IEU GWAS QC Report

name	value
build	HG19/GRCh37
covariates	ancestry PCs
year	2019
id	ieu-b-73
sex	Males and Females
pmid	30643251
category	Continuous
doi	10.1038/s41588-018-0307-5
author	Liu, M
subcategory	Behavioural
consortium	GWAS and Sequencing Consortium of Alcohol and Nicotine use
group_name	public
population	European
sample_size	335394
nsnp	11887865
trait	Alcoholic drinks per week
study_design	Meta-analysis of cohort/cross-sectional studies
imputation_panel	HRC
coverage	whole genome
mr	1
qc_prior_to_upload	mapped rsids to genomic position

name	value
gwas_id	ieu-b-73
bcf_file	ieu-b-73.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-11-24 20:37 UTC
build_version	master-2dbfcc4-2020-10-23

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 /data/cromwell-executions/qc/22abd93d-3510-4ca4-b903-2b3c93d7533c/call-ldsc/inputs/562856314/ieu-b-73.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-73/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Tue Nov 24 20:12:22 2020
Reading summary statistics from /data/cromwell-executions/qc/22abd93d-3510-4ca4-b903-2b3c93d7533c/call-ldsc/inputs/562856314/ieu-b-73.vcf.gz ...
Read summary statistics for 11887091 SNPs.
Dropped 37432 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1206690 SNPs remain.
After merging with regression SNP LD, 1206690 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0482 (0.0021)
Lambda GC: 1.3124
Mean Chi^2: 1.4431
Intercept: 0.9324 (0.0086)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Nov 24 20:14:14 2020
Total time elapsed: 1.0m:51.57s

{
    "af_correlation": 0.9641,
    "inflation_factor": 1.1268,
    "mean_EFFECT": -0.0001,
    "n": 537352,
    "n_snps": 11887400,
    "n_clumped_hits": 35,
    "n_p_sig": 5195,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 296452,
    "n_est": 516757.6348,
    "ratio_se_n": 0.9806,
    "mean_diff": 0,
    "ratio_diff": 1.0149,
    "sd_y_est1": 1.0231,
    "sd_y_est2": 1.0033,
    "r2_sum1": 0.0063,
    "r2_sum2": 0.006,
    "r2_sum3": 0.0062,
    "r2_sum4": 0.0048,
    "ldsc_nsnp_merge_refpanel_ld": 1206690,
    "ldsc_nsnp_merge_regression_ld": 1206690,
    "ldsc_observed_scale_h2_beta": 0.0482,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 0.9324,
    "ldsc_intercept_se": 0.0086,
    "ldsc_lambda_gc": 1.3124,
    "ldsc_mean_chisq": 1.4431,
    "ldsc_ratio": -0.1526
}

