IEU GWAS QC Report

name	value
id	UKB-b-3357
trait	Birth weight of first child
note	2744: Output from GWAS pipeline using Phesant derived variables from UKBiobank
year	2018
author	Ben Elsworth
population	European
sex	Males and Females
sample_size	200272
units	SD
build	HG19/GRCh37
group_name	public
access	public
nsnp	9851867
mr	1
category	Categorical Ordered
batch	UKB-b
sd	NULL
priority	1
consortium	MRC-IEU

name	value
gwas_id	ukb-b-3357
bcf_file	ukb-b-3357.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-09 13:15 BST
build_version	run_igd-8f4f4c9-2020-05-09

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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3357/UKB-b-3357_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3357/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3357/UKB-b-3357_data.vcf.gz ...
Read summary statistics for 9499677 SNPs.
Dropped 11626 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1288365 SNPs remain.
After merging with regression SNP LD, 1288365 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1025 (0.0052)
Lambda GC: 1.2968
Mean Chi^2: 1.4422
Intercept: 1.0361 (0.0091)
Ratio: 0.0817 (0.0205)
Analysis finished at Thu Oct 17 14:45:08 2019
Total time elapsed: 1.0m:44.55s

{
    "af_correlation": 0.9491,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 70,
    "n_p_sig": 3960,
    "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": 133524,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1288365,
    "ldsc_nsnp_merge_regression_ld": 1288365,
    "ldsc_observed_scale_h2_beta": 0.1025,
    "ldsc_observed_scale_h2_se": 0.0052,
    "ldsc_intercept_beta": 1.0361,
    "ldsc_intercept_se": 0.0091,
    "ldsc_lambda_gc": 1.2968,
    "ldsc_mean_chisq": 1.4422,
    "ldsc_ratio": 0.0816
}

name	value
name	value
af_correlation	FALSE
inflation_factor	FALSE
n	TRUE
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

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	logical.mean	logical.count	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	logical.mean	logical.count	numeric.mean	numeric.sd	numeric.p0	numeric.p25	numeric.p50	numeric.p75	numeric.p100	numeric.hist
character	ID	0	1.0000000	3	58	0	9488111	0	NA	NA	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	NA	NA
character	ALT	0	1.0000000	1	1	0	4	0	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
logical	N	9499677	0.0000000	NA	NA	NA	NA	NA	NaN	:	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	8.629569e+00	5.751976e+00	1.0000000	4.000000e+00	8.000000e+00	1.300000e+01	2.200000e+01	▇▅▃▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	7.883561e+07	5.630796e+07	828.0000000	3.254173e+07	6.942154e+07	1.145653e+08	2.492385e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	-1.172000e-04	1.563390e-02	-0.2642490	-5.812400e-03	-3.460000e-05	5.694600e-03	2.795050e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	1.155270e-02	9.681500e-03	0.0036449	4.420200e-03	7.130300e-03	1.571680e-02	1.298580e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	4.683192e-01	2.980006e-01	0.0000000	2.000000e-01	4.600002e-01	7.300002e-01	1.000000e+00	▇▆▆▆▆
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	4.683189e-01	2.979753e-01	0.0000000	2.020421e-01	4.588753e-01	7.262474e-01	9.999997e-01	▇▆▆▆▆
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	2.098262e-01	2.573296e-01	0.0017480	1.577900e-02	8.689200e-02	3.284040e-01	9.982520e-01	▇▂▁▁▁
numeric	AF_reference	133524	0.9859444	NA	NA	NA	NA	NA	NA	NA	2.115048e-01	2.490511e-01	0.0000000	1.337860e-02	1.064300e-01	3.296730e-01	1.000000e+00	▇▂▁▁▁

