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IEU GWAS information

Trait: Birth weight.

name	value
id	ieu-a-1083
pmid	27680694
year	2016
mr	1
note	BW Z-score transformed
trait	Birth weight
category	Risk factor
subcategory	Anthropometric
population	European
sex	Males and females
ncase	NULL
ncontrol	NULL
sample_size	143677
nsnp	16245524
sd	NULL
priority	1
author	Horikoshi
group_name	public
access	public
build	HG19/GRCh37

Report information

name	value
gwas_id	ieu-a-1083
bcf_file	ieu-a-1083.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 23:18 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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}

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/ieu-a-import/processed/ieu-a-1083/ieu-a-1083.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/ieu-a-import/processed/ieu-a-1083/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 16:10:45 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1083/ieu-a-1083.vcf.gz ...
Read summary statistics for 15314235 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, 1284284 SNPs remain.
After merging with regression SNP LD, 1284284 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1012 (0.0063)
Lambda GC: 1.2155
Mean Chi^2: 1.3075
Intercept: 1.0417 (0.0084)
Ratio: 0.1355 (0.0274)
Analysis finished at Tue Feb  4 16:13:14 2020
Total time elapsed: 2.0m:28.88s

QC metrics

Metrics

{
    "af_correlation": 0.9517,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -0.0002,
    "n": 143677,
    "n_snps": 15314235,
    "n_clumped_hits": 50,
    "n_p_sig": 2273,
    "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": 4267567,
    "n_miss_AF_reference": 151471,
    "n_est": 136660.188,
    "ratio_se_n": 0.9753,
    "mean_diff": 0,
    "ratio_diff": 1.3329,
    "sd_y_est1": 1.0669,
    "sd_y_est2": 1.0406,
    "r2_sum1": 0.0186,
    "r2_sum2": 0.0163,
    "r2_sum3": 0.0172,
    "r2_sum4": 0.018,
    "ldsc_nsnp_merge_refpanel_ld": 1284284,
    "ldsc_nsnp_merge_regression_ld": 1284284,
    "ldsc_observed_scale_h2_beta": 0.1012,
    "ldsc_observed_scale_h2_se": 0.0063,
    "ldsc_intercept_beta": 1.0417,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.2155,
    "ldsc_mean_chisq": 1.3075,
    "ldsc_ratio": 0.1356
}

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	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

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	15314234	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	8.931900e+00	6.053154e+00	1.0000	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.867932e+07	5.620043e+07	56.0000	3.245258e+07	6.942720e+07	1.146140e+08	2.492405e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-1.972000e-04	4.560530e-02	-0.9057	-9.500000e-03	-1.000000e-04	9.300000e-03	9.232000e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	3.142940e-02	3.264930e-02	0.0034	5.400000e-03	1.500000e-02	5.290000e-02	4.607000e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.836231e-01	2.937199e-01	0.0000	2.300001e-01	4.799997e-01	7.400005e-01	1.000000e+00	▇▇▇▆▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.836347e-01	2.937143e-01	0.0000	2.252193e-01	4.779042e-01	7.388827e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	4267567	0.7213333	NA	NA	NA	NA	NA	2.062843e-01	2.564199e-01	0.0010	1.400000e-02	8.100000e-02	3.200000e-01	9.990000e-01	▇▂▁▁▁
numeric	AF_reference	151471	0.9901091	NA	NA	NA	NA	NA	1.529414e-01	2.323834e-01	0.0000	1.397800e-03	2.715650e-02	2.160540e-01	1.000000e+00	▇▁▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	1.084943e+05	3.267376e+04	7636.0000	6.778600e+04	1.255800e+05	1.381970e+05	1.436770e+05	▁▁▅▁▇

