IEU GWAS QC Report

name	value
id	ieu-a-781
pmid	24097068
year	2013
mr	1
note	Metabo-chip
trait	LDL cholesterol
category	Risk factor
subcategory	Lipid
population	Mixed
sex	Males and females
ncase	NULL
ncontrol	NULL
sample_size	83198
nsnp	120251
sd	38.6745912
priority	2
author	Willer CJ
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-781
bcf_file	ieu-a-781.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 14:08 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-781/ieu-a-781.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-781/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 11:34:13 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-781/ieu-a-781.vcf.gz ...
Read summary statistics for 119270 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, 53290 SNPs remain.
After merging with regression SNP LD, 53290 SNPs remain.
WARNING: number of SNPs less than 200k; this is almost always bad.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 1.2236 (0.4191)
Lambda GC: 1.2921
Mean Chi^2: 2.4726
Intercept: 1.1351 (0.0461)
Ratio: 0.0918 (0.0313)
Analysis finished at Wed Feb  5 11:34:23 2020
Total time elapsed: 9.63s

{
    "af_correlation": 0.9365,
    "inflation_factor": 1.2204,
    "mean_EFFECT": 0.0002,
    "n": 83197.6,
    "n_snps": 119270,
    "n_clumped_hits": 41,
    "n_p_sig": 1423,
    "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": 25,
    "n_miss_AF_reference": 756,
    "n_est": 80842.0017,
    "ratio_se_n": 0.9857,
    "mean_diff": -7.6506e-06,
    "ratio_diff": 3.7537,
    "sd_y_est1": 1.0679,
    "sd_y_est2": 1.0527,
    "r2_sum1": 0.0866,
    "r2_sum2": 0.0759,
    "r2_sum3": 0.0782,
    "r2_sum4": 0.0784,
    "ldsc_nsnp_merge_refpanel_ld": 53290,
    "ldsc_nsnp_merge_regression_ld": 53290,
    "ldsc_observed_scale_h2_beta": 1.2236,
    "ldsc_observed_scale_h2_se": 0.4191,
    "ldsc_intercept_beta": 1.1351,
    "ldsc_intercept_se": 0.0461,
    "ldsc_lambda_gc": 1.2921,
    "ldsc_mean_chisq": 2.4726,
    "ldsc_ratio": 0.0917
}

name	value
name	value
af_correlation	FALSE
inflation_factor	TRUE
n	FALSE
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	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	5	23	0	119270	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	8.655454e+00	5.544551e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.200000e+01	2.200000e+01	▇▆▆▃▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.376183e+07	5.532306e+07	4.0483e+04	2.795968e+07	6.162139e+07	1.108185e+08	2.491546e+08	▇▅▃▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	1.918000e-04	1.921650e-02	-5.8980e-01	-6.400000e-03	0.000000e+00	6.400000e-03	3.090000e-01	▁▁▁▇▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.092330e-02	1.094530e-02	5.1000e-03	5.600000e-03	7.100000e-03	1.140000e-02	2.455000e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.644603e-01	3.029176e-01	0.0000e+00	1.939001e-01	4.561997e-01	7.289001e-01	1.000000e+00	▇▆▆▆▆
