IEU GWAS QC Report

name	value
id	ieu-a-292
pmid	23128233
year	2012
mr	1
note	NULL
trait	Inflammatory bowel disease
category	Disease
subcategory	Autoimmune / inflammatory
population	European
sex	Males and females
ncase	NULL
ncontrol	NULL
sample_size	75000
nsnp	14378
sd	NULL
priority	1
author	Jostins L
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-292
bcf_file	ieu-a-292.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 04:11 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-292/ieu-a-292.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-292/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 11:46:48 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-292/ieu-a-292.vcf.gz ...
Read summary statistics for 14352 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, 14107 SNPs remain.
After merging with regression SNP LD, 14107 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: 15.5612 (1.7143)
Lambda GC: 27.6897
Mean Chi^2: 22.684
Intercept: 8.2358 (0.3569)
Ratio: 0.3337 (0.0165)
Analysis finished at Wed Feb  5 11:46:55 2020
Total time elapsed: 7.46s

{
    "af_correlation": 0.8863,
    "inflation_factor": 27.2402,
    "mean_EFFECT": 0.0043,
    "n": 33000,
    "n_snps": 14352,
    "n_clumped_hits": 114,
    "n_p_sig": 3061,
    "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": 94,
    "n_est": 32851.0508,
    "ratio_se_n": 0.9977,
    "mean_diff": -0.0011,
    "ratio_diff": 6.003,
    "sd_y_est1": 1.4178,
    "sd_y_est2": 1.4146,
    "r2_sum1": 0.6063,
    "r2_sum2": 0.3016,
    "r2_sum3": 0.3029,
    "r2_sum4": 0.2887,
    "ldsc_nsnp_merge_refpanel_ld": 14107,
    "ldsc_nsnp_merge_regression_ld": 14107,
    "ldsc_observed_scale_h2_beta": 15.5612,
    "ldsc_observed_scale_h2_se": 1.7143,
    "ldsc_intercept_beta": 8.2358,
    "ldsc_intercept_se": 0.3569,
    "ldsc_lambda_gc": 27.6897,
    "ldsc_mean_chisq": 22.684,
    "ldsc_ratio": 0.3337
}

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	TRUE
n_clumped_hits	FALSE
r2_sum1	TRUE
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	21	0	14352	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	8.829501e+00	6.212953e+00	1.00000e+00	3.000000e+00	8.000000e+00	1.30000e+01	2.20000e+01	▇▃▃▃▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.846165e+07	5.664125e+07	6.53510e+04	3.748686e+07	6.228988e+07	1.13037e+08	2.47655e+08	▇▆▃▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	4.348100e-03	6.507820e-02	-7.09480e-01	-4.489280e-02	1.488860e-02	5.05567e-02	5.61899e-01	▁▁▇▂▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.394590e-02	6.135900e-03	1.07999e-02	1.130020e-02	1.220020e-02	1.42999e-02	2.19300e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	3.543910e-02	1.034758e-01	0.00000e+00	4.000000e-07	4.311000e-04	1.69725e-02	9.97600e-01	▇▁▁▁▁
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	3.545130e-02	1.034479e-01	0.00000e+00	4.000000e-07	4.235000e-04	1.68700e-02	1.00000e+00	▇▁▁▁▁
