IEU GWAS QC Report

name	value
group_name	public
author	Vuckovic, D
sample_size	563946
consortium	Blood Cell Consortium
subcategory	Immune system
build	HG19/GRCh37
trait	white blood cell count
priority	0
sex	Males and Females
id	ieu-b-30
mr	1
year	2020
population	European
category	Continuous

name	value
gwas_id	ieu-b-30
bcf_file	ieu-b-30.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2021-02-24 20:44 UTC
build_version	master-2dbfcc4-2020-10-23

manhattan_plot

qq_plot

af_plot

pz_plot

beta_std_plot

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}

*********************************************************************
* 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 /data/cromwell-executions/qc/57e34be8-352f-4f93-9d1d-0b7a687e067e/call-ldsc/inputs/562856187/ieu-b-30.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-30/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Aug 21 01:29:43 2020
Reading summary statistics from /data/cromwell-executions/qc/57e34be8-352f-4f93-9d1d-0b7a687e067e/call-ldsc/inputs/562856187/ieu-b-30.vcf.gz ...
Read summary statistics for 27090670 SNPs.
Dropped 128540 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/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 /data/ref/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1220780 SNPs remain.
After merging with regression SNP LD, 1220780 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1774 (0.0112)
Lambda GC: 1.9241
Mean Chi^2: 3.4242
Intercept: 1.3376 (0.0289)
Ratio: 0.1392 (0.0119)
Analysis finished at Fri Aug 21 01:34:34 2020
Total time elapsed: 4.0m:51.01s

{
    "af_correlation": 0.9668,
    "inflation_factor": 1.2184,
    "mean_EFFECT": 0.0001,
    "n": 562243,
    "n_snps": 27090906,
    "n_clumped_hits": 507,
    "n_p_sig": 117809,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 67997,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 2142622,
    "n_est": 401285.6742,
    "ratio_se_n": 0.8448,
    "mean_diff": -0.0001,
    "ratio_diff": 1.2433,
    "sd_y_est1": 1.3843,
    "sd_y_est2": 1.1695,
    "r2_sum1": 0.0967,
    "r2_sum2": 0.0505,
    "r2_sum3": 0.0707,
    "r2_sum4": 0.0991,
    "ldsc_nsnp_merge_refpanel_ld": 1220780,
    "ldsc_nsnp_merge_regression_ld": 1220780,
    "ldsc_observed_scale_h2_beta": 0.1774,
    "ldsc_observed_scale_h2_se": 0.0112,
    "ldsc_intercept_beta": 1.3376,
    "ldsc_intercept_se": 0.0289,
    "ldsc_lambda_gc": 1.9241,
    "ldsc_mean_chisq": 3.4242,
    "ldsc_ratio": 0.1393
}

name	value
name	value
af_correlation	FALSE
inflation_factor	TRUE
n	FALSE
is_snpid_non_unique	TRUE
mean_EFFECT_nonfinite	FALSE
mean_EFFECT_05	FALSE
mean_EFFECT_01	FALSE
mean_chisq	TRUE
n_p_sig	TRUE
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

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 $\beta_j$

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
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	48	0.9999982	3	64	0	27089072	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	8.652631e+00	5.781882e+00	1.000000	4.000000e+00	8.000000e+00	1.300000e+01	2.200000e+01	▇▅▃▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.898692e+07	5.625017e+07	56.000000	3.283874e+07	6.963686e+07	1.148587e+08	2.492398e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	1.297000e-04	1.792292e-01	-74.136800	-2.199700e-02	5.700000e-05	2.253200e-02	4.481330e+01	▁▁▁▇▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	8.649400e-02	1.642921e-01	0.001799	6.855000e-03	4.628900e-02	1.180820e-01	8.903050e+01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.663526e-01	3.000334e-01	0.000000	1.983741e-01	4.565728e-01	7.267098e-01	1.000000e+00	▇▆▆▆▆
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.663522e-01	3.000346e-01	0.000000	1.983951e-01	4.565628e-01	7.266991e-01	1.000000e+00	▇▆▆▆▆
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	7.845300e-02	1.921642e-01	0.000025	1.720000e-04	8.200000e-04	2.239480e-02	9.999750e-01	▇▁▁▁▁
numeric	AF_reference	2142622	0.9209099	NA	NA	NA	NA	NA	8.923040e-02	1.918093e-01	0.000000	1.397800e-03	7.188500e-03	5.211660e-02	1.000000e+00	▇▁▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	4.582429e+05	1.388749e+05	683.000000	4.444420e+05	4.890530e+05	5.581440e+05	5.622430e+05	▁▁▁▃▇

