IEU GWAS QC Report

name	value
id	ieu-a-6
pmid	21378988
year	2011
mr	1
note	NULL
trait	Coronary heart disease
category	Disease
subcategory	Cardiovascular
population	Mixed
sex	Males and females
ncase	15420
ncontrol	15062
sample_size	30482
nsnp	540233
sd	NULL
priority	3
author	Peden
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-6
bcf_file	ieu-a-6.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 02:30 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-6/ieu-a-6.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-6/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 11:33:50 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-6/ieu-a-6.vcf.gz ...
Read summary statistics for 539613 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, 514439 SNPs remain.
After merging with regression SNP LD, 514439 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0647 (0.0196)
Lambda GC: 1.0926
Mean Chi^2: 1.0947
Intercept: 1.0614 (0.0072)
Ratio: 0.6485 (0.076)
Analysis finished at Wed Feb  5 11:34:03 2020
Total time elapsed: 12.21s

{
    "af_correlation": 0.9399,
    "inflation_factor": 1.0931,
    "mean_EFFECT": -0.0001,
    "n": 30453,
    "n_snps": 539613,
    "n_clumped_hits": 3,
    "n_p_sig": 29,
    "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": 3202,
    "n_est": 28460.8722,
    "ratio_se_n": 0.9667,
    "mean_diff": 0,
    "ratio_diff": 2.5026,
    "sd_y_est1": 2.1502,
    "sd_y_est2": 2.0787,
    "r2_sum1": 0.0358,
    "r2_sum2": 0.0077,
    "r2_sum3": 0.0083,
    "r2_sum4": 0.0082,
    "ldsc_nsnp_merge_refpanel_ld": 514439,
    "ldsc_nsnp_merge_regression_ld": 514439,
    "ldsc_observed_scale_h2_beta": 0.0647,
    "ldsc_observed_scale_h2_se": 0.0196,
    "ldsc_intercept_beta": 1.0614,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.0926,
    "ldsc_mean_chisq": 1.0947,
    "ldsc_ratio": 0.6484
}

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	FALSE
miss_EFFECT	FALSE
miss_SE	FALSE
miss_PVAL	FALSE
ldsc_ratio	TRUE
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	30	0	539613	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	8.789751e+00	5.783061e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.794116e+07	5.665020e+07	1.8856e+04	3.102050e+07	6.862144e+07	1.143486e+08	2.492107e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-5.580000e-05	2.718170e-02	-3.3790e-01	-1.550000e-02	0.000000e+00	1.550000e-02	3.455000e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	2.395080e-02	1.029080e-02	1.6300e-02	1.770000e-02	2.040000e-02	2.600000e-02	1.409000e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.863210e-01	2.921061e-01	0.0000e+00	2.301998e-01	4.806999e-01	7.396002e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.863195e-01	2.921049e-01	0.0000e+00	2.301393e-01	4.806465e-01	7.398216e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	3.717760e-01	2.544763e-01	1.0000e-02	1.550000e-01	3.150000e-01	5.730000e-01	9.900000e-01	▇▆▃▃▂
numeric	AF_reference	3202	0.9940661	NA	NA	NA	NA	NA	3.722214e-01	2.445588e-01	1.9970e-04	1.671330e-01	3.180910e-01	5.503190e-01	9.962060e-01	▇▇▅▃▂
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	2.883952e+04	4.305464e+03	8.8580e+03	3.038200e+04	3.041800e+04	3.043200e+04	3.045300e+04	▁▁▁▁▇

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	0.0156	0.0315	0.6204003	0.6204321	0.810	0.718251	13897
1	768448	rs12562034	G	A	-0.0507	0.0215	0.0184502	0.0183668	0.191	0.191893	30342
1	846808	rs4475691	C	T	0.0173	0.0344	0.6146997	0.6150297	0.217	0.254792	13823
1	900505	rs28705211	G	C	-0.0150	0.0319	0.6378007	0.6381982	0.282	0.168730	13767
1	918384	rs13303118	G	T	-0.0559	0.0298	0.0604798	0.0606774	0.605	0.492612	13777
1	928836	rs9777703	C	T	-0.0005	0.0929	0.9956000	0.9957057	0.971	0.890176	13811
1	943468	rs3121567	T	C	0.0927	0.0800	0.2467999	0.2465581	0.962	0.893770	13815
1	1005806	rs3934834	C	T	-0.0175	0.0220	0.4255004	0.4263491	0.179	0.223442	30310
1	1018704	rs9442372	A	G	0.0288	0.0169	0.0886605	0.0883546	0.556	0.611022	30351
1	1021415	rs3737728	A	G	0.0167	0.0193	0.3877002	0.3868824	0.745	0.812700	30430

