IEU GWAS QC Report

name	value
id	ieu-a-1019
pmid	25451450
year	2015
mr	1
note	NULL
trait	Migraine in bipolar disorder
category	Risk factor
subcategory	Psychiatric / neurological
population	European
sex	Males and females
ncase	460
ncontrol	924
sample_size	1374
nsnp	723225
sd	NULL
priority	1
author	Jacobsen KK
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-1019
bcf_file	ieu-a-1019.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-09 20:31 BST
build_version	run_igd-8f4f4c9-2020-05-09

$manhattan_plot$

manhattan_plot

qq_plot

af_plot

$pz_plot$

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-1019/ieu-a-1019.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-1019/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 21:10:01 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1019/ieu-a-1019.vcf.gz ...
Read summary statistics for 722473 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, 668247 SNPs remain.
After merging with regression SNP LD, 668247 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0759 (0.3235)
Lambda GC: 0.9979
Mean Chi^2: 0.9916
Intercept: 0.9896 (0.0063)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Tue Feb  4 21:10:15 2020
Total time elapsed: 14.56s

{
    "af_correlation": 0.922,
    "inflation_factor": 0.9991,
    "mean_EFFECT": -0.0012,
    "n": 1374,
    "n_snps": 722473,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 5000,
    "n_est": 1363.545,
    "ratio_se_n": 0.9962,
    "mean_diff": 0.0013,
    "ratio_diff": 2.0382,
    "sd_y_est1": 2.1354,
    "sd_y_est2": 2.1273,
    "r2_sum1": 0.0981,
    "r2_sum2": 0.0215,
    "r2_sum3": 0.0217,
    "r2_sum4": 0.0219,
    "ldsc_nsnp_merge_refpanel_ld": 668247,
    "ldsc_nsnp_merge_regression_ld": 668247,
    "ldsc_observed_scale_h2_beta": 0.0759,
    "ldsc_observed_scale_h2_se": 0.3235,
    "ldsc_intercept_beta": 0.9896,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 0.9979,
    "ldsc_mean_chisq": 0.9916,
    "ldsc_ratio": 1.2381
}

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	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	25	0	722473	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	24	0.9999668	NA	NA	NA	NA	NA	9.182708e+00	6.235181e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.300000e+01	2.400000e+01	▇▆▃▃▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.872254e+07	5.641375e+07	1.4380e+03	3.161567e+07	7.005013e+07	1.156412e+08	2.491982e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-1.245300e-03	1.333402e-01	-2.6818e+00	-7.267820e-02	0.000000e+00	7.232070e-02	1.431290e+00	▁▁▁▇▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.199889e-01	5.619980e-02	7.6200e-02	8.501000e-02	9.752000e-02	1.304000e-01	1.123000e+00	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	5.002108e-01	2.880157e-01	0.0000e+00	2.509002e-01	5.002004e-01	7.492004e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	5.002111e-01	2.880187e-01	0.0000e+00	2.508665e-01	5.002401e-01	7.492259e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	3.638353e-01	2.672112e-01	8.7340e-03	1.332000e-01	3.046000e-01	5.591000e-01	9.915560e-01	▇▅▃▃▂
numeric	AF_reference	5000	0.9930793	NA	NA	NA	NA	NA	3.676907e-01	2.508123e-01	7.9870e-04	1.561500e-01	3.095050e-01	5.497200e-01	9.994700e-01	▇▇▅▃▂
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	1.367842e+03	1.664977e+01	4.6400e+02	1.367000e+03	1.373000e+03	1.374000e+03	1.374000e+03	▁▁▁▁▇