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	49298	rs200943160	T	C	0.0034520	0.0067194	0.6100002	0.6074400	0.623274	0.7821490	NA
1	54676	rs2462492	C	T	0.0051242	0.0066408	0.4400003	0.4403323	0.401252	NA	NA
1	86028	rs114608975	T	C	-0.0095730	0.0106569	0.3700002	0.3690313	0.103568	0.0277556	NA
1	91536	rs6702460	G	T	0.0004633	0.0065480	0.9400001	0.9435904	0.456978	0.4207270	NA
1	234313	rs8179466	C	T	0.0031829	0.0129719	0.8100000	0.8061691	0.074316	NA	NA
1	534192	rs6680723	C	T	0.0058887	0.0074882	0.4299995	0.4316371	0.241128	NA	NA
1	546697	rs12025928	A	G	-0.0077630	0.0093430	0.4100001	0.4060365	0.913547	NA	NA
1	693731	rs12238997	A	G	0.0068082	0.0062630	0.2800000	0.2770165	0.116834	0.1417730	NA
1	705882	rs72631875	G	A	-0.0089105	0.0092327	0.3300000	0.3344942	0.066796	0.0315495	NA
1	706368	rs55727773	A	G	-0.0053818	0.0046479	0.2500000	0.2469011	0.514864	0.2751600	NA

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	51219704	rs147475742	G	A	-0.0120240	0.0097768	0.2200002	0.2187541	0.041821	0.0473243	NA
22	51219766	rs182321900	C	T	-0.0124441	0.0469407	0.7899998	0.7909305	0.001838	NA	NA
22	51220146	rs868950473	C	T	-0.0057628	0.0464117	0.9000000	0.9011832	0.001884	NA	NA
22	51221190	rs369304721	G	A	-0.0057576	0.0097720	0.5600000	0.5557369	0.049495	NA	NA
22	51221731	rs115055839	T	C	-0.0057886	0.0072988	0.4299995	0.4277309	0.073109	0.0625000	NA
22	51222100	rs114553188	G	T	0.0125218	0.0085642	0.1400000	0.1437121	0.054687	0.0880591	NA
22	51223637	rs375798137	G	A	0.0119478	0.0086062	0.1700000	0.1650499	0.054312	0.0788738	NA
22	51229805	rs9616985	T	C	-0.0055970	0.0073239	0.4400003	0.4447420	0.072992	0.0730831	NA
22	51232488	rs376461333	A	G	0.0106449	0.0171509	0.5300002	0.5348225	0.020173	NA	NA
22	51237063	rs3896457	T	C	-0.0042624	0.0044666	0.3400001	0.3399384	0.298201	0.2050720	NA

