IEU GWAS QC Report

name	value
id	ieu-a-7
pmid	26343387
year	2015
mr	1
note	NULL
trait	Coronary heart disease
category	Disease
subcategory	Cardiovascular
population	Mixed
sex	Males and females
ncase	60801
ncontrol	123504
sample_size	184305
nsnp	9455779
sd	NULL
priority	1
author	Nikpay
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-7
bcf_file	ieu-a-7.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 10:23 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/dev/ieu-a-import/processed/ieu-a-7/ieu-a-7.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-7/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 09:21:15 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-7/ieu-a-7.vcf.gz ...
Read summary statistics for 8479693 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, 1286923 SNPs remain.
After merging with regression SNP LD, 1286923 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0659 (0.0042)
Lambda GC: 1.0465
Mean Chi^2: 1.1242
Intercept: 0.8866 (0.0072)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 09:22:34 2020
Total time elapsed: 1.0m:18.76s

{
    "af_correlation": 0.9621,
    "inflation_factor": 1.0011,
    "mean_EFFECT": 0.0006,
    "n": 184305,
    "n_snps": 8479693,
    "n_clumped_hits": 41,
    "n_p_sig": 2022,
    "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": 204800,
    "n_est": 177406.6453,
    "ratio_se_n": 0.9811,
    "mean_diff": -0.0004,
    "ratio_diff": 22.3357,
    "sd_y_est1": 2.9757,
    "sd_y_est2": 2.9195,
    "r2_sum1": 0.1164,
    "r2_sum2": 0.0131,
    "r2_sum3": 0.0137,
    "r2_sum4": 0.0135,
    "ldsc_nsnp_merge_refpanel_ld": 1286923,
    "ldsc_nsnp_merge_regression_ld": 1286923,
    "ldsc_observed_scale_h2_beta": 0.0659,
    "ldsc_observed_scale_h2_se": 0.0042,
    "ldsc_intercept_beta": 0.8866,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.0465,
    "ldsc_mean_chisq": 1.1242,
    "ldsc_ratio": -0.913
}

name	value
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	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	0	1.0000000	3	59	0	8479691	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	8.639618e+00	5.752451e+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	7.888446e+07	5.635321e+07	8.28000e+02	3.254795e+07	6.954272e+07	1.146369e+08	2.492223e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	5.743000e-04	2.535190e-02	-2.88636e-01	-1.061200e-02	3.160000e-04	1.133300e-02	5.503510e-01	▁▇▁▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	2.134400e-02	1.515200e-02	9.05300e-03	1.060100e-02	1.465610e-02	2.656280e-02	1.697250e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.987318e-01	2.905055e-01	0.00000e+00	2.474589e-01	4.997560e-01	7.502759e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.987318e-01	2.905055e-01	0.00000e+00	2.474592e-01	4.997560e-01	7.502756e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	2.440651e-01	2.513024e-01	5.77400e-03	3.966600e-02	1.424650e-01	3.867900e-01	9.931970e-01	▇▂▂▁▁
numeric	AF_reference	204800	0.9758482	NA	NA	NA	NA	NA	2.497691e-01	2.545520e-01	0.00000e+00	4.153350e-02	1.561500e-01	3.919730e-01	1.000000e+00	▇▃▂▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	1.843050e+05	0.000000e+00	1.84305e+05	1.843050e+05	1.843050e+05	1.843050e+05	1.843050e+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	752566	rs3094315	G	A	-0.005243	0.0157652	0.7394605	0.7394605	0.763018	0.718251	184305
1	752721	rs3131972	A	G	-0.003032	0.0156381	0.8462652	0.8462656	0.740969	0.653355	184305
1	752894	rs3131971	T	C	0.004640	0.0162377	0.7750666	0.7750660	0.744287	0.753195	184305
1	753474	rs2073814	C	G	0.000407	0.0157456	0.9793782	0.9793782	0.716742	0.611422	184305
1	753541	rs2073813	G	A	0.005802	0.0167808	0.7295297	0.7295289	0.194804	0.301917	184305
1	754182	rs3131969	A	G	-0.006522	0.0165571	0.6936478	0.6936478	0.760434	0.678514	184305
1	754192	rs3131968	A	G	-0.006791	0.0165668	0.6818675	0.6818674	0.759886	0.678514	184305
1	754334	rs3131967	T	C	-0.009343	0.0168482	0.5792086	0.5792094	0.747971	0.684305	184305
1	754503	rs3115859	G	A	-0.000146	0.0158271	0.9926398	0.9926399	0.742041	0.663938	184305
1	754964	rs3131966	C	T	0.002221	0.0162312	0.8911609	0.8911610	0.727432	0.663339	184305

