IEU GWAS QC Report

name	value
consortium	GSCAN
note	overall sample size corresponds to the median effective sample size across SNPs
sex	Males and Females
ontology	EFO_0006525
id	ieu-b-142
unit	SD
sample_size	249752
year	2019
author	Liu M
subcategory	Behavioural
build	HG19/GRCh37
pmid	30643251
group_name	public
nsnp	12003613
population	European
category	Risk factor
trait	Cigarettes smoked per day

name	value
gwas_id	ieu-b-142
bcf_file	ieu-b-142.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2021-04-13 15:57 UTC
build_version	master-74213fc-2021-03-26

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/c9e5588b-b7db-45da-9958-cdbef9e9832d/call-ldsc/inputs/268670865/ieu-b-142.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-142/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Tue Apr 13 15:22:29 2021
Reading summary statistics from /data/cromwell-executions/qc/c9e5588b-b7db-45da-9958-cdbef9e9832d/call-ldsc/inputs/268670865/ieu-b-142.vcf.gz ...
Read summary statistics for 12000768 SNPs.
Dropped 38625 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, 1210013 SNPs remain.
After merging with regression SNP LD, 1210013 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0719 (0.0065)
Lambda GC: 1.2222
Mean Chi^2: 1.3256
Intercept: 0.9632 (0.009)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Apr 13 15:25:10 2021
Total time elapsed: 2.0m:40.94s

{
    "af_correlation": 0.9643,
    "inflation_factor": 1.1167,
    "mean_EFFECT": 0.0002,
    "n": 263956,
    "n_snps": 12003613,
    "n_clumped_hits": 23,
    "n_p_sig": 2130,
    "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": 316675,
    "n_est": 252796.1744,
    "ratio_se_n": 0.9786,
    "mean_diff": -0.0002,
    "ratio_diff": 2.2908,
    "sd_y_est1": 2.0598,
    "sd_y_est2": 2.0158,
    "r2_sum1": 0.0354,
    "r2_sum2": 0.0083,
    "r2_sum3": 0.0087,
    "r2_sum4": 0.0088,
    "ldsc_nsnp_merge_refpanel_ld": 1210013,
    "ldsc_nsnp_merge_regression_ld": 1210013,
    "ldsc_observed_scale_h2_beta": 0.0719,
    "ldsc_observed_scale_h2_se": 0.0065,
    "ldsc_intercept_beta": 0.9632,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.2222,
    "ldsc_mean_chisq": 1.3256,
    "ldsc_ratio": -0.113
}

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	2782	0.9997682	3	23	0	11999829	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	8.648272e+00	5.764243e+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	7.881140e+07	5.628402e+07	1.73000e+02	3.255261e+07	6.938894e+07	1.145416e+08	2.492385e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	1.690000e-04	3.878860e-02	-4.29195e-01	-1.060310e-02	3.770000e-05	1.073030e-02	4.622720e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	2.803460e-02	2.633740e-02	5.50530e-03	7.103900e-03	1.568750e-02	4.332120e-02	1.847140e-01	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.816127e-01	2.939517e-01	0.00000e+00	2.230001e-01	4.760001e-01	7.360003e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.816132e-01	2.939512e-01	0.00000e+00	2.222173e-01	4.760056e-01	7.367534e-01	9.999997e-01	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.676301e-01	2.453959e-01	1.00000e-03	5.130000e-03	3.640000e-02	2.410000e-01	9.990000e-01	▇▁▁▁▁
numeric	AF_reference	316675	0.9736184	NA	NA	NA	NA	NA	1.739681e-01	2.400397e-01	0.00000e+00	4.193300e-03	5.670930e-02	2.553910e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	2.254055e+05	4.504733e+04	2.64190e+04	1.991120e+05	2.497520e+05	2.597250e+05	2.639560e+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	54676	rs2462492	C	T	-0.0040647	0.0069202	0.5569997	0.5569567	0.37200	NA	56929
1	55326	rs3107975	T	C	0.0145564	0.0296514	0.6240006	0.6234846	0.00910	0.0459265	78220
1	79033	rs2462495	A	G	0.0174489	0.0743349	0.8140000	0.8144155	0.99700	NA	81377
1	79137	rs143777184	A	T	0.0700055	0.0761109	0.3580000	0.3576863	0.00220	0.0413339	62961
1	86028	rs114608975	T	C	0.0009764	0.0093093	0.9160001	0.9164704	0.09160	0.0277556	81864
1	91536	rs6702460	G	T	0.0005392	0.0060814	0.9290000	0.9293548	0.44700	0.4207270	83832
1	234313	rs8179466	C	T	-0.0043619	0.0119158	0.7149999	0.7143195	0.07500	NA	61220
1	526736	rs28863004	C	G	0.0230709	0.0240009	0.3359998	0.3364258	0.00945	0.1317890	91142
1	533198	rs78497331	C	T	0.0275874	0.0478786	0.5639999	0.5644835	0.00405	0.0814696	66754
1	534192	rs6680723	C	T	-0.0043337	0.0084026	0.6060005	0.6060275	0.23600	NA	63438