1   49298   rs10399793  T   C   .   PASS    AF=0.623274 ES:SE:LP:AF:ID  0.00345196:0.00671939:0.21467:0.623274:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.401252 ES:SE:LP:AF:ID  0.00512424:0.00664078:0.356547:0.401252:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103568 ES:SE:LP:AF:ID  -0.00957298:0.0106569:0.431798:0.103568:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456978 ES:SE:LP:AF:ID  0.000463323:0.006548:0.0268721:0.456978:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074316 ES:SE:LP:AF:ID  0.00318293:0.0129719:0.091515:0.074316:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241128 ES:SE:LP:AF:ID  0.00588867:0.0074882:0.366532:0.241128:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913547 ES:SE:LP:AF:ID  -0.00776296:0.00934296:0.387216:0.913547:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116834 ES:SE:LP:AF:ID  0.00680818:0.00626301:0.552842:0.116834:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066796 ES:SE:LP:AF:ID  -0.00891047:0.00923268:0.481486:0.066796:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514864 ES:SE:LP:AF:ID  -0.0053818:0.00464786:0.60206:0.514864:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032861 ES:SE:LP:AF:ID  0.0172831:0.0117367:0.853872:0.032861:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036455 ES:SE:LP:AF:ID  0.018746:0.0106646:1.10237:0.036455:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036538 ES:SE:LP:AF:ID  0.0179763:0.01063:1.04096:0.036538:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036228 ES:SE:LP:AF:ID  0.019755:0.0107088:1.18709:0.036228:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01626  ES:SE:LP:AF:ID  0.00157618:0.0165072:0.0362122:0.01626:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036761 ES:SE:LP:AF:ID  0.017147:0.0105897:0.958607:0.036761:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036853 ES:SE:LP:AF:ID  0.0187866:0.0105546:1.12494:0.036853:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101152 ES:SE:LP:AF:ID  -0.00932168:0.00766102:0.657577:0.101152:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959377 ES:SE:LP:AF:ID  -0.0134501:0.0101826:0.721246:0.959377:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031567 ES:SE:LP:AF:ID  0.00218991:0.0182795:0.0457575:0.031567:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053453 ES:SE:LP:AF:ID  -0.00237679:0.0146059:0.0604807:0.053453:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036396 ES:SE:LP:AF:ID  0.0176924:0.0106167:1.01773:0.036396:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036743 ES:SE:LP:AF:ID  0.0171199:0.010518:1:0.036743:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842995 ES:SE:LP:AF:ID  -0.00754899:0.00543672:0.79588:0.842995:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056048 ES:SE:LP:AF:ID  0.00281568:0.00878774:0.124939:0.056048:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122806 ES:SE:LP:AF:ID  0.00596702:0.00594074:0.49485:0.122806:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025637 ES:SE:LP:AF:ID  -0.0043955:0.0146632:0.119186:0.025637:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122025 ES:SE:LP:AF:ID  0.00621825:0.00594344:0.522879:0.122025:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13283  ES:SE:LP:AF:ID  0.0101632:0.00585343:1.08092:0.13283:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011144 ES:SE:LP:AF:ID  0.015001:0.0213205:0.318759:0.011144:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.00588  ES:SE:LP:AF:ID  -0.0172389:0.0269615:0.283997:0.00588:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002204 ES:SE:LP:AF:ID  -0.00704331:0.0469433:0.0555173:0.002204:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036653 ES:SE:LP:AF:ID  0.0179383:0.0104125:1.07058:0.036653:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838701 ES:SE:LP:AF:ID  -0.00714521:0.00526337:0.769551:0.838701:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83834  ES:SE:LP:AF:ID  -0.00702891:0.00525836:0.744727:0.83834:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869408 ES:SE:LP:AF:ID  -0.00435378:0.00563792:0.356547:0.869408:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130225 ES:SE:LP:AF:ID  0.00501701:0.00565045:0.431798:0.130225:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03715  ES:SE:LP:AF:ID  0.0150646:0.0102375:0.853872:0.03715:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037415 ES:SE:LP:AF:ID  0.013996:0.0101681:0.769551:0.037415:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868768 ES:SE:LP:AF:ID  -0.00430323:0.00562847:0.356547:0.868768:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868838 ES:SE:LP:AF:ID  -0.00421662:0.00563036:0.346787:0.868838:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037352 ES:SE:LP:AF:ID  0.0142868:0.0102156:0.79588:0.037352:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868769 ES:SE:LP:AF:ID  -0.00421605:0.00562833:0.346787:0.868769:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.004969 ES:SE:LP:AF:ID  -0.0322709:0.0294254:0.568636:0.004969:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.004934 ES:SE:LP:AF:ID  -0.0312046:0.0295052:0.537602:0.004934:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837797 ES:SE:LP:AF:ID  -0.0067128:0.00524357:0.69897:0.837797:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037366 ES:SE:LP:AF:ID  0.0151618:0.0102308:0.853872:0.037366:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838438 ES:SE:LP:AF:ID  -0.00660861:0.0052584:0.677781:0.838438:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013714 ES:SE:LP:AF:ID  0.0102294:0.0184154:0.236572:0.013714:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005598 ES:SE:LP:AF:ID  0.0300086:0.0281867:0.537602:0.005598:rs184270342

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