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	51147015	rs2040487	A	G	0.0264	0.0169	0.1170000	0.1182573	0.433	0.4556710	30414
22	51150473	rs5770820	G	A	0.0246	0.0192	0.2013001	0.2001059	0.254	0.2462060	30395
22	51151350	rs6009951	C	T	-0.0008	0.0300	0.9784000	0.9787256	0.396	0.5559110	13830
22	51151724	rs6010061	C	T	0.0121	0.0173	0.4829999	0.4842884	0.384	0.6098240	30265
22	51163138	rs715586	C	T	0.0074	0.0241	0.7592993	0.7588023	0.140	0.0902556	30405
22	51165664	rs8137951	G	A	0.0057	0.0180	0.7492004	0.7514965	0.317	0.4063500	30436
22	51171693	rs756638	G	A	-0.0172	0.0199	0.3863003	0.3874112	0.236	0.3049120	30403
22	51175626	rs3810648	A	G	0.0015	0.0366	0.9670001	0.9673090	0.055	0.1084270	30436
22	51178090	rs2285395	G	A	0.0462	0.0390	0.2360000	0.2361696	0.048	0.0666933	30443
23	51666786	rs14115	A	G	0.0203	0.0323	0.5304995	0.5296876	0.072	NA	30406

1   752566  rs3094315   G   A   .   PASS    AF=0.81 ES:SE:LP:AF:SS:ID   0.0156:0.0315:0.207328:0.81:13897:rs3094315
1   768448  rs12562034  G   A   .   PASS    AF=0.191    ES:SE:LP:AF:SS:ID   -0.0507:0.0215:1.734:0.191:30342:rs12562034
1   846808  rs4475691   C   T   .   PASS    AF=0.217    ES:SE:LP:AF:SS:ID   0.0173:0.0344:0.211337:0.217:13823:rs4475691
1   900505  rs28705211  G   C   .   PASS    AF=0.282    ES:SE:LP:AF:SS:ID   -0.015:0.0319:0.195315:0.282:13767:rs28705211
1   918384  rs13303118  G   T   .   PASS    AF=0.605    ES:SE:LP:AF:SS:ID   -0.0559:0.0298:1.21839:0.605:13777:rs13303118
1   928836  rs9777703   C   T   .   PASS    AF=0.971    ES:SE:LP:AF:SS:ID   -0.0005:0.0929:0.00191511:0.971:13811:rs9777703
1   943468  rs3121567   T   C   .   PASS    AF=0.962    ES:SE:LP:AF:SS:ID   0.0927:0.08:0.607655:0.962:13815:rs3121567
1   1005806 rs3934834   C   T   .   PASS    AF=0.179    ES:SE:LP:AF:SS:ID   -0.0175:0.022:0.3711:0.179:30310:rs3934834
1   1018704 rs9442372   A   G   .   PASS    AF=0.556    ES:SE:LP:AF:SS:ID   0.0288:0.0169:1.05227:0.556:30351:rs9442372
1   1021415 rs3737728   A   G   .   PASS    AF=0.745    ES:SE:LP:AF:SS:ID   0.0167:0.0193:0.411504:0.745:30430:rs3737728
1   1030565 rs6687776   C   T   .   PASS    AF=0.199    ES:SE:LP:AF:SS:ID   -0.0422:0.0212:1.33479:0.199:30435:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.779    ES:SE:LP:AF:SS:ID   0.041:0.0206:1.32985:0.779:30371:rs9651273
1   1048955 rs4970405   A   G   .   PASS    AF=0.139    ES:SE:LP:AF:SS:ID   -0.0591:0.0243:1.81844:0.139:30418:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.178    ES:SE:LP:AF:SS:ID   -0.0208:0.0219:0.465974:0.178:30436:rs12726255
1   1061166 rs11807848  T   C   .   PASS    AF=0.39 ES:SE:LP:AF:SS:ID   -0.0403:0.0172:1.71332:0.39:30409:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.594    ES:SE:LP:AF:SS:ID   0.0197:0.0171:0.599462:0.594:30349:rs9442373
1   1064979 rs2298217   C   T   .   PASS    AF=0.164    ES:SE:LP:AF:SS:ID   -0.0056:0.0226:0.0940962:0.164:30408:rs2298217
1   1066029 rs12145826  G   A   .   PASS    AF=0.052    ES:SE:LP:AF:SS:ID   -0.0068:0.0381:0.0663103:0.052:30419:rs12145826
1   1087683 rs9442380   T   C   .   PASS    AF=0.892    ES:SE:LP:AF:SS:ID   0.0316:0.0272:0.611544:0.892:30436:rs9442380
1   1090557 rs7553429   A   C   .   PASS    AF=0.061    ES:SE:LP:AF:SS:ID   0.0155:0.0351:0.181444:0.061:30398:rs7553429
1   1094738 rs4970362   A   G   .   PASS    AF=0.665    ES:SE:LP:AF:SS:ID   0.0336:0.0247:0.762205:0.665:14745:rs4970362
1   1099342 rs9660710   A   C   .   PASS    AF=0.913    ES:SE:LP:AF:SS:ID   0.0085:0.0297:0.110194:0.913:30428:rs9660710