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	16141	rs529651976	C	T	0.204886	0.210882	0.3312547	0.3312660	0.000523	0.0025958	36410
1	49298	rs200943160	T	C	0.013640	0.011139	0.2207257	0.2207537	0.823664	0.7821490	36410
1	54353	rs140052487	C	A	0.082686	0.098517	0.4012989	0.4012971	0.001861	0.0089856	36410
1	54564	rs558796213	G	T	0.081243	0.114214	0.4768974	0.4768843	0.000141	0.0041933	408032
1	54591	rs561234294	A	G	-0.118643	0.118275	0.3157941	0.3158071	0.001561	0.0035942	36410
1	54712	rs552304420	T	C	0.086113	0.043579	0.0481682	0.0481524	0.010412	0.0109824	36410
1	54815	rs568686875	T	C	-0.028470	0.184712	0.8774860	0.8775058	0.000480	0.0019968	36410
1	55326	rs3107975	T	C	-0.013205	0.032807	0.6873374	0.6873120	0.019657	0.0459265	36410
1	55351	rs531766459	T	A	-0.044334	0.060044	0.4603127	0.4602966	0.000503	0.0007987	408032
1	55405	rs372455836	C	T	0.049440	0.055084	0.3694214	0.3694317	0.006910	0.0075879	36410

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
22	51237137	rs534739169	A	C	-0.079274	0.087784	0.3664933	0.3664954	0.000215	0.0001997	444442
22	51237410	rs530437591	G	A	0.013528	0.056995	0.8123689	0.8123821	0.000358	0.0017971	444442
22	51237486	rs149820726	G	C	0.063270	0.157960	0.6887744	0.6887556	0.000536	0.0025958	36410
22	51238275	rs202031343	C	T	0.148257	0.102879	0.1495481	0.1495617	0.001263	0.0009984	36410
22	51238307	rs577028785	A	G	0.006675	0.226187	0.9764459	0.9764571	0.000261	0.0015974	36410
22	51238349	rs546389903	T	C	-0.193449	0.284541	0.4966072	0.4965910	0.000165	0.0013978	36410
22	51238660	rs569936315	A	G	-0.047204	0.151800	0.7558385	0.7558297	0.000066	0.0167732	444442
22	51239586	rs535432390	T	G	-0.027704	0.020913	0.1852371	0.1852620	0.002968	0.0001997	490028
22	51239678	rs573137567	G	T	0.057569	0.084080	0.4935475	0.4935376	0.001895	0.0233626	36410
22	51244163	rs199560686	A	G	0.008184	0.205218	0.9681751	0.9681892	0.000054	0.0077875	444442