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.489947e-01	3.054321e-01	0.0000e+00	1.721322e-01	4.335827e-01	7.144743e-01	1.000000e+00	▇▆▅▅▅
numeric	AF	25	0.9997904	NA	NA	NA	NA	NA	2.830127e-01	2.628648e-01	1.3190e-03	6.332000e-02	1.953000e-01	4.446000e-01	9.986810e-01	▇▃▂▂▁
numeric	AF_reference	756	0.9936614	NA	NA	NA	NA	NA	2.864424e-01	2.548989e-01	1.9970e-04	7.967250e-02	2.044730e-01	4.394970e-01	1.000000e+00	▇▃▂▂▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	7.753923e+04	1.123076e+04	2.0001e+04	7.735350e+04	8.297620e+04	8.311200e+04	8.319760e+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	721290	rs12565286	G	C	-0.0587	0.0257	0.0160901	0.0223688	0.04354	0.0371406	30614.1
1	1140435	rs1815606	G	T	-0.0148	0.0057	0.0135500	0.0094181	0.31270	0.7120610	75333.0
1	1706136	rs6603811	T	C	-0.0011	0.0108	0.9809000	0.9188743	0.93668	0.7466050	82531.1
1	1706160	rs7531583	A	G	-0.0008	0.0062	0.9394001	0.8973321	0.75730	0.5832670	77222.0
1	1708801	rs12044597	A	G	0.0061	0.0053	0.2737001	0.2497555	0.51060	0.3602240	77205.1
1	1723031	rs9660180	G	A	0.0053	0.0054	0.3595001	0.3263554	0.51320	0.3580270	74405.9
1	1812688	rs6603803	A	G	0.0053	0.0053	0.3297000	0.3173105	0.50790	0.3606230	76869.0
1	1823922	rs6688000	A	G	-0.0081	0.0114	0.5748996	0.4773778	0.94195	0.7651760	82524.6
1	1874326	rs2803328	C	G	0.0083	0.0055	0.1650000	0.1312756	0.50000	0.3835860	70716.0
1	2035379	rs10910029	A	G	-0.0029	0.0053	0.5976006	0.5842621	0.62270	0.5315500	82513.1

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	50661869	rs5771242	T	C	0.0071	0.0059	0.2247000	0.2288255	0.76780	0.8512380	82509.0
22	50672097	rs17248301	T	C	-0.0046	0.0197	0.8232001	0.8153712	0.01583	0.0517173	71802.5
22	50858813	rs7410608	G	C	0.0122	0.0053	0.0281501	0.0213416	0.34960	0.4916130	82394.1
22	50873497	rs1134848	C	T	-0.0135	0.0100	0.1605000	0.1770160	0.13980	0.0529153	51716.0
22	50873694	rs2273259	T	C	0.0100	0.0057	0.0882592	0.0793644	0.33910	0.4802320	72178.1
22	50878927	rs12171249	G	A	-0.0089	0.0062	0.1737001	0.1511493	0.28760	0.2062700	73882.0
22	51062832	rs8142033	G	A	0.0016	0.0101	0.8372000	0.8741291	0.08575	0.1773160	82502.5
22	51163138	rs715586	C	T	-0.0089	0.0075	0.2391002	0.2353591	0.12140	0.0902556	80673.9
22	51165664	rs8137951	G	A	0.0053	0.0055	0.3577997	0.3352283	0.28100	0.4063500	82520.0
22	51178090	rs2285395	G	A	0.0161	0.0116	0.1647002	0.1651580	0.05145	0.0666933	77204.8

1   721290  rs12565286  G   C   .   PASS    AF=0.04354  ES:SE:LP:AF:SS:ID   -0.0587:0.0257:1.79344:0.04354:30614.1:rs12565286
1   1140435 rs1815606   G   T   .   PASS    AF=0.3127   ES:SE:LP:AF:SS:ID   -0.0148:0.0057:1.86806:0.3127:75333:rs1815606
1   1706136 rs6603811   T   C   .   PASS    AF=0.93668  ES:SE:LP:AF:SS:ID   -0.0011:0.0108:0.00837527:0.93668:82531.1:rs6603811
1   1706160 rs7531583   A   G   .   PASS    AF=0.7573   ES:SE:LP:AF:SS:ID   -0.0008:0.0062:0.0271494:0.7573:77222:rs7531583