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	10511	rs534229142	G	A	0.0335	0.1112	0.7600007	0.7632170	NA	0.0001997	67786
1	11008	rs575272151	C	G	0.0198	0.0135	0.1400000	0.1424668	0.09	0.0880591	67786
1	11012	rs544419019	C	G	0.0198	0.0135	0.1400000	0.1424668	0.09	0.0880591	67786
1	13110	rs540538026	G	A	0.0039	0.0175	0.8300000	0.8236467	0.06	0.0267572	67786
1	13116	rs62635286	T	G	-0.0038	0.0107	0.7199992	0.7224846	0.19	0.0970447	67786
1	13273	rs531730856	G	C	0.0056	0.0123	0.6499995	0.6489045	0.13	0.0950479	67786
1	13453	rs568927457	T	C	-0.0516	0.0478	0.2800000	0.2803658	0.01	0.0007987	67786
1	13483	rs554760071	G	C	-0.0864	0.0537	0.1100001	0.1076298	0.01	0.0019968	67786
1	13494	rs574697788	A	G	-0.0117	0.0740	0.8700001	0.8743716	NA	0.0013978	67786
1	13550	rs554008981	G	A	-0.0445	0.0765	0.5600000	0.5607692	NA	0.0033946	67786

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154930230	rs781880	A	G	0.0067	0.0079	0.4000000	0.3963816	0.240	0.3618540	30972
23	155069592	rs35519384	C	T	0.0104	0.0118	0.3800004	0.3781252	0.067	0.0565096	57580
23	155071332	rs6567777	G	A	-0.0097	0.0124	0.4299995	0.4340629	0.060	0.3105030	57611
23	155088980	rs73234571	C	T	0.0047	0.0190	0.8000000	0.8046231	0.026	0.0079872	57619
23	155172982	rs11547143	T	C	0.0070	0.0201	0.7300002	0.7276459	0.020	0.0065895	54120
23	155184453	rs75303099	C	T	0.0048	0.0080	0.5500004	0.5485062	0.160	0.0906550	57583
23	155221513	rs141839773	G	A	0.0256	0.0175	0.1400000	0.1435065	0.029	0.0157748	57666
23	155223923	rs73237067	T	C	0.0017	0.0187	0.9299999	0.9275648	0.030	0.0079872	56925
23	155228901	rs1883079	A	G	0.0062	0.0123	0.6100002	0.6142157	0.939	0.9848240	57560
23	155229962	rs3093535	T	C	-0.0330	0.0283	0.2399999	0.2435830	0.010	0.0047923	57658

