IEU GWAS QC Report

name	value
id	ieu-a-1009
pmid	27089181
year	2016
mr	1
note	NULL
trait	Subjective well being
category	Risk factor
subcategory	Psychiatric / neurological
population	European
sex	Males and females
ncase	NULL
ncontrol	NULL
sample_size	298420
nsnp	2268675
sd	NULL
priority	1
author	Okbay
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-1009
bcf_file	ieu-a-1009.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 14:47 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-1009/ieu-a-1009.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-1009/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 11:09:28 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1009/ieu-a-1009.vcf.gz ...
Read summary statistics for 2268424 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, 1107672 SNPs remain.
After merging with regression SNP LD, 1107672 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0352 (0.0022)
Lambda GC: 1.2365
Mean Chi^2: 1.2286
Intercept: 1.0188 (0.0076)
Ratio: 0.0821 (0.0334)
Analysis finished at Wed Feb  5 11:09:56 2020
Total time elapsed: 27.55s

{
    "af_correlation": 0.9179,
    "inflation_factor": 1.1396,
    "mean_EFFECT": -0,
    "n": 298420,
    "n_snps": 2268424,
    "n_clumped_hits": 1,
    "n_p_sig": 8,
    "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": 15076,
    "n_est": 241311.6928,
    "ratio_se_n": 0.8992,
    "mean_diff": 3.9441e-06,
    "ratio_diff": 18.0092,
    "sd_y_est1": 1.3068,
    "sd_y_est2": 1.1751,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0001,
    "r2_sum3": 0.0001,
    "r2_sum4": 0.0001,
    "ldsc_nsnp_merge_refpanel_ld": 1107672,
    "ldsc_nsnp_merge_regression_ld": 1107672,
    "ldsc_observed_scale_h2_beta": 0.0352,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0188,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.2365,
    "ldsc_mean_chisq": 1.2286,
    "ldsc_ratio": 0.0822
}

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	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	1.000000	3	34	0	2268424	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.000000	1	1	0	4	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.000000	1	1	0	4	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.000000	NA	NA	NA	NA	NA	8.625020e+00	5.659207e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.200000e+01	2.200000e+01	▇▅▅▂▂
numeric	POS	0	1.000000	NA	NA	NA	NA	NA	7.883314e+07	5.560844e+07	1.1523e+04	3.279621e+07	7.041106e+07	1.144197e+08	2.492107e+08	▇▇▅▂▁
numeric	EFFECT	0	1.000000	NA	NA	NA	NA	NA	-2.790000e-05	4.999700e-03	-4.7000e-02	-3.000000e-03	0.000000e+00	3.000000e-03	4.700000e-02	▁▁▇▁▁
numeric	SE	0	1.000000	NA	NA	NA	NA	NA	4.356700e-03	1.664200e-03	3.0000e-03	3.000000e-03	4.000000e-03	5.000000e-03	1.300000e-02	▇▂▁▁▁
numeric	PVAL	0	1.000000	NA	NA	NA	NA	NA	4.783831e-01	2.944220e-01	0.0000e+00	2.183001e-01	4.715003e-01	7.327992e-01	1.000000e+00	▇▇▆▆▆
numeric	PVAL_ztest	0	1.000000	NA	NA	NA	NA	NA	4.740005e-01	3.026047e-01	0.0000e+00	1.985428e-01	4.532547e-01	7.388827e-01	1.000000e+00	▇▆▆▆▆
numeric	AF	0	1.000000	NA	NA	NA	NA	NA	3.719535e-01	2.605213e-01	1.1190e-02	1.455000e-01	3.134000e-01	5.653000e-01	9.869400e-01	▇▆▃▃▂
numeric	AF_reference	15076	0.993354	NA	NA	NA	NA	NA	3.726519e-01	2.481597e-01	1.9970e-04	1.643370e-01	3.164940e-01	5.537140e-01	9.956070e-01	▇▇▅▃▂
numeric	N	0	1.000000	NA	NA	NA	NA	NA	2.984200e+05	0.000000e+00	2.9842e+05	2.984200e+05	2.984200e+05	2.984200e+05	2.984200e+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	-0.001	0.005	0.7953000	0.8414806	0.84510	0.7182510	298420
1	754192	rs3131968	A	G	-0.006	0.005	0.2709000	0.2301393	0.87870	0.6785140	298420
1	777122	rs2980319	A	T	0.004	0.006	0.4657995	0.5049851	0.88060	0.7472040	298420
1	779322	rs4040617	A	G	-0.005	0.006	0.4334999	0.4046568	0.11750	0.2264380	298420
1	780785	rs2977612	T	A	0.003	0.006	0.6085006	0.6170751	0.87870	0.6693290	298420
1	785989	rs2980300	T	C	0.004	0.006	0.4369000	0.5049851	0.86750	0.6269970	298420
1	798801	rs12132517	G	A	0.018	0.008	0.0208598	0.0244489	0.07649	0.0740815	298420
1	798959	rs11240777	G	A	0.014	0.005	0.0046990	0.0051103	0.20150	0.4099440	298420
1	846864	rs950122	G	C	-0.006	0.006	0.2432999	0.3173105	0.18470	0.2228430	298420
1	882033	rs2272756	G	A	-0.006	0.005	0.2495003	0.2301393	0.24250	0.1367810	298420