1   16141   rs529651976 C   T   .   PASS    AF=0.000523 ES:SE:LP:AF:SS:ID   0.204886:0.210882:0.479838:0.000523:36410:rs529651976
1   49298   rs10399793  T   C   .   PASS    AF=0.823664 ES:SE:LP:AF:SS:ID   0.01364:0.011139:0.656147:0.823664:36410:rs10399793
1   54353   rs140052487 C   A   .   PASS    AF=0.001861 ES:SE:LP:AF:SS:ID   0.082686:0.098517:0.396532:0.001861:36410:rs140052487
1   54564   rs558796213 G   T   .   PASS    AF=0.000141 ES:SE:LP:AF:SS:ID   0.081243:0.114214:0.321575:0.000141:408032:rs558796213
1   54591   rs561234294 A   G   .   PASS    AF=0.001561 ES:SE:LP:AF:SS:ID   -0.118643:0.118275:0.500596:0.001561:36410:rs561234294
1   54712   rs573184866 T   C   .   PASS    AF=0.010412 ES:SE:LP:AF:SS:ID   0.086113:0.043579:1.31724:0.010412:36410:rs573184866
1   54815   rs568686875 T   C   .   PASS    AF=0.00048  ES:SE:LP:AF:SS:ID   -0.02847:0.184712:0.0567598:0.00048:36410:rs568686875
1   55326   rs3107975   T   C   .   PASS    AF=0.019657 ES:SE:LP:AF:SS:ID   -0.013205:0.032807:0.16283:0.019657:36410:rs3107975
1   55351   rs531766459 T   A   .   PASS    AF=0.000503 ES:SE:LP:AF:SS:ID   -0.044334:0.060044:0.336947:0.000503:408032:rs531766459
1   55405   rs372455836 C   T   .   PASS    AF=0.00691  ES:SE:LP:AF:SS:ID   0.04944:0.055084:0.432478:0.00691:36410:rs372455836
1   55416   rs193242050 G   A   .   PASS    AF=9.4e-05  ES:SE:LP:AF:SS:ID   0.024508:0.162627:0.0554226:9.4e-05:444442:rs193242050
1   55427   rs183189405 T   C   .   PASS    AF=0.002378 ES:SE:LP:AF:SS:ID   -0.029572:0.10776:0.105819:0.002378:36410:rs183189405
1   56586   rs541979596 G   A   .   PASS    AF=0.001497 ES:SE:LP:AF:SS:ID   -0.087601:0.130091:0.300406:0.001497:36410:rs541979596
1   57095   rs553759011 T   C   .   PASS    AF=3.6e-05  ES:SE:LP:AF:SS:ID   0.222206:0.223963:0.493348:3.6e-05:408032:rs553759011
1   57183   rs368339209 A   G   .   PASS    AF=2.8e-05  ES:SE:LP:AF:SS:ID   0.27325:0.367894:0.339467:2.8e-05:408032:rs368339209
1   61804   rs567421057 G   A   .   PASS    AF=7.4e-05  ES:SE:LP:AF:SS:ID   0.239626:0.164391:0.838866:7.4e-05:408032:rs567421057
1   61993   rs190553843 C   T   .   PASS    AF=9.5e-05  ES:SE:LP:AF:SS:ID   0.192671:0.157861:0.65316:9.5e-05:444442:rs190553843
1   62124   rs528478839 G   A   .   PASS    AF=0.00018  ES:SE:LP:AF:SS:ID   0.397854:0.393755:0.505449:0.00018:36410:rs528478839
1   62157   rs10399597  G   A   .   PASS    AF=0.00014  ES:SE:LP:AF:SS:ID   0.151662:0.096676:0.932951:0.00014:444442:rs10399597
1   62509   rs534313866 T   C   .   PASS    AF=0.000544 ES:SE:LP:AF:SS:ID   0.198491:0.212872:0.454569:0.000544:36410:rs534313866
1   62617   rs543126209 T   G   .   PASS    AF=9.3e-05  ES:SE:LP:AF:SS:ID   0.036725:0.16193:0.0858817:9.3e-05:444442:rs543126209
1   64670   rs545257650 A   G   .   PASS    AF=0.000147 ES:SE:LP:AF:SS:ID   -0.104839:0.117257:0.430315:0.000147:444442:rs545257650
1   64908   rs540391097 A   G   .   PASS    AF=0.000642 ES:SE:LP:AF:SS:ID   -0.034953:0.053777:0.28758:0.000642:444442:rs540391097
1   65009   rs563233355 G   A   .   PASS    AF=0.000292 ES:SE:LP:AF:SS:ID   0.091127:0.07334:0.669542:0.000292:444442:rs563233355
1   65974   rs531923826 A   G   .   PASS    AF=0.004619 ES:SE:LP:AF:SS:ID   -0.085504:0.068244:0.677332:0.004619:36410:rs531923826