name	value
name	value
af_correlation	FALSE
inflation_factor	FALSE
n	FALSE
is_snpid_non_unique	TRUE
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	260	0.9999781	3	23	0	11886496	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	8.655097e+00	5.768289e+00	1.00000e+00	4.000000e+00	8.000000e+00	1.300000e+01	2.200000e+01	▇▅▃▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.875946e+07	5.630030e+07	1.73000e+02	3.249008e+07	6.934299e+07	1.144971e+08	2.492385e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-7.240000e-05	1.256800e-02	-2.51222e-01	-3.810900e-03	-1.690000e-05	3.737800e-03	1.881150e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	9.499200e-03	8.723800e-03	1.92920e-03	2.468900e-03	5.399900e-03	1.487970e-02	5.612470e-02	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.791770e-01	2.956168e-01	0.00000e+00	2.180003e-01	4.739996e-01	7.360003e-01	1.000000e+00	▇▇▇▆▆
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.791775e-01	2.956162e-01	0.00000e+00	2.176204e-01	4.738422e-01	7.356353e-01	1.000000e+00	▇▇▆▆▆
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.679213e-01	2.448872e-01	1.00000e-03	5.250000e-03	3.720000e-02	2.410000e-01	9.990000e-01	▇▁▁▁▁
numeric	AF_reference	296452	0.9750617	NA	NA	NA	NA	NA	1.738887e-01	2.395603e-01	0.00000e+00	4.193300e-03	5.710860e-02	2.557910e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	4.696303e+05	8.082826e+04	5.78440e+04	4.188720e+05	5.132690e+05	5.304320e+05	5.373520e+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	49298	rs200943160	T	C	0.0025868	0.0022600	0.2520003	0.2523938	0.64000	0.7821490	147852
1	54676	rs2462492	C	T	-0.0002940	0.0023613	0.9010000	0.9009203	0.37200	NA	120693
1	55326	rs3107975	T	C	-0.0084691	0.0095648	0.3760001	0.3759205	0.00910	0.0459265	159859
1	79033	rs2462495	A	G	0.0011374	0.0127250	0.9290000	0.9287743	0.99700	NA	172280
1	79137	rs143777184	A	T	-0.0157255	0.0203185	0.4390005	0.4389604	0.00220	0.0413339	169985
1	86028	rs114608975	T	C	-0.0039748	0.0034210	0.2459999	0.2452777	0.09160	0.0277556	170207
1	91536	rs6702460	G	T	0.0009076	0.0020398	0.6560002	0.6563398	0.44700	0.4207270	167723
1	234313	rs8179466	C	T	-0.0017084	0.0044866	0.7029995	0.7033603	0.07500	NA	107381
1	526736	rs28863004	C	G	0.0196406	0.0095159	0.0389000	0.0390201	0.00945	0.1317890	173338
1	533179	rs111501994	A	G	0.0574957	0.0244496	0.0185999	0.0186928	0.00159	0.0299521	187286

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	51227766	rs186062720	T	C	0.0266713	0.0205164	0.1929999	0.1936013	0.00225	0.0005990	272924
22	51229788	rs533405760	T	G	-0.0167419	0.0311427	0.5909993	0.5908624	0.00123	0.0229633	221077
22	51229805	rs9616985	T	C	-0.0033732	0.0037342	0.3659999	0.3663532	0.07640	0.0730831	462570
22	51229816	rs183253204	G	A	-0.0122730	0.0287682	0.6689998	0.6696584	0.00149	0.0229633	223407
22	51230673	rs555680442	G	C	0.0003646	0.0218260	0.9870000	0.9866733	0.00174	0.0017971	260977
22	51232488	rs376461333	A	G	-0.0081148	0.0076338	0.2870001	0.2877752	0.01910	NA	234071
22	51234048	rs141330630	T	C	-0.0266789	0.0265465	0.3150003	0.3149029	0.00196	0.0095847	250749
22	51234159	rs8138356	T	A	-0.0251137	0.0249890	0.3140003	0.3149016	0.00209	0.0215655	242489
22	51237063	rs3896457	T	C	0.0022835	0.0021111	0.2789999	0.2794014	0.28600	0.2050720	400345
22	51239586	rs535432390	T	G	-0.0144818	0.0211690	0.4940001	0.4939094	0.00243	0.0001997	262462