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	721290	rs12565286	G	C	-0.3143000	0.19980	0.1156999	0.1157019	0.05033	0.0371406	1371
1	752566	rs3094315	G	A	0.0177567	0.10100	0.8603000	0.8604441	0.81360	0.7182510	1368
1	761732	rs2286139	C	T	-0.0953102	0.11370	0.4043002	0.4018845	0.85380	0.6257990	1351
1	777122	rs2980319	A	T	-0.0723207	0.11600	0.5309003	0.5329860	0.86230	0.7472040	1373
1	785989	rs2980300	T	C	-0.0198026	0.11070	0.8604000	0.8580278	0.83980	0.6269970	1373
1	798959	rs11240777	G	A	0.1570040	0.09259	0.0906192	0.0899445	0.23030	0.4099440	1374
1	888659	rs3748597	T	C	0.0155198	0.17160	0.9280001	0.9279362	0.94169	0.9227240	1372
1	918573	rs2341354	A	G	-0.1544360	0.08341	0.0641594	0.0640935	0.57470	0.5491210	1346
1	926431	rs4970403	A	T	-0.0468836	0.20010	0.8152999	0.8147514	0.95670	0.8927720	1374
1	947034	rs2465126	G	A	-0.0049875	0.18960	0.9794000	0.9790136	0.95070	0.8256790	1359

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
NA	11719	rs2853495	G	A	-0.1052610	0.1144	0.3592998	0.3575134	0.50870	NA	1374
NA	11812	rs3088053	A	G	-0.1423700	0.2116	0.5010003	0.5010579	0.08333	NA	1368
NA	11914	rs2853496	G	A	-0.0068232	0.2945	0.9814000	0.9815156	0.03956	NA	1365
NA	12007	rs2853497	G	A	-0.5461070	0.5120	0.2861001	0.2861456	0.01602	NA	1373
NA	12308	rs2853498	A	G	-0.1638140	0.1419	0.2482001	0.2483228	0.21410	NA	1373
NA	12612	rs28359172	A	G	0.0953102	0.1950	0.6242995	0.6250044	0.09243	NA	1374
NA	13617	rs2853503	T	C	0.0188218	0.2058	0.9271000	0.9271297	0.08382	NA	1372
NA	13708	rs28359178	G	A	0.1371500	0.1754	0.4338005	0.4342575	0.11650	NA	1373
NA	14470	rs3135030	T	C	0.1406310	0.3833	0.7129006	0.7136971	0.02187	NA	1372
NA	15218	rs2853506	A	G	0.1856490	0.2822	0.5104004	0.5106260	0.04079	NA	1373