1   1708801 rs12044597  A   G   .   PASS    AF=0.5106   ES:SE:LP:AF:SS:ID   0.0061:0.0053:0.562725:0.5106:77205.1:rs12044597
1   1723031 rs9660180   G   A   .   PASS    AF=0.5132   ES:SE:LP:AF:SS:ID   0.0053:0.0054:0.444301:0.5132:74405.9:rs9660180
1   1812688 rs6603803   A   G   .   PASS    AF=0.5079   ES:SE:LP:AF:SS:ID   0.0053:0.0053:0.481881:0.5079:76869:rs6603803
1   1823922 rs6688000   A   G   .   PASS    AF=0.94195  ES:SE:LP:AF:SS:ID   -0.0081:0.0114:0.240408:0.94195:82524.6:rs6688000
1   1874326 rs2803328   C   G   .   PASS    AF=0.5  ES:SE:LP:AF:SS:ID   0.0083:0.0055:0.782516:0.5:70716:rs2803328
1   2035379 rs10910029  A   G   .   PASS    AF=0.6227   ES:SE:LP:AF:SS:ID   -0.0029:0.0053:0.223589:0.6227:82513.1:rs10910029
1   2069172 rs425277    C   T   .   PASS    AF=0.2836   ES:SE:LP:AF:SS:ID   0.0024:0.0057:0.162096:0.2836:82592.1:rs425277
1   2119833 rs2460002   A   G   .   PASS    AF=0.6755   ES:SE:LP:AF:SS:ID   -0.0028:0.0054:0.213249:0.6755:82574:rs2460002
1   2142518 rs380190    A   C   .   PASS    AF=0.2863   ES:SE:LP:AF:SS:ID   -0.0005:0.0061:0.0290955:0.2863:71146.9:rs380190
1   2182342 rs10797416  T   C   .   PASS    AF=0.3654   ES:SE:LP:AF:SS:ID   -0.0033:0.0053:0.238373:0.3654:82586:rs10797416
1   2184855 rs12385717  G   C   .   PASS    AF=0.06464  ES:SE:LP:AF:SS:ID   -0.0134:0.0107:0.65189:0.06464:82485.1:rs12385717
1   2204755 rs7553178   G   A   .   PASS    AF=0.6596   ES:SE:LP:AF:SS:ID   -0.0127:0.0055:1.54577:0.6596:82530:rs7553178
1   2251357 rs12080256  C   A   .   PASS    AF=0.2177   ES:SE:LP:AF:SS:ID   0.0021:0.0073:0.0587371:0.2177:64649:rs12080256
1   2280661 rs2055204   G   A   .   PASS    AF=0.5158   ES:SE:LP:AF:SS:ID   -0.013:0.0051:1.75895:0.5158:82513:rs2055204
1   2390331 rs10910077  G   A   .   PASS    AF=0.2916   ES:SE:LP:AF:SS:ID   -0.0111:0.0056:1.17659:0.2916:79950.9:rs10910077
1   2409383 rs12742193  G   A   .   PASS    AF=0.1253   ES:SE:LP:AF:SS:ID   -0.0032:0.0111:0.114695:0.1253:39179:rs12742193
1   2420913 rs6668720   A   G   .   PASS    AF=0.6359   ES:SE:LP:AF:SS:ID   0.0019:0.0053:0.121651:0.6359:82428:rs6668720
1   2541727 rs11589185  C   T   .   PASS    AF=0.07916  ES:SE:LP:AF:SS:ID   0.0043:0.0094:0.144481:0.07916:71723.8:rs11589185
1   2723345 rs4648360   C   T   .   PASS    AF=0.4288   ES:SE:LP:AF:SS:ID   0.0035:0.0051:0.301986:0.4288:82544.1:rs4648360
1   2725952 rs7538063   C   T   .   PASS    AF=0.1715   ES:SE:LP:AF:SS:ID   -0.0073:0.0071:0.488117:0.1715:78043:rs7538063
1   2727804 rs10909880  C   T   .   PASS    AF=0.4274   ES:SE:LP:AF:SS:ID   -0.0018:0.0063:0.0987052:0.4274:54836:rs10909880
1   2829551 rs1869970   A   G   .   PASS    AF=0.2322   ES:SE:LP:AF:SS:ID   -0.0023:0.0061:0.158703:0.2322:82519:rs1869970
1   2839757 rs4648432   A   C   .   PASS    AF=0.2691   ES:SE:LP:AF:SS:ID   0.0028:0.0057:0.217384:0.2691:82451:rs4648432