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	51198577	rs146015776	T	C	-0.086545	0.0362339	0.0169169	0.0169169	0.041843	NA	184305
22	51198590	rs138731614	A	G	-0.078713	0.0369356	0.0330819	0.0330819	0.036627	NA	184305
22	51199281	rs4040021	T	C	-0.033522	0.0144953	0.0207439	0.0207440	0.390830	0.4612620	184305
22	51208568	rs148425445	G	T	-0.044068	0.0275991	0.1103281	0.1103284	0.059355	0.1160140	184305
22	51210268	rs2341018	T	G	-0.005034	0.0149657	0.7365920	0.7365925	0.441612	0.4468850	184305
22	51211031	rs9616968	A	G	0.093196	0.0605079	0.1235043	0.1235046	0.050705	0.0373403	184305
22	51213613	rs34726907	C	T	-0.000428	0.0192738	0.9822834	0.9822834	0.133301	0.1727240	184305
22	51216731	rs5771014	T	C	-0.016457	0.0394971	0.6769241	0.6769246	0.252603	0.2593850	184305
22	51219006	rs28729663	G	A	0.010715	0.0181365	0.5546564	0.5546561	0.172818	0.2052720	184305
23	100784211	rs188350543	C	A	0.020365	0.0139109	0.1432043	0.1432049	0.746040	0.6498010	184305