1   721290  rs12565286  G   C   .   PASS    AF=0.05033  ES:SE:LP:AF:SS:ID   -0.3143:0.1998:0.936667:0.05033:1371:rs12565286
1   752566  rs3094315   G   A   .   PASS    AF=0.8136   ES:SE:LP:AF:SS:ID   0.0177567:0.101:0.0653501:0.8136:1368:rs3094315
1   761732  rs2286139   C   T   .   PASS    AF=0.8538   ES:SE:LP:AF:SS:ID   -0.0953102:0.1137:0.393296:0.8538:1351:rs2286139
1   777122  rs2980319   A   T   .   PASS    AF=0.8623   ES:SE:LP:AF:SS:ID   -0.0723207:0.116:0.274987:0.8623:1373:rs2980319
1   785989  rs2980300   T   C   .   PASS    AF=0.8398   ES:SE:LP:AF:SS:ID   -0.0198026:0.1107:0.0652996:0.8398:1373:rs2980300
1   798959  rs11240777  G   A   .   PASS    AF=0.2303   ES:SE:LP:AF:SS:ID   0.157004:0.09259:1.04278:0.2303:1374:rs11240777
1   888659  rs3748597   T   C   .   PASS    AF=0.94169  ES:SE:LP:AF:SS:ID   0.0155198:0.1716:0.032452:0.94169:1372:rs3748597
1   918573  rs2341354   A   G   .   PASS    AF=0.5747   ES:SE:LP:AF:SS:ID   -0.154436:0.08341:1.19274:0.5747:1346:rs2341354
1   926431  rs4970403   A   T   .   PASS    AF=0.9567   ES:SE:LP:AF:SS:ID   -0.0468836:0.2001:0.0886826:0.9567:1374:rs4970403
1   947034  rs2465126   G   A   .   PASS    AF=0.9507   ES:SE:LP:AF:SS:ID   -0.00498754:0.1896:0.0090399:0.9507:1359:rs2465126
1   949608  rs1921  G   A   .   PASS    AF=0.3999   ES:SE:LP:AF:SS:ID   0.0962189:0.08437:0.593119:0.3999:1364:rs1921
1   990417  rs2465136   T   C   .   PASS    AF=0.2991   ES:SE:LP:AF:SS:ID   -0.058795:0.08856:0.295163:0.2991:1371:rs2465136
1   1018704 rs9442372   A   G   .   PASS    AF=0.5512   ES:SE:LP:AF:SS:ID   0.086975:0.08275:0.532688:0.5512:1358:rs9442372
1   1039098 rs11260595  C   A   .   PASS    AF=0.02725  ES:SE:LP:AF:SS:ID   -0.390675:0.2726:0.819014:0.02725:1358:rs11260595
1   1041700 rs6604968   A   G   .   PASS    AF=0.1348   ES:SE:LP:AF:SS:ID   -0.138113:0.12:0.602234:0.1348:1372:rs6604968
1   1048955 rs4970405   A   G   .   PASS    AF=0.09767  ES:SE:LP:AF:SS:ID   -0.10948:0.1379:0.369369:0.09767:1372:rs4970405
1   1097335 rs9442385   T   G   .   PASS    AF=0.93252  ES:SE:LP:AF:SS:ID   0.0381173:0.1651:0.0875122:0.93252:1356:rs9442385
1   1129672 rs11260554  G   T   .   PASS    AF=0.1107   ES:SE:LP:AF:SS:ID   -0.106472:0.1296:0.385841:0.1107:1368:rs11260554
1   1130727 rs10907175  A   C   .   PASS    AF=0.09789  ES:SE:LP:AF:SS:ID   0.0944007:0.1376:0.307858:0.09789:1374:rs10907175
1   1156131 rs2887286   T   C   .   PASS    AF=0.1696   ES:SE:LP:AF:SS:ID   0.14583:0.1053:0.780154:0.1696:1374:rs2887286
1   1158277 rs3813199   G   A   .   PASS    AF=0.103    ES:SE:LP:AF:SS:ID   0.00498754:0.1343:0.0120211:0.103:1374:rs3813199
1   1158631 rs6603781   A   G   .   PASS    AF=0.8927   ES:SE:LP:AF:SS:ID   -0.00299551:0.13:0.008641:0.8927:1351:rs6603781
1   1165310 rs11260562  G   A   .   PASS    AF=0.04492  ES:SE:LP:AF:SS:ID   -0.113617:0.1975:0.247721:0.04492:1369:rs11260562
1   1195690 rs11260568  G   C   .   PASS    AF=0.01202  ES:SE:LP:AF:SS:ID   -1.05757:0.4889:1.51499:0.01202:1373:rs11260568
1   1198618 rs12563338  T   A   .   PASS    AF=0.03621  ES:SE:LP:AF:SS:ID   0.34359:0.2059:1.02091:0.03621:1367:rs12563338
