  rs184266993 G   A   .   PASS    AF=0.00541372   ES:SE:LP:AF:SS:ID   0.0190449:0.0230546:0.388532:0.00541372:334169:rs184266993
1   785050  rs2905062   G   A   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   -0.00262973:0.00471902:0.238562:0.87014:334169:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.87009  ES:SE:LP:AF:SS:ID   -0.00255426:0.00472203:0.230209:0.87009:334169:rs2980300