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	3.985416e-01	2.307958e-01	2.62000e-04	2.140000e-01	3.670000e-01	5.77000e-01	9.92000e-01	▆▇▆▅▂
numeric	AF_reference	94	0.9934504	NA	NA	NA	NA	NA	3.933883e-01	2.293012e-01	3.99400e-04	2.040730e-01	3.619210e-01	5.63898e-01	9.94010e-01	▆▇▆▅▂
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.300000e+04	0.000000e+00	3.30000e+04	3.300000e+04	3.300000e+04	3.30000e+04	3.30000e+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	1120431	rs1320571	G	A	0.0487902	0.0302005	0.1049999	0.1061932	0.0442	0.185304	33000
1	1140435	rs1815606	G	T	0.0497421	0.0125014	0.0000633	0.0000692	0.3100	0.712061	33000
1	1152631	rs11721	C	A	0.0971267	0.0174996	0.0000000	0.0000000	0.0781	0.158546	33000
1	1163804	rs7515488	C	T	0.0953102	0.0155009	0.0000000	0.0000000	0.1470	0.186901	33000
1	1165310	rs11260562	G	A	0.1079570	0.0239007	0.0000066	0.0000063	0.0546	0.101837	33000
1	1173611	rs6697886	G	A	0.0962189	0.0162001	0.0000000	0.0000000	0.1310	0.220647	33000
1	1174282	rs4970364	T	C	0.0901435	0.0141999	0.0000000	0.0000000	0.2400	0.658147	33000
1	1176597	rs6675798	T	C	0.0977231	0.0172002	0.0000000	0.0000000	0.1000	0.182109	33000
1	1177630	rs2297864	A	G	0.0980539	0.0172000	0.0000000	0.0000000	0.0990	0.170128	33000
1	1178245	rs11260566	C	T	0.0980337	0.0171993	0.0000000	0.0000000	0.0931	0.178714	33000

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	50333415	rs4073387	G	A	0.0582689	0.0174999	0.0008108	0.0008695	0.141	0.0898562	33000
22	50351977	rs28681372	G	A	-0.0294288	0.0124000	0.0179399	0.0176304	0.620	0.5822680	33000
22	50435480	rs5771069	A	G	0.0313875	0.0113001	0.0055280	0.0054757	0.509	0.6070290	33000
22	50439430	rs137845	A	G	0.0310780	0.0113000	0.0060660	0.0059547	0.507	0.6080270	33000
22	50446550	rs137862	C	A	0.0305292	0.0114007	0.0064880	0.0074100	0.514	0.5938500	33000
22	50446988	rs137864	C	T	0.0305292	0.0112993	0.0071280	0.0068951	0.508	0.5818690	33000
22	50961854	rs2782	T	C	-0.0525924	0.0114012	0.0000039	0.0000040	0.609	0.6525560	33000
22	50962208	rs12148	T	G	-0.0525924	0.0114012	0.0000039	0.0000040	0.609	0.6555510	33000
22	50966914	rs470119	T	C	-0.0525924	0.0114012	0.0000044	0.0000040	0.608	0.5547120	33000
22	50971266	rs140522	T	C	-0.0563803	0.0115991	0.0000011	0.0000012	0.669	0.6190100	33000

1   1120431 rs1320571   G   A   .   PASS    AF=0.0442   ES:SE:LP:AF:SS:ID   0.0487902:0.0302005:0.978811:0.0442:33000:rs1320571
1   1140435 rs1815606   G   T   .   PASS    AF=0.31 ES:SE:LP:AF:SS:ID   0.0497421:0.0125014:4.1988:0.31:33000:rs1815606
1   1152631 rs11721 C   A   .   PASS    AF=0.0781   ES:SE:LP:AF:SS:ID   0.0971267:0.0174996:7.52959:0.0781:33000:rs11721
1   1163804 rs7515488   C   T   .   PASS    AF=0.147    ES:SE:LP:AF:SS:ID   0.0953102:0.0155009:9.1152:0.147:33000:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.0546   ES:SE:LP:AF:SS:ID   0.107957:0.0239007:5.18013:0.0546:33000:rs11260562