1   752566  rs3094315   G   A   .   PASS    AF=0.763018 ES:SE:LP:AF:SS:ID   -0.005243:0.0157652:0.131085:0.763018:184305:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.740969 ES:SE:LP:AF:SS:ID   -0.003032:0.0156381:0.0724935:0.740969:184305:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.744287 ES:SE:LP:AF:SS:ID   0.00464:0.0162377:0.110661:0.744287:184305:rs3131971
1   753474  rs2073814   C   G   .   PASS    AF=0.716742 ES:SE:LP:AF:SS:ID   0.000407:0.0157456:0.00904957:0.716742:184305:rs2073814
1   753541  rs2073813   G   A   .   PASS    AF=0.194804 ES:SE:LP:AF:SS:ID   0.005802:0.0167808:0.136957:0.194804:184305:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.760434 ES:SE:LP:AF:SS:ID   -0.006522:0.0165571:0.158861:0.760434:184305:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.759886 ES:SE:LP:AF:SS:ID   -0.006791:0.0165668:0.1663:0.759886:184305:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.747971 ES:SE:LP:AF:SS:ID   -0.009343:0.0168482:0.237165:0.747971:184305:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.742041 ES:SE:LP:AF:SS:ID   -0.000146:0.0158271:0.00320832:0.742041:184305:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.727432 ES:SE:LP:AF:SS:ID   0.002221:0.0162312:0.0500439:0.727432:184305:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.71467  ES:SE:LP:AF:SS:ID   0.006636:0.0164734:0.162997:0.71467:184305:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.776798 ES:SE:LP:AF:SS:ID   -0.008914:0.0170133:0.221619:0.776798:184305:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.756247 ES:SE:LP:AF:SS:ID   -0.004858:0.0168188:0.111988:0.756247:184305:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.749175 ES:SE:LP:AF:SS:ID   -0.008785:0.0168699:0.220013:0.749175:184305:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.782655 ES:SE:LP:AF:SS:ID   -0.014073:0.0170176:0.389067:0.782655:184305:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.78203  ES:SE:LP:AF:SS:ID   -0.014716:0.0170263:0.41182:0.78203:184305:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.767599 ES:SE:LP:AF:SS:ID   -0.006877:0.0164376:0.170262:0.767599:184305:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.781067 ES:SE:LP:AF:SS:ID   -0.013634:0.0171545:0.369833:0.781067:184305:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.73858  ES:SE:LP:AF:SS:ID   0.005562:0.0164788:0.133286:0.73858:184305:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.740961 ES:SE:LP:AF:SS:ID   4.8e-05:0.0166255:0.00100159:0.740961:184305:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.726374 ES:SE:LP:AF:SS:ID   0.005293:0.0171078:0.12089:0.726374:184305:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.769413 ES:SE:LP:AF:SS:ID   -0.006653:0.0175564:0.15198:0.769413:184305:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.745318 ES:SE:LP:AF:SS:ID   -0.007391:0.0177444:0.169396:0.745318:184305:rs3115849
1   764191  rs7515915   T   G   .   PASS    AF=0.155298 ES:SE:LP:AF:SS:ID   -0.000659:0.018596:0.0124541:0.155298:184305:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.117535 ES:SE:LP:AF:SS:ID   -0.0006:0.0210901:0.00997046:0.117535:184305:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.648619 ES:SE:LP:AF:SS:ID   -0.010842:0.0146235:0.338713:0.648619:184305:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.133117 ES:SE:LP:AF:SS:ID   -0.00342:0.0172229:0.07438:0.133117:184305:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.147952 ES:SE:LP:AF:SS:ID   0.002734:0.0187665:0.0534641:0.147952:184305:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.124842 ES:SE:LP:AF:SS:ID   -0.001891:0.0184102:0.0370677:0.124842:184305:rs7518545
1   771823  rs2977605   T   C   .   PASS    AF=0.78219  ES:SE:LP:AF:SS:ID   -0.006408:0.0179203:0.142272:0.78219:184305:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.148426 ES:SE:LP:AF:SS:ID   0.003761:0.0184819:0.0763688:0.148426:184305:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.780253 ES:SE:LP:AF:SS:ID   -0.00819:0.0177487:0.19079:0.780253:184305:rs2905039
1   775181  rs61768182  A   G   .   PASS    AF=0.154809 ES:SE:LP:AF:SS:ID   0.001659:0.0177118:0.0336827:0.154809:184305:rs61768182
1   777122  rs2980319   A   T   .   PASS    AF=0.785305 ES:SE:LP:AF:SS:ID   2.8e-05:0.0173153:0.000560732:0.785305:184305:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.065846 ES:SE:LP:AF:SS:ID   0.035269:0.029713:0.628505:0.065846:184305:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.147126 ES:SE:LP:AF:SS:ID   -0.002725:0.01808:0.0554199:0.147126:184305:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.152134 ES:SE:LP:AF:SS:ID   -0.002915:0.017778:0.0606018:0.152134:184305:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.769873 ES:SE:LP:AF:SS:ID   0.001497:0.0167895:0.0320065:0.769873:184305:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.096234 ES:SE:LP:AF:SS:ID   -0.006469:0.0224577:0.111648:0.096234:184305:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.190557 ES:SE:LP:AF:SS:ID   -0.009817:0.0171273:0.246781:0.190557:184305:rs6594026
1   783318  rs6686696   A   G   .   PASS    AF=0.138281 ES:SE:LP:AF:SS:ID   -0.005518:0.018798:0.114012:0.138281:184305:rs6686696
1   785050  rs2905062   G   A   .   PASS    AF=0.763925 ES:SE:LP:AF:SS:ID   -0.000143:0.0165277:0.00300846:0.763925:184305:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.75437  ES:SE:LP:AF:SS:ID   0.000981:0.0163463:0.021297:0.75437:184305:rs2980300
1   786995  rs61768202  G   A   .   PASS    AF=0.151266 ES:SE:LP:AF:SS:ID   -0.002106:0.0182777:0.0417856:0.151266:184305:rs61768202
1   787121  rs12077234  T   A   .   PASS    AF=0.156307 ES:SE:LP:AF:SS:ID   -0.008706:0.0188632:0.190834:0.156307:184305:rs12077234
1   787151  rs2519065   G   A   .   PASS    AF=0.168643 ES:SE:LP:AF:SS:ID   -0.001924:0.0189121:0.0366996:0.168643:184305:rs2519065
1   787399  rs2905055   G   T   .   PASS    AF=0.747237 ES:SE:LP:AF:SS:ID   -0.000423:0.0172794:0.00856578:0.747237:184305:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.151655 ES:SE:LP:AF:SS:ID   -0.007309:0.0185764:0.158651:0.151655:184305:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.737835 ES:SE:LP:AF:SS:ID   -0.001878:0.0170068:0.0399714:0.737835:184305:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.764577 ES:SE:LP:AF:SS:ID   -0.000971:0.0173566:0.019821:0.764577:184305:rs2905053

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