1   2842270 rs2045331   G   A   .   PASS    AF=0.2691   ES:SE:LP:AF:SS:ID   0.0027:0.0057:0.21056:0.2691:82501:rs2045331
1   2890345 rs4648445   G   A   .   PASS    AF=0.7111   ES:SE:LP:AF:SS:ID   0.0005:0.0055:0.0307705:0.7111:81320:rs4648445
1   2904056 rs10797373  G   A   .   PASS    AF=0.7058   ES:SE:LP:AF:SS:ID   0.0145:0.0069:1.37304:0.7058:54424:rs10797373
1   2996196 rs7525173   C   G   .   PASS    AF=0.4974   ES:SE:LP:AF:SS:ID   0.0084:0.0056:0.823909:0.4974:69184:rs7525173
1   3089849 rs17390062  T   C   .   PASS    AF=0.1135   ES:SE:LP:AF:SS:ID   -0.0054:0.0088:0.287266:0.1135:82743.4:rs17390062
1   3103826 rs4233024   C   T   .   PASS    AF=0.8522   ES:SE:LP:AF:SS:ID   0.0073:0.0092:0.317674:0.8522:54546:rs4233024
1   3105276 rs2817138   T   G   .   PASS    AF=0.8588   ES:SE:LP:AF:SS:ID   0.0054:0.0077:0.268814:0.8588:82640:rs2817138
1   3117678 rs12095716  G   C   .   PASS    AF=0.2256   ES:SE:LP:AF:SS:ID   0.003:0.0064:0.192871:0.2256:82516:rs12095716
1   3138136 rs2817148   A   G   .   PASS    AF=0.02375  ES:SE:LP:AF:SS:ID   -0.0237:0.0178:0.500313:0.02375:68844.8:rs2817148
1   3144068 rs10158583  G   A   .   PASS    AF=0.08971  ES:SE:LP:AF:SS:ID   -0.0098:0.0101:0.434034:0.08971:72857.4:rs10158583
1   3209631 rs4648376   G   A   .   PASS    AF=0.562    ES:SE:LP:AF:SS:ID   0.0035:0.0052:0.276134:0.562:82713.1:rs4648376
1   3214170 rs7553849   T   C   .   PASS    AF=0.7625   ES:SE:LP:AF:SS:ID   -0.0021:0.0062:0.117589:0.7625:82727:rs7553849
1   3229185 rs12743017  G   A   .   PASS    AF=0.07652  ES:SE:LP:AF:SS:ID   -0.0164:0.0095:1.14521:0.07652:82716.2:rs12743017
1   3264190 rs2483289   A   C   .   PASS    AF=0.7098   ES:SE:LP:AF:SS:ID   0.0026:0.0056:0.216239:0.7098:82715:rs2483289
1   3491107 rs4431782   T   C   .   PASS    AF=0.0752   ES:SE:LP:AF:SS:ID   0.0046:0.009:0.185153:0.0752:77490.8:rs4431782
1   3564818 rs3765690   A   T   .   PASS    AF=0.04222  ES:SE:LP:AF:SS:ID   -0.0027:0.012:0.103143:0.04222:81276.9:rs3765690
1   3654747 rs7515164   C   A   .   PASS    AF=0.06464  ES:SE:LP:AF:SS:ID   0.0035:0.0108:0.208731:0.06464:82681.5:rs7515164
1   3793324 rs6668103   A   G   .   PASS    AF=0.2876   ES:SE:LP:AF:SS:ID   0.0012:0.0068:0.0464819:0.2876:61672.1:rs6668103
1   3812610 rs12757243  G   A   .   PASS    AF=0.009235 ES:SE:LP:AF:SS:ID   0.0253:0.0239:0.422049:0.009235:76286.9:rs12757243
1   4010342 rs12046333  A   G   .   PASS    AF=0.06992  ES:SE:LP:AF:SS:ID   0.0056:0.0113:0.0879374:0.06992:71169:rs12046333
1   4039896 rs11587331  C   T   .   PASS    AF=0.5897   ES:SE:LP:AF:SS:ID   0.0093:0.0052:0.930702:0.5897:82723:rs11587331
1   4080885 rs4378174   C   T   .   PASS    AF=0.1583   ES:SE:LP:AF:SS:ID   0.0078:0.0074:0.521145:0.1583:82668:rs4378174
1   4085543 rs12026862  T   C   .   PASS    AF=0.01451  ES:SE:LP:AF:SS:ID   0.0298:0.0189:0.406936:0.01451:64620.7:rs12026862

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