1   1173611 rs6697886   G   A   .   PASS    AF=0.131    ES:SE:LP:AF:SS:ID   0.0962189:0.0162001:8.61243:0.131:33000:rs6697886
1   1174282 rs4970364   T   C   .   PASS    AF=0.24 ES:SE:LP:AF:SS:ID   0.0901435:0.0141999:9.63339:0.24:33000:rs4970364
1   1176597 rs6675798   T   C   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   0.0977231:0.0172002:7.89722:0.1:33000:rs6675798
1   1177630 rs2297864   A   G   .   PASS    AF=0.099    ES:SE:LP:AF:SS:ID   0.0980539:0.0172:7.88739:0.099:33000:rs2297864
1   1178245 rs11260566  C   T   .   PASS    AF=0.0931   ES:SE:LP:AF:SS:ID   0.0980337:0.0171993:7.87647:0.0931:33000:rs11260566
1   1178925 rs12093154  G   A   .   PASS    AF=0.0953   ES:SE:LP:AF:SS:ID   0.0980337:0.0171993:7.94539:0.0953:33000:rs12093154
1   1192515 rs7524470   A   G   .   PASS    AF=0.039    ES:SE:LP:AF:SS:ID   0.0653922:0.0234999:2.26769:0.039:33000:rs7524470
1   1193723 rs12072310  A   C   .   PASS    AF=0.051    ES:SE:LP:AF:SS:ID   0.0778534:0.0228999:3.17705:0.051:33000:rs12072310
1   1194804 rs11804831  T   C   .   PASS    AF=0.183    ES:SE:LP:AF:SS:ID   0.0990472:0.0147999:10.7077:0.183:33000:rs11804831
1   1201640 rs11260570  T   C   .   PASS    AF=0.039    ES:SE:LP:AF:SS:ID   0.0662466:0.0235001:2.3165:0.039:33000:rs11260570
1   1206343 rs6667923   C   A   .   PASS    AF=0.0354   ES:SE:LP:AF:SS:ID   0.0667236:0.0234997:2.34065:0.0354:33000:rs6667923
1   1209636 rs3737722   A   G   .   PASS    AF=0.064    ES:SE:LP:AF:SS:ID   0.0705298:0.0218001:2.92046:0.064:33000:rs3737722
1   1210471 rs11260577  T   C   .   PASS    AF=0.078    ES:SE:LP:AF:SS:ID   0.0803428:0.0210999:3.86012:0.078:33000:rs11260577
1   1211292 rs6685064   C   T   .   PASS    AF=0.0625   ES:SE:LP:AF:SS:ID   0.0695261:0.0213989:2.923:0.0625:33000:rs6685064
1   1218086 rs6603788   C   T   .   PASS    AF=0.0732   ES:SE:LP:AF:SS:ID   0.0825012:0.0212007:4.01117:0.0732:33000:rs6603788
1   1232319 rs604618    G   A   .   PASS    AF=0.0711   ES:SE:LP:AF:SS:ID   0.0861777:0.0235991:3.6038:0.0711:33000:rs604618
1   1233941 rs1739855   T   C   .   PASS    AF=0.072    ES:SE:LP:AF:SS:ID   0.0864297:0.0233001:3.69186:0.072:33000:rs1739855
1   1237036 rs2477782   T   C   .   PASS    AF=0.074    ES:SE:LP:AF:SS:ID   0.0868659:0.0231999:3.73707:0.074:33000:rs2477782
1   1239339 rs11260584  T   G   .   PASS    AF=0.9342   ES:SE:LP:AF:SS:ID   -0.0870947:0.0232994:3.71422:0.9342:33000:rs11260584
1   1239935 rs12410087  A   C   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.100705:0.0163001:9.15503:0.108:33000:rs12410087
1   1247494 rs12103 T   C   .   PASS    AF=0.818    ES:SE:LP:AF:SS:ID   -0.109751:0.0152993:12.1157:0.818:33000:rs12103
1   1249187 rs12142199  G   A   .   PASS    AF=0.811    ES:SE:LP:AF:SS:ID   -0.0977231:0.0150002:10.12:0.811:33000:rs12142199