1   49298   rs10399793  T   C   .   PASS    AF=0.64 ES:SE:LP:AF:SS:ID   0.00258675:0.00226005:0.598599:0.64:147852:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.372    ES:SE:LP:AF:SS:ID   -0.000293978:0.00236129:0.0452752:0.372:120693:rs2462492
1   55326   rs3107975   T   C   .   PASS    AF=0.0091   ES:SE:LP:AF:SS:ID   -0.00846908:0.00956485:0.424812:0.0091:159859:rs3107975
1   79033   rs2462495   A   G   .   PASS    AF=0.997    ES:SE:LP:AF:SS:ID   0.00113745:0.012725:0.0319843:0.997:172280:rs2462495
1   79137   rs143777184 A   T   .   PASS    AF=0.0022   ES:SE:LP:AF:SS:ID   -0.0157255:0.0203185:0.357535:0.0022:169985:rs143777184
1   86028   rs114608975 T   C   .   PASS    AF=0.0916   ES:SE:LP:AF:SS:ID   -0.0039748:0.00342096:0.609065:0.0916:170207:rs114608975
1   91536   rs1251109649    G   T   .   PASS    AF=0.447    ES:SE:LP:AF:SS:ID   0.000907641:0.00203977:0.183096:0.447:167723:rs1251109649
1   234313  rs8179466   C   T   .   PASS    AF=0.075    ES:SE:LP:AF:SS:ID   -0.00170843:0.00448656:0.153045:0.075:107381:rs8179466
1   526736  rs28863004  C   G   .   PASS    AF=0.00945  ES:SE:LP:AF:SS:ID   0.0196406:0.00951591:1.41005:0.00945:173338:rs28863004
1   533179  rs1557498752    A   G   .   PASS    AF=0.00159  ES:SE:LP:AF:SS:ID   0.0574957:0.0244496:1.73049:0.00159:187286:rs1557498752
1   533198  rs1557498752    C   T   .   PASS    AF=0.00405  ES:SE:LP:AF:SS:ID   -0.00623348:0.010462:0.258848:0.00405:181664:rs1557498752
1   534192  rs6680723   C   T   .   PASS    AF=0.236    ES:SE:LP:AF:SS:ID   0.00195589:0.00274148:0.323306:0.236:127681:rs6680723
1   544584  rs576404767 C   T   .   PASS    AF=0.00228  ES:SE:LP:AF:SS:ID   0.0430933:0.0258923:1.01818:0.00228:191631:rs576404767
1   546697  rs12025928  A   G   .   PASS    AF=0.917    ES:SE:LP:AF:SS:ID   0.00671172:0.0043324:0.917215:0.917:163876:rs12025928
1   565111  rs573042692 T   C   .   PASS    AF=0.00142  ES:SE:LP:AF:SS:ID   0.0139421:0.0288836:0.201349:0.00142:129667:rs573042692
1   565130  rs371431021 G   A   .   PASS    AF=0.0043   ES:SE:LP:AF:SS:ID   0.0206599:0.0138974:0.863279:0.0043:154853:rs371431021
1   565196  rs139723294 T   C   .   PASS    AF=0.00185  ES:SE:LP:AF:SS:ID   0.0304671:0.0151206:1.35853:0.00185:161949:rs139723294
1   565469  rs554127336 C   T   .   PASS    AF=0.0028   ES:SE:LP:AF:SS:ID   0.000376125:0.020768:0.00612309:0.0028:174863:rs554127336
1   565490  rs7349153   T   C   .   PASS    AF=0.00166  ES:SE:LP:AF:SS:ID   -0.00899762:0.00922651:0.481486:0.00166:121094:rs7349153
1   565728  rs199661867 C   A   .   PASS    AF=0.00131  ES:SE:LP:AF:SS:ID   -0.00278128:0.0265184:0.0381045:0.00131:135841:rs199661867
1   566024  rs6421779   G   A   .   PASS    AF=0.00162  ES:SE:LP:AF:SS:ID   -0.00111432:0.0154827:0.0254883:0.00162:123800:rs6421779
1   566371  rs1832731   A   G   .   PASS    AF=0.0018   ES:SE:LP:AF:SS:ID   0.00447365:0.0265931:0.0624821:0.0018:124469:rs1832731
1   566792  rs9283152   T   C   .   PASS    AF=0.00499  ES:SE:LP:AF:SS:ID   0.000679184:0.0160532:0.0150229:0.00499:165124:rs9283152
1   566875  rs2185539   C   T   .   PASS    AF=0.00211  ES:SE:LP:AF:SS:ID   -0.00897588:0.0221644:0.163676:0.00211:165486:rs2185539
1   567006  rs565235853 G   T   .   PASS    AF=0.00179  ES:SE:LP:AF:SS:ID   0.0172485:0.0216453:0.37059:0.00179:235616:rs565235853