bcf preview

1   10511   rs534229142 G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0335:0.1112:0.119186:67786:rs534229142
1   11008   rs575272151 C   G   .   PASS    AF=0.09 ES:SE:LP:AF:SS:ID   0.0198:0.0135:0.853872:0.09:67786:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.09 ES:SE:LP:AF:SS:ID   0.0198:0.0135:0.853872:0.09:67786:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.06 ES:SE:LP:AF:SS:ID   0.0039:0.0175:0.0809219:0.06:67786:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.19 ES:SE:LP:AF:SS:ID   -0.0038:0.0107:0.142668:0.19:67786:rs62635286
1   13273   rs531730856 G   C   .   PASS    AF=0.13 ES:SE:LP:AF:SS:ID   0.0056:0.0123:0.187087:0.13:67786:rs531730856
1   13453   rs568927457 T   C   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.0516:0.0478:0.552842:0.01:67786:rs568927457
1   13483   rs554760071 G   C   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.0864:0.0537:0.958607:0.01:67786:rs554760071
1   13494   rs574697788 A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0117:0.074:0.0604807:67786:rs574697788
1   13550   rs554008981 G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0445:0.0765:0.251812:67786:rs554008981
1   14464   rs546169444 A   T   .   PASS    AF=0.16 ES:SE:LP:AF:SS:ID   -0.0175:0.0112:0.920819:0.16:67786:rs546169444
1   14604   rs541940975 A   G   .   PASS    AF=0.19 ES:SE:LP:AF:SS:ID   0.0046:0.0103:0.187087:0.19:67786:rs541940975
1   14933   rs199856693 G   A   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.0076:0.019:0.161151:0.05:67786:rs199856693
1   15245   rs576044687 C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0921:0.1049:0.420216:67786:rs576044687
1   15585   rs533630043 G   A   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   0.0765:0.0494:0.920819:0.01:67786:rs533630043
1   15644   rs564003018 G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0159:0.07:0.0861861:67786:rs564003018
1   15774   rs374029747 G   A   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.0328:0.0591:0.236572:0.01:67786:rs374029747
1   15820   rs2691315   G   T   .   PASS    AF=0.27 ES:SE:LP:AF:SS:ID   -0.0079:0.0094:0.39794:0.27:67786:rs2691315
1   16142   rs548165136 G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0896:0.075:0.638272:67786:rs548165136
1   16949   rs199745162 A   C   .   PASS    AF=0.02 ES:SE:LP:AF:SS:ID   0.0647:0.0279:1.69897:0.02:67786:rs199745162
1   18643   rs564023708 G   A   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.0483:0.0511:0.468521:0.01:67786:rs564023708
1   18849   rs533090414 C   G   .   PASS    AF=0.975    ES:SE:LP:AF:SS:ID   0.0001:0.0235:-0:0.975:67786:rs533090414
1   30923   rs806731    G   T   .   PASS    AF=0.904    ES:SE:LP:AF:SS:ID   0.0025:0.0141:0.0655015:0.904:67786:rs806731
1   47159   rs540662756 T   C   .   PASS    AF=0.07 ES:SE:LP:AF:SS:ID   -0.042:0.0168:1.92082:0.07:67786:rs540662756
1   49315   rs567788405 T   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0203:0.1241:0.0604807:67786:rs567788405
1   49318   rs536836601 A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0564:0.0976:0.251812:67786:rs536836601
1   49343   rs553572247 T   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0918:0.0895:0.522879:67786:rs553572247
1   49554   rs539322794 A   G   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   0.0055:0.0138:0.161151:0.1:67786:rs539322794
1   50891   rs542415070 T   C   .   PASS    .   ES:SE:LP:SS:ID  -0.1444:0.076:1.24413:67786:rs542415070
1   51047   rs559500163 A   T   .   PASS    .   ES:SE:LP:SS:ID  0.0268:0.102:0.102373:67786:rs559500163
1   51049   rs528344458 A   C   .   PASS    .   ES:SE:LP:SS:ID  0.0268:0.102:0.102373:67786:rs528344458
1   51050   rs551668143 A   T   .   PASS    .   ES:SE:LP:SS:ID  0.0268:0.102:0.102373:67786:rs551668143
1   51053   rs565211799 G   T   .   PASS    .   ES:SE:LP:SS:ID  0.0268:0.102:0.102373:67786:rs565211799
1   51479   rs116400033 T   A   .   PASS    AF=0.21 ES:SE:LP:AF:SS:ID   -0.0025:0.0099:0.09691:0.21:67786:rs116400033
1   51762   rs559190862 A   G   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   0.0383:0.0453:0.39794:0.01:67786:rs559190862
1   51765   rs575564077 C   G   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   0.0383:0.0454:0.39794:0.01:67786:rs575564077
1   52238   rs2691277   T   G   .   PASS    AF=0.978    ES:SE:LP:AF:SS:ID   0.0519:0.0292:1.12494:0.978:67786:rs2691277
1   52253   rs530867301 C   G   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.1075:0.059:1.16115:0.01:67786:rs530867301
1   54353   rs140052487 C   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0732:0.08:0.443698:67786:rs140052487
1   54354   rs569165477 C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0038:0.0747:0.0177288:67786:rs569165477
1   54490   rs141149254 G   A   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.0007:0.0111:0.0222764:0.15:67786:rs141149254
1   54591   rs561234294 A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0257:0.0839:0.119186:67786:rs561234294
1   54716   rs569128616 C   T   .   PASS    AF=0.43 ES:SE:LP:AF:SS:ID   0.0047:0.0083:0.236572:0.43:67786:rs569128616
1   54830   rs552733564 G   A   .   PASS    .   ES:SE:LP:SS:ID  0.1137:0.1026:0.568636:67786:rs552733564
1   54945   rs569799965 C   A   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.0752:0.0506:0.853872:0.01:67786:rs569799965
1   55136   rs574692163 T   C   .   PASS    .   ES:SE:LP:SS:ID  -0.017:0.1:0.0655015:67786:rs574692163
1   55164   rs3091274   C   A   .   PASS    AF=0.983    ES:SE:LP:AF:SS:ID   0.0277:0.0322:0.408935:0.983:67786:rs3091274
1   55326   rs3107975   T   C   .   PASS    AF=0.02 ES:SE:LP:AF:SS:ID   0.0347:0.0336:0.522879:0.02:67786:rs3107975
1   55405   rs372455836 C   T   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   0.0448:0.0569:0.366532:0.01:67786:rs372455836
1   55427   rs183189405 T   C   .   PASS    .   ES:SE:LP:SS:ID  0.019:0.1168:0.0604807:67786:rs183189405