1   1250957 rs34054191  G   A   .   PASS    AF=0.0335   ES:SE:LP:AF:SS:ID   0.0916672:0.0271012:3.17627:0.0335:33000:rs34054191
1   1254136 rs4970432   G   A   .   PASS    AF=0.931    ES:SE:LP:AF:SS:ID   -0.0842516:0.0225001:3.75056:0.931:33000:rs4970432
1   1258246 rs3845293   A   C   .   PASS    AF=0.9345   ES:SE:LP:AF:SS:ID   -0.0834216:0.0225013:3.7018:0.9345:33000:rs3845293
1   1287127 rs307380    G   A   .   PASS    AF=0.933    ES:SE:LP:AF:SS:ID   -0.0811016:0.0223:3.56976:0.933:33000:rs307380
1   1295323 rs34389364  G   A   .   PASS    AF=0.929    ES:SE:LP:AF:SS:ID   -0.0808847:0.0223002:3.5516:0.929:33000:rs34389364
1   1295403 rs34876581  T   C   .   PASS    AF=0.9326   ES:SE:LP:AF:SS:ID   -0.0806579:0.0223002:3.55783:0.9326:33000:rs34876581
1   1297065 rs2765023   C   T   .   PASS    AF=0.106    ES:SE:LP:AF:SS:ID   0.0998453:0.0161991:9.13859:0.106:33000:rs2765023
1   1297422 rs2765021   C   T   .   PASS    AF=0.932    ES:SE:LP:AF:SS:ID   -0.0806679:0.0222:3.56607:0.932:33000:rs2765021
1   1305561 rs17160669  C   T   .   PASS    AF=0.105    ES:SE:LP:AF:SS:ID   0.0971267:0.0161993:8.73377:0.105:33000:rs17160669
1   1314015 rs2649588   C   T   .   PASS    AF=0.927    ES:SE:LP:AF:SS:ID   -0.0772051:0.0217998:3.41061:0.927:33000:rs2649588
1   1333598 rs35242196  C   A   .   PASS    AF=0.0964   ES:SE:LP:AF:SS:ID   0.0925792:0.0166008:7.55098:0.0964:33000:rs35242196
1   1335790 rs1240708   A   G   .   PASS    AF=0.168    ES:SE:LP:AF:SS:ID   0.100815:0.0155001:10.0802:0.168:33000:rs1240708
1   1365570 rs1695824   A   C   .   PASS    AF=0.218    ES:SE:LP:AF:SS:ID   0.08534:0.015:7.85699:0.218:33000:rs1695824
1   1366830 rs873927    A   G   .   PASS    AF=0.218    ES:SE:LP:AF:SS:ID   0.085449:0.0151:7.84224:0.218:33000:rs873927
1   1665613 rs4648764   A   G   .   PASS    AF=0.457    ES:SE:LP:AF:SS:ID   0.0537173:0.0120999:5.0355:0.457:33000:rs4648764
1   1684472 rs7407  C   T   .   PASS    AF=0.507    ES:SE:LP:AF:SS:ID   -0.0525573:0.0116998:5.16564:0.507:33000:rs7407
1   1687625 rs34306661  T   C   .   PASS    AF=0.436    ES:SE:LP:AF:SS:ID   0.0534008:0.0116002:5.38059:0.436:33000:rs34306661
1   1689164 rs2235536   C   T   .   PASS    AF=0.424    ES:SE:LP:AF:SS:ID   0.0535408:0.0116007:5.35184:0.424:33000:rs2235536
1   1689762 rs2235537   T   C   .   PASS    AF=0.439    ES:SE:LP:AF:SS:ID   0.0528735:0.0116:5.31876:0.439:33000:rs2235537
1   1691050 rs35672141  C   T   .   PASS    AF=0.487    ES:SE:LP:AF:SS:ID   -0.0544562:0.0115002:5.70908:0.487:33000:rs35672141
1   1692321 rs1107910   T   C   .   PASS    AF=0.448    ES:SE:LP:AF:SS:ID   0.0515038:0.0113001:5.27893:0.448:33000:rs1107910
1   1707740 rs12041925  T   G   .   PASS    AF=0.262    ES:SE:LP:AF:SS:ID   0.0442654:0.0125:3.42864:0.262:33000:rs12041925
1   1708801 rs12044597  A   G   .   PASS    AF=0.497    ES:SE:LP:AF:SS:ID   -0.0573251:0.0110993:6.63676:0.497:33000:rs12044597

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