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	51162059	rs10451	G	A	-0.001	0.004	0.7337008	0.8025873	0.27800	0.3865810	298420
22	51163138	rs715586	C	T	-0.006	0.005	0.2270999	0.2301393	0.12500	0.0902556	298420
22	51165664	rs8137951	G	A	-0.002	0.004	0.5707002	0.6170751	0.27610	0.4063500	298420
22	51171497	rs2301584	G	A	-0.012	0.005	0.0091369	0.0163951	0.16040	0.2533950	298420
22	51171693	rs756638	G	A	0.002	0.004	0.5764000	0.6170751	0.27050	0.3049120	298420
22	51173542	rs4824147	T	C	-0.002	0.009	0.8278000	0.8241409	0.95896	0.9812300	298420
22	51175626	rs3810648	A	G	0.007	0.007	0.3442001	0.3173105	0.05037	0.1084270	298420
22	51178090	rs2285395	G	A	0.011	0.008	0.1590000	0.1691314	0.04851	0.0666933	298420
22	51196164	rs8136603	A	T	0.008	0.008	0.3044002	0.3173105	0.05410	0.1427720	298420
22	51212875	rs2238837	A	C	-0.004	0.004	0.3078003	0.3173105	0.20150	0.3724040	298420

1   752566  rs3094315   G   A   .   PASS    AF=0.8451   ES:SE:LP:AF:SS:ID   -0.001:0.005:0.099469:0.8451:298420:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   -0.006:0.005:0.567191:0.8787:298420:rs3131968
1   777122  rs2980319   A   T   .   PASS    AF=0.8806   ES:SE:LP:AF:SS:ID   0.004:0.006:0.331801:0.8806:298420:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.1175   ES:SE:LP:AF:SS:ID   -0.005:0.006:0.363011:0.1175:298420:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.8787   ES:SE:LP:AF:SS:ID   0.003:0.006:0.215739:0.8787:298420:rs2977612
1   785989  rs2980300   T   C   .   PASS    AF=0.8675   ES:SE:LP:AF:SS:ID   0.004:0.006:0.359618:0.8675:298420:rs2980300
1   798801  rs12132517  G   A   .   PASS    AF=0.07649  ES:SE:LP:AF:SS:ID   0.018:0.008:1.68069:0.07649:298420:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.2015   ES:SE:LP:AF:SS:ID   0.014:0.005:2.32799:0.2015:298420:rs11240777
1   846864  rs950122    G   C   .   PASS    AF=0.1847   ES:SE:LP:AF:SS:ID   -0.006:0.006:0.613858:0.1847:298420:rs950122
1   882033  rs2272756   G   A   .   PASS    AF=0.2425   ES:SE:LP:AF:SS:ID   -0.006:0.005:0.602929:0.2425:298420:rs2272756
1   962210  rs3128126   A   G   .   PASS    AF=0.375    ES:SE:LP:AF:SS:ID   -0.003:0.004:0.313185:0.375:298420:rs3128126
1   990380  rs3121561   C   T   .   PASS    AF=0.2817   ES:SE:LP:AF:SS:ID   -0.004:0.004:0.540155:0.2817:298420:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.153    ES:SE:LP:AF:SS:ID   0.004:0.005:0.34785:0.153:298420:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7313   ES:SE:LP:AF:SS:ID   0.002:0.004:0.286593:0.7313:298420:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.1511   ES:SE:LP:AF:SS:ID   0.001:0.005:0.0433994:0.1511:298420:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.5466   ES:SE:LP:AF:SS:ID   0.004:0.003:0.617083:0.5466:298420:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5448   ES:SE:LP:AF:SS:ID   0.003:0.004:0.430392:0.5448:298420:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.1399   ES:SE:LP:AF:SS:ID   0:0.005:0.0009565:0.1399:298420:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.5634   ES:SE:LP:AF:SS:ID   0.003:0.003:0.521578:0.5634:298420:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.5634   ES:SE:LP:AF:SS:ID   0.004:0.003:0.54485:0.5634:298420:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1549   ES:SE:LP:AF:SS:ID   0:0.005:0.0197239:0.1549:298420:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.722    ES:SE:LP:AF:SS:ID   0.002:0.004:0.290645:0.722:298420:rs3737728