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	0.0137456	0.0553828	0.8039999	0.8039854	0.00225	0.0005990	139204
22	51229788	rs533405760	T	G	0.0074353	0.0903661	0.9340001	0.9344240	0.00123	0.0229633	88433
22	51229805	rs9616985	T	C	-0.0014901	0.0108388	0.8910000	0.8906542	0.07640	0.0730831	224158
22	51229816	rs183253204	G	A	-0.0103456	0.0893726	0.9079999	0.9078443	0.00149	0.0229633	87571
22	51230673	rs555680442	G	C	0.0151673	0.0598606	0.8000000	0.7999769	0.00174	0.0017971	139633
22	51232488	rs376461333	A	G	-0.0453464	0.0193358	0.0189998	0.0190167	0.01910	NA	134324
22	51234048	rs141330630	T	C	-0.0783230	0.0746780	0.2930003	0.2942658	0.00196	0.0095847	127634
22	51234159	rs8138356	T	A	0.2011460	0.0920985	0.0290001	0.0289600	0.00209	0.0215655	94255
22	51237063	rs3896457	T	C	-0.0014461	0.0059787	0.8090000	0.8088826	0.28600	0.2050720	201630
22	51239586	rs535432390	T	G	-0.0394083	0.0627827	0.5300002	0.5302047	0.00243	0.0001997	112757