1   1211292 rs6685064   C   T   .   PASS    AF=0.06477  ES:SE:LP:AF:SS:ID   0.260825:0.1562:1.02393:0.06477:1374:rs6685064
1   1217058 rs3753340   G   A   .   PASS    AF=0.02054  ES:SE:LP:AF:SS:ID   -0.740868:0.3414:1.52259:0.02054:1363:rs3753340
1   1218086 rs6603788   C   T   .   PASS    AF=0.07465  ES:SE:LP:AF:SS:ID   0.0563803:0.1508:0.150212:0.07465:1373:rs6603788
1   1242215 rs4970431   A   G   .   PASS    AF=0.97785  ES:SE:LP:AF:SS:ID   0.0320068:0.2811:0.0412928:0.97785:1309:rs4970431
1   1297065 rs2765023   C   T   .   PASS    AF=0.1129   ES:SE:LP:AF:SS:ID   0.0227395:0.1291:0.0657036:0.1129:1373:rs2765023
1   1297422 rs2765021   C   T   .   PASS    AF=0.93061  ES:SE:LP:AF:SS:ID   0.0143018:0.1594:0.0322181:0.93061:1369:rs2765021
1   1311716 rs2649589   G   A   .   PASS    AF=0.92978  ES:SE:LP:AF:SS:ID   0.00110061:0.1624:0.00230788:0.92978:1360:rs2649589
1   1333436 rs1240743   C   A   .   PASS    AF=0.6267   ES:SE:LP:AF:SS:ID   0.164639:0.0857:1.26209:0.6267:1373:rs1240743
1   1365570 rs1695824   A   C   .   PASS    AF=0.2031   ES:SE:LP:AF:SS:ID   -0.018979:0.1024:0.069051:0.2031:1374:rs1695824
1   1462766 rs9439462   C   T   .   PASS    AF=0.03367  ES:SE:LP:AF:SS:ID   0.107957:0.2153:0.209996:0.03367:1366:rs9439462
1   1467485 rs1987191   T   C   .   PASS    AF=0.01969  ES:SE:LP:AF:SS:ID   -0.26958:0.3043:0.425274:0.01969:1371:rs1987191
1   1478153 rs3766180   T   C   .   PASS    AF=0.274    ES:SE:LP:AF:SS:ID   0.00697561:0.08979:0.0290491:0.274:1374:rs3766180
1   1500941 rs6603791   A   G   .   PASS    AF=0.3126   ES:SE:LP:AF:SS:ID   0.0544882:0.08595:0.281831:0.3126:1374:rs6603791
1   1506035 rs7540231   G   A   .   PASS    AF=0.8452   ES:SE:LP:AF:SS:ID   -0.127513:0.1088:0.615288:0.8452:1373:rs7540231
1   1510801 rs7519837   C   T   .   PASS    AF=0.2999   ES:SE:LP:AF:SS:ID   0.0168571:0.0876:0.0697643:0.2999:1374:rs7519837
1   1647686 rs909823    A   C   .   PASS    AF=0.93421  ES:SE:LP:AF:SS:ID   -0.150143:0.1623:0.450016:0.93421:1368:rs909823
1   1688192 rs2281173   A   G   .   PASS    AF=0.92031  ES:SE:LP:AF:SS:ID   -0.220741:0.1494:0.855426:0.92031:1374:rs2281173
1   1692321 rs1107910   T   C   .   PASS    AF=0.4429   ES:SE:LP:AF:SS:ID   -0.0565704:0.08192:0.309715:0.4429:1374:rs1107910
1   1721479 rs2272908   C   T   .   PASS    AF=0.516    ES:SE:LP:AF:SS:ID   -0.0246926:0.08158:0.118729:0.516:1374:rs2272908
1   1722932 rs3737628   C   T   .   PASS    AF=0.5144   ES:SE:LP:AF:SS:ID   -0.0478373:0.08306:0.24849:0.5144:1356:rs3737628
1   1746694 rs12742323  G   T   .   PASS    AF=0.1619   ES:SE:LP:AF:SS:ID   -0.0968414:0.1108:0.418164:0.1619:1353:rs12742323
1   1759026 rs9786963   T   C   .   PASS    AF=0.94756  ES:SE:LP:AF:SS:ID   -0.290428:0.1795:0.975104:0.94756:1373:rs9786963
1   1759054 rs10907187  G   A   .   PASS    AF=0.2616   ES:SE:LP:AF:SS:ID   0.0592119:0.08988:0.291919:0.2616:1374:rs10907187
1   1778090 rs12126768  T   G   .   PASS    AF=0.1653   ES:SE:LP:AF:SS:ID   -0.117208:0.1104:0.540608:0.1653:1373:rs12126768
1   1783201 rs12402876  G   A   .   PASS    AF=0.2593   ES:SE:LP:AF:SS:ID   0.07139:0.09301:0.355069:0.2593:1313:rs12402876

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