1   1021695 rs9442398   A   G   .   PASS    AF=0.7146   ES:SE:LP:AF:SS:ID   0.003:0.004:0.44855:0.7146:298420:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5578   ES:SE:LP:AF:SS:ID   0.004:0.003:0.522589:0.5578:298420:rs6701114
1   1025301 rs9442400   T   C   .   PASS    AF=0.91791  ES:SE:LP:AF:SS:ID   0.002:0.007:0.120904:0.91791:298420:rs9442400
1   1026707 rs4074137   C   A   .   PASS    AF=0.5914   ES:SE:LP:AF:SS:ID   0.007:0.004:1.33847:0.5914:298420:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.1474   ES:SE:LP:AF:SS:ID   -0.004:0.005:0.419759:0.1474:298420:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.1474   ES:SE:LP:AF:SS:ID   -0.005:0.005:0.502656:0.1474:298420:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.7164   ES:SE:LP:AF:SS:ID   -0.001:0.004:0.10133:0.7164:298420:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.1101   ES:SE:LP:AF:SS:ID   -0.01:0.005:1.17076:0.1101:298420:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.1306   ES:SE:LP:AF:SS:ID   -0.004:0.005:0.361311:0.1306:298420:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.1306   ES:SE:LP:AF:SS:ID   -0.004:0.005:0.388702:0.1306:298420:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.1063   ES:SE:LP:AF:SS:ID   -0.009:0.005:1.03348:0.1063:298420:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.1306   ES:SE:LP:AF:SS:ID   -0.005:0.005:0.530473:0.1306:298420:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.1082   ES:SE:LP:AF:SS:ID   -0.01:0.005:1.31283:0.1082:298420:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.2761   ES:SE:LP:AF:SS:ID   0.002:0.004:0.260507:0.2761:298420:rs7548798
1   1060608 rs17160824  G   A   .   PASS    AF=0.1082   ES:SE:LP:AF:SS:ID   -0.011:0.005:1.48241:0.1082:298420:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.1063   ES:SE:LP:AF:SS:ID   -0.01:0.005:1.33059:0.1063:298420:rs17160826
1   1061166 rs11807848  T   C   .   PASS    AF=0.4067   ES:SE:LP:AF:SS:ID   -0.003:0.004:0.471598:0.4067:298420:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.556    ES:SE:LP:AF:SS:ID   0.003:0.004:0.453951:0.556:298420:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.7369   ES:SE:LP:AF:SS:ID   0.001:0.004:0.072373:0.7369:298420:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.1287   ES:SE:LP:AF:SS:ID   -0.008:0.005:1.04861:0.1287:298420:rs2298217
1   1066029 rs12145826  G   A   .   PASS    AF=0.07649  ES:SE:LP:AF:SS:ID   -0.007:0.008:0.427012:0.07649:298420:rs12145826
1   1066403 rs10907182  T   C   .   PASS    AF=0.6101   ES:SE:LP:AF:SS:ID   0.005:0.004:0.77963:0.6101:298420:rs10907182
1   1071118 rs10907183  G   C   .   PASS    AF=0.6194   ES:SE:LP:AF:SS:ID   0.004:0.004:0.619789:0.6194:298420:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.92724  ES:SE:LP:AF:SS:ID   0.003:0.006:0.217241:0.92724:298420:rs4970357
1   1079198 rs11260603  T   C   .   PASS    AF=0.2593   ES:SE:LP:AF:SS:ID   0.001:0.005:0.0509029:0.2593:298420:rs11260603
1   1087683 rs9442380   T   C   .   PASS    AF=0.9403   ES:SE:LP:AF:SS:ID   0:0.007:0.0123337:0.9403:298420:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.97575  ES:SE:LP:AF:SS:ID   -0.013:0.011:0.679854:0.97575:298420:rs4970358
1   1094738 rs4970362   A   G   .   PASS    AF=0.6381   ES:SE:LP:AF:SS:ID   0.001:0.004:0.138466:0.6381:298420:rs4970362

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