1   54676   rs2462492   C   T   .   PASS    AF=0.372    ES:SE:LP:AF:SS:ID   -0.00406472:0.00692023:0.254145:0.372:56929:rs2462492
1   55326   rs3107975   T   C   .   PASS    AF=0.0091   ES:SE:LP:AF:SS:ID   0.0145564:0.0296514:0.204815:0.0091:78220:rs3107975
1   79033   rs2462495   A   G   .   PASS    AF=0.997    ES:SE:LP:AF:SS:ID   0.0174489:0.0743349:0.0893756:0.997:81377:rs2462495
1   79137   rs143777184 A   T   .   PASS    AF=0.0022   ES:SE:LP:AF:SS:ID   0.0700055:0.0761109:0.446117:0.0022:62961:rs143777184
1   86028   rs114608975 T   C   .   PASS    AF=0.0916   ES:SE:LP:AF:SS:ID   0.000976363:0.00930926:0.0381045:0.0916:81864:rs114608975
1   91536   rs1251109649    G   T   .   PASS    AF=0.447    ES:SE:LP:AF:SS:ID   0.000539154:0.00608137:0.0319843:0.447:83832:rs1251109649
1   234313  rs8179466   C   T   .   PASS    AF=0.075    ES:SE:LP:AF:SS:ID   -0.00436191:0.0119158:0.145694:0.075:61220:rs8179466
1   526736  rs28863004  C   G   .   PASS    AF=0.00945  ES:SE:LP:AF:SS:ID   0.0230709:0.0240009:0.473661:0.00945:91142:rs28863004
1   533198  rs1557498752    C   T   .   PASS    AF=0.00405  ES:SE:LP:AF:SS:ID   0.0275874:0.0478786:0.248721:0.00405:66754:rs1557498752
1   534192  rs6680723   C   T   .   PASS    AF=0.236    ES:SE:LP:AF:SS:ID   -0.00433367:0.00840262:0.217527:0.236:63438:rs6680723
1   544584  rs576404767 C   T   .   PASS    AF=0.00228  ES:SE:LP:AF:SS:ID   -0.0101225:0.0684012:0.0545314:0.00228:106048:rs576404767
1   546697  rs12025928  A   G   .   PASS    AF=0.917    ES:SE:LP:AF:SS:ID   0.00902947:0.011696:0.356547:0.917:89785:rs12025928
1   565130  rs371431021 G   A   .   PASS    AF=0.0043   ES:SE:LP:AF:SS:ID   0.0302587:0.0386158:0.363512:0.0043:81591:rs371431021
1   565196  rs139723294 T   C   .   PASS    AF=0.00185  ES:SE:LP:AF:SS:ID   0.0102884:0.0427201:0.091515:0.00185:85698:rs139723294
1   565469  rs554127336 C   T   .   PASS    AF=0.0028   ES:SE:LP:AF:SS:ID   -0.0621803:0.0590189:0.533132:0.0028:101311:rs554127336
1   566792  rs9283152   T   C   .   PASS    AF=0.00499  ES:SE:LP:AF:SS:ID   0.00821866:0.0453109:0.0675262:0.00499:81517:rs9283152
1   566875  rs2185539   C   T   .   PASS    AF=0.00211  ES:SE:LP:AF:SS:ID   -0.0382939:0.0641807:0.258848:0.00211:65472:rs2185539
1   567006  rs565235853 G   T   .   PASS    AF=0.00179  ES:SE:LP:AF:SS:ID   0.0460053:0.0622034:0.337242:0.00179:123087:rs565235853
1   567540  rs146275198 A   G   .   PASS    AF=0.00156  ES:SE:LP:AF:SS:ID   0.113052:0.0840307:0.74958:0.00156:65034:rs146275198
1   567726  rs560688216 T   C   .   PASS    AF=0.00325  ES:SE:LP:AF:SS:ID   0.0432953:0.0654189:0.294136:0.00325:67905:rs560688216
1   567867  rs2000096   A   G   .   PASS    AF=0.0121   ES:SE:LP:AF:SS:ID   0.0309717:0.0333395:0.452225:0.0121:72584:rs2000096
1   568201  rs4098611   T   C   .   PASS    AF=0.00182  ES:SE:LP:AF:SS:ID   0.104507:0.054552:1.25649:0.00182:60595:rs4098611
1   568322  rs9699599   A   G   .   PASS    AF=0.00202  ES:SE:LP:AF:SS:ID   0.0361731:0.0739923:0.20412:0.00202:70350:rs9699599
1   568800  rs375217967 G   A   .   PASS    AF=0.0148   ES:SE:LP:AF:SS:ID   0.0173727:0.0139541:0.67162:0.0148:81013:rs375217967
1   569204  rs112660509 T   C   .   PASS    AF=0.0026   ES:SE:LP:AF:SS:ID   0.0066166:0.0122029:0.230623:0.0026:73100:rs112660509