1   1106473 rs4970420   G   A   .   PASS    AF=0.296    ES:SE:LP:AF:SS:ID   0.0131:0.0188:0.31399:0.296:30413:rs4970420
1   1119858 rs1320565   C   T   .   PASS    AF=0.179    ES:SE:LP:AF:SS:ID   -0.0315:0.0226:0.786748:0.179:30437:rs1320565
1   1121794 rs11260549  G   A   .   PASS    AF=0.173    ES:SE:LP:AF:SS:ID   -0.0059:0.0223:0.10133:0.173:30422:rs11260549
1   1135242 rs9729550   A   C   .   PASS    AF=0.338    ES:SE:LP:AF:SS:ID   0.0053:0.0179:0.115885:0.338:30401:rs9729550
1   1152631 rs11721 C   A   .   PASS    AF=0.086    ES:SE:LP:AF:SS:ID   -0.0024:0.03:0.0284458:0.086:30419:rs11721
1   1156131 rs2887286   T   C   .   PASS    AF=0.325    ES:SE:LP:AF:SS:ID   -0.0184:0.0191:0.473919:0.325:30431:rs2887286
1   1158277 rs3813199   G   A   .   PASS    AF=0.094    ES:SE:LP:AF:SS:ID   -0.0032:0.0288:0.0401004:0.094:30438:rs3813199
1   1162435 rs3766186   C   A   .   PASS    AF=0.094    ES:SE:LP:AF:SS:ID   -0.0046:0.0288:0.0595333:0.094:30410:rs3766186
1   1163804 rs7515488   C   T   .   PASS    AF=0.159    ES:SE:LP:AF:SS:ID   0.003:0.023:0.0479344:0.159:30407:rs7515488
1   1172907 rs715643    C   T   .   PASS    AF=0.039    ES:SE:LP:AF:SS:ID   -0.0983:0.0617:0.953895:0.039:19951:rs715643
1   1176597 rs6675798   T   C   .   PASS    AF=0.116    ES:SE:LP:AF:SS:ID   -0.0015:0.0264:0.0207249:0.116:30389:rs6675798
1   1192515 rs7524470   A   G   .   PASS    AF=0.044    ES:SE:LP:AF:SS:ID   0.0586:0.0408:0.822464:0.044:30440:rs7524470
1   1194804 rs11804831  T   C   .   PASS    AF=0.302    ES:SE:LP:AF:SS:ID   0.0179:0.0189:0.4642:0.302:30365:rs11804831
1   1211292 rs6685064   C   T   .   PASS    AF=0.198    ES:SE:LP:AF:SS:ID   0.0111:0.022:0.211902:0.198:30395:rs6685064
1   1242084 rs3737717   A   G   .   PASS    AF=0.175    ES:SE:LP:AF:SS:ID   -0.0007:0.0312:0.00784429:0.175:14694:rs3737717
1   1288583 rs3845295   C   G   .   PASS    AF=0.889    ES:SE:LP:AF:SS:ID   -0.0041:0.0441:0.0330608:0.889:13809:rs3845295
1   1305561 rs17160669  C   T   .   PASS    AF=0.263    ES:SE:LP:AF:SS:ID   -0.0267:0.0327:0.383735:0.263:13820:rs17160669
1   1310924 rs2765033   T   C   .   PASS    AF=0.952    ES:SE:LP:AF:SS:ID   -0.0129:0.0392:0.129596:0.952:30328:rs2765033
1   1314015 rs2649588   C   T   .   PASS    AF=0.891    ES:SE:LP:AF:SS:ID   -0.0385:0.0268:0.822464:0.891:30410:rs2649588
1   1334475 rs17851391  G   C   .   PASS    AF=0.024    ES:SE:LP:AF:SS:ID   -0.0926:0.0998:0.451488:0.024:13820:rs17851391
1   1425700 rs819980    T   C   .   PASS    AF=0.2  ES:SE:LP:AF:SS:ID   0.0325:0.0216:0.875496:0.2:30383:rs819980
1   1447325 rs6690515   G   A   .   PASS    AF=0.214    ES:SE:LP:AF:SS:ID   0.0101:0.0347:0.112495:0.214:13815:rs6690515
1   1462766 rs9439462   C   T   .   PASS    AF=0.127    ES:SE:LP:AF:SS:ID   0.0243:0.0259:0.457299:0.127:30405:rs9439462
1   1478180 rs3766178   T   C   .   PASS    AF=0.318    ES:SE:LP:AF:SS:ID   0.0127:0.0181:0.315424:0.318:30429:rs3766178
1   1485984 rs2031709   C   A   .   PASS    AF=0.09 ES:SE:LP:AF:SS:ID   -0.0234:0.0302:0.357832:0.09:30360:rs2031709
1   1486834 rs3128342   C   A   .   PASS    AF=0.326    ES:SE:LP:AF:SS:ID   0.0213:0.0185:0.602929:0.326:30426:rs3128342
1   1493727 rs880051    G   A   .   PASS    AF=0.337    ES:SE:LP:AF:SS:ID   -0.0089:0.021:0.173407:0.337:20317:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.189    ES:SE:LP:AF:SS:ID   0.0045:0.0216:0.0774302:0.189:30432:rs2296716

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