1   567092  rs9326622   T   C   .   PASS    AF=0.00183  ES:SE:LP:AF:SS:ID   -0.0118971:0.0148482:0.37366:0.00183:128215:rs9326622
1   567119  rs9283153   A   C   .   PASS    AF=0.00188  ES:SE:LP:AF:SS:ID   -0.0110547:0.014733:0.343902:0.00188:127402:rs9283153
1   567540  rs146275198 A   G   .   PASS    AF=0.00156  ES:SE:LP:AF:SS:ID   0.0163132:0.0296849:0.234331:0.00156:165354:rs146275198
1   567726  rs560688216 T   C   .   PASS    AF=0.00325  ES:SE:LP:AF:SS:ID   -0.003042:0.022611:0.0491485:0.00325:169986:rs560688216
1   567867  rs2000096   A   G   .   PASS    AF=0.0121   ES:SE:LP:AF:SS:ID   -0.00946177:0.0114995:0.386158:0.0121:181243:rs2000096
1   568201  rs4098611   T   C   .   PASS    AF=0.00182  ES:SE:LP:AF:SS:ID   -0.00699387:0.0247425:0.109579:0.00182:106570:rs4098611
1   568322  rs9699599   A   G   .   PASS    AF=0.00202  ES:SE:LP:AF:SS:ID   -0.00487847:0.0255351:0.0716041:0.00202:175371:rs9699599
1   568800  rs375217967 G   A   .   PASS    AF=0.0148   ES:SE:LP:AF:SS:ID   0.000124943:0.0059362:0.00744648:0.0148:150266:rs375217967
1   569004  rs9285835   T   C   .   PASS    AF=0.013    ES:SE:LP:AF:SS:ID   -0.00982064:0.0108583:0.436519:0.013:100793:rs9285835
1   569204  rs112660509 T   C   .   PASS    AF=0.0026   ES:SE:LP:AF:SS:ID   -0.00740274:0.00413826:1.13253:0.0026:139277:rs112660509
1   569543  rs538153094 G   A   .   PASS    AF=0.00145  ES:SE:LP:AF:SS:ID   0.00695883:0.0115981:0.261219:0.00145:145160:rs538153094
1   569604  rs9645429   G   A   .   PASS    AF=0.00122  ES:SE:LP:AF:SS:ID   0.01339:0.0164819:0.380907:0.00122:155811:rs9645429
1   600495  rs147241137 G   C   .   PASS    AF=0.00208  ES:SE:LP:AF:SS:ID   0.0240608:0.0311665:0.356547:0.00208:230828:rs147241137
1   601583  rs2792926   G   A   .   PASS    AF=0.00206  ES:SE:LP:AF:SS:ID   0.00202989:0.0177352:0.0414361:0.00206:184067:rs2792926
1   603515  rs190065153 C   A   .   PASS    AF=0.003    ES:SE:LP:AF:SS:ID   0.0082095:0.0223434:0.14691:0.003:195742:rs190065153
1   603516  rs182349900 C   A   .   PASS    AF=0.00303  ES:SE:LP:AF:SS:ID   0.00769421:0.0224942:0.135489:0.00303:193100:rs182349900
1   612758  rs4387125   T   C   .   PASS    AF=0.00662  ES:SE:LP:AF:SS:ID   0.011705:0.0157831:0.339135:0.00662:93751:rs4387125
1   636975  rs144572927 G   A   .   PASS    AF=0.00303  ES:SE:LP:AF:SS:ID   0.0492851:0.03293:0.869666:0.00303:249070:rs144572927
1   693731  rs12238997  A   G   .   PASS    AF=0.122    ES:SE:LP:AF:SS:ID   -0.0022522:0.00301232:0.342944:0.122:398857:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0671   ES:SE:LP:AF:SS:ID   0.00105074:0.00406847:0.0990869:0.0671:263393:rs72631875
1   705942  rs544671234 A   T   .   PASS    AF=0.00176  ES:SE:LP:AF:SS:ID   -0.0577158:0.0231605:1.8962:0.00176:184108:rs544671234
1   706368  rs963699400 A   G   .   PASS    AF=0.49 ES:SE:LP:AF:SS:ID   0.00123837:0.0019293:0.283162:0.49:293820:rs963699400
1   710445  rs1334659872    A   G   .   PASS    AF=0.00407  ES:SE:LP:AF:SS:ID   0.0580638:0.0339212:1.06098:0.00407:163011:rs1334659872
1   713092  rs4565649   G   A   .   PASS    AF=0.00624  ES:SE:LP:AF:SS:ID   0.0150394:0.0200259:0.343902:0.00624:265910:rs4565649
1   713977  rs74512038  C   T   .   PASS    AF=0.00621  ES:SE:LP:AF:SS:ID   0.00764212:0.0157645:0.20204:0.00621:239792:rs74512038

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