1   569543  rs538153094 G   A   .   PASS    AF=0.00145  ES:SE:LP:AF:SS:ID   0.00802521:0.0319986:0.0958256:0.00145:78482:rs538153094
1   569604  rs9645429   G   A   .   PASS    AF=0.00122  ES:SE:LP:AF:SS:ID   0.0366699:0.0467978:0.363512:0.00122:80002:rs9645429
1   569624  rs6594035   T   C   .   PASS    AF=0.0127   ES:SE:LP:AF:SS:ID   0.0436797:0.033902:0.703335:0.0127:55632:rs6594035
1   592007  rs771664146 G   A   .   PASS    AF=0.00163  ES:SE:LP:AF:SS:ID   0.00575513:0.104039:0.0195421:0.00163:79005:rs771664146
1   601583  rs2792926   G   A   .   PASS    AF=0.00206  ES:SE:LP:AF:SS:ID   -0.0125859:0.0640607:0.0736575:0.00206:68036:rs2792926
1   603515  rs190065153 C   A   .   PASS    AF=0.003    ES:SE:LP:AF:SS:ID   -0.0409762:0.086578:0.196543:0.003:74355:rs190065153
1   603516  rs182349900 C   A   .   PASS    AF=0.00303  ES:SE:LP:AF:SS:ID   -0.0405629:0.0874802:0.191789:0.00303:73517:rs182349900
1   693731  rs12238997  A   G   .   PASS    AF=0.122    ES:SE:LP:AF:SS:ID   0.0189452:0.00853249:1.5784:0.122:190193:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0671   ES:SE:LP:AF:SS:ID   -0.0142258:0.011938:0.630784:0.0671:126102:rs72631875
1   705942  rs544671234 A   T   .   PASS    AF=0.00176  ES:SE:LP:AF:SS:ID   -0.00772927:0.0667708:0.0419142:0.00176:97047:rs544671234
1   706368  rs963699400 A   G   .   PASS    AF=0.49 ES:SE:LP:AF:SS:ID   -0.00799705:0.0055054:0.832683:0.49:145601:rs963699400
1   710445  rs1334659872    A   G   .   PASS    AF=0.00407  ES:SE:LP:AF:SS:ID   -0.218895:0.0941975:1.6968:0.00407:63212:rs1334659872
1   713092  rs4565649   G   A   .   PASS    AF=0.00624  ES:SE:LP:AF:SS:ID   0.00861835:0.0685639:0.0457575:0.00624:104173:rs4565649
1   713977  rs74512038  C   T   .   PASS    AF=0.00621  ES:SE:LP:AF:SS:ID   0.0304419:0.0703965:0.177178:0.00621:89602:rs74512038
1   714277  rs138660747 C   A   .   PASS    AF=0.00698  ES:SE:LP:AF:SS:ID   -0.0615096:0.0372957:1.00305:0.00698:113104:rs138660747
1   714439  rs74707816  G   A   .   PASS    AF=0.00508  ES:SE:LP:AF:SS:ID   0.0381563:0.0763127:0.209715:0.00508:91312:rs74707816
1   714596  rs149887893 T   C   .   PASS    AF=0.0378   ES:SE:LP:AF:SS:ID   -0.0265501:0.0192615:0.774691:0.0378:117773:rs149887893
1   715205  rs141090730 C   G   .   PASS    AF=0.00668  ES:SE:LP:AF:SS:ID   0.0261346:0.0665971:0.158641:0.00668:103637:rs141090730
1   715265  rs12184267  C   T   .   PASS    AF=0.0408   ES:SE:LP:AF:SS:ID   -0.0235141:0.0169258:0.785156:0.0408:156175:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.0411   ES:SE:LP:AF:SS:ID   -0.0220653:0.0168737:0.721246:0.0411:157297:rs12184277
1   717474  rs141784362 C   T   .   PASS    AF=0.0061   ES:SE:LP:AF:SS:ID   0.0190829:0.0688594:0.106793:0.0061:104056:rs141784362
1   717485  rs12184279  C   A   .   PASS    AF=0.0406   ES:SE:LP:AF:SS:ID   -0.0296267:0.0185895:0.954677:0.0406:126642:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.0152   ES:SE:LP:AF:SS:ID   0.00251738:0.0251738:0.0362122:0.0152:154135:rs144155419
1   718336  rs188996809 T   C   .   PASS    AF=0.00157  ES:SE:LP:AF:SS:ID   -0.0905102:0.0621627:0.838632:0.00157:106402:rs188996809
1   720381  rs116801199 G   T   .   PASS    AF=0.0422   ES:SE:LP:AF:SS:ID   -0.0230564:0.0167711:0.772113:