1   67179   rs149952626 C   G   .   PASS    AF=0.00014  ES:SE:LP:AF:SS:ID   -0.108757:0.344577:0.123612:0.00014:36410:rs149952626
1   67223   rs78676975  C   T   .   PASS    AF=0.000484 ES:SE:LP:AF:SS:ID   0.071448:0.245207:0.113077:0.000484:36410:rs78676975
1   67224   rs566526215 G   A   .   PASS    AF=0.000161 ES:SE:LP:AF:SS:ID   0.004988:0.124951:0.0140609:0.000161:444442:rs566526215
1   67631   rs533896527 G   C   .   PASS    AF=0.0002   ES:SE:LP:AF:SS:ID   -0.059728:0.095267:0.27514:0.0002:444442:rs533896527
1   69594   rs144967600 T   C   .   PASS    AF=0.00074  ES:SE:LP:AF:SS:ID   -0.10272:0.185953:0.236049:0.00074:36410:rs144967600
1   69610   rs376022826 C   T   .   PASS    AF=0.000218 ES:SE:LP:AF:SS:ID   0.103237:0.378603:0.105075:0.000218:36410:rs376022826
1   70317   rs570011908 G   A   .   PASS    AF=0.000635 ES:SE:LP:AF:SS:ID   -0.006827:0.2034:0.011793:0.000635:36410:rs570011908
1   72526   rs547237130 A   G   .   PASS    AF=0.038254 ES:SE:LP:AF:SS:ID   0.004603:0.022997:0.0750269:0.038254:36410:rs547237130
1   73093   rs535508237 G   A   .   PASS    AF=0.004009 ES:SE:LP:AF:SS:ID   -0.015467:0.068491:0.0854855:0.004009:36410:rs535508237
1   77763   rs557457745 G   A   .   PASS    AF=0.005348 ES:SE:LP:AF:SS:ID   -0.06144:0.062396:0.488425:0.005348:36410:rs557457745
1   78942   rs372315362 C   G   .   PASS    AF=0.00803  ES:SE:LP:AF:SS:ID   0.008269:0.048369:0.0633656:0.00803:36410:rs372315362
1   79033   rs2462495   A   G   .   PASS    AF=0.998702 ES:SE:LP:AF:SS:ID   -0.011079:0.047298:0.0889538:0.998702:408032:rs2462495
1   79137   rs143777184 A   T   .   PASS    AF=0.001023 ES:SE:LP:AF:SS:ID   -0.023925:0.043042:0.237819:0.001023:444442:rs143777184
1   79188   rs534350410 G   T   .   PASS    AF=0.001123 ES:SE:LP:AF:SS:ID   -0.123423:0.145978:0.400295:0.001123:36410:rs534350410
1   82957   rs189774606 C   T   .   PASS    AF=0.000468 ES:SE:LP:AF:SS:ID   0.019902:0.056268:0.140519:0.000468:444442:rs189774606
1   82961   rs537801787 C   T   .   PASS    AF=0.000513 ES:SE:LP:AF:SS:ID   0.059909:0.211141:0.109796:0.000513:36410:rs537801787
1   82994   rs574556077 A   G   .   PASS    AF=0.000185 ES:SE:LP:AF:SS:ID   0.107309:0.316355:0.134028:0.000185:36410:rs574556077
1   83170   rs562997564 G   T   .   PASS    AF=0.001239 ES:SE:LP:AF:SS:ID   0.176298:0.138248:0.694202:0.001239:36410:rs562997564
1   83771   rs189906733 T   G   .   PASS    AF=0.000664 ES:SE:LP:AF:SS:ID   -0.012065:0.049139:0.0936407:0.000664:444442:rs189906733
1   84139   rs183605470 A   T   .   PASS    AF=0.020806 ES:SE:LP:AF:SS:ID   -0.005258:0.031329:0.0621337:0.020806:36410:rs183605470
1   84618   rs576633512 C   T   .   PASS    AF=0.000712 ES:SE:LP:AF:SS:ID   -0.035167:0.184108:0.0713466:0.000712:36410:rs576633512
1   85622   rs185273034 A   T   .   PASS    AF=0.001245 ES:SE:LP:AF:SS:ID   0.131455:0.137799:0.468402:0.001245:36410:rs185273034
1   85892   rs147185795 A   G   .   PASS    AF=0.000455 ES:SE:LP:AF:SS:ID   -0.066499:0.064435:0.519928:0.000455:444442:rs147185795
1   86028   rs114608975 T   C   .   PASS    AF=0.061235 ES:SE:LP:AF:SS:ID   -0.015394:0.018023:0.40559:0.061235:36410:rs114608975
1   86192   rs548281277 G   A   .   PASS    AF=0.03455  ES:SE:LP:AF:SS:ID   0.005175:0.024172:0.0806719:0.03455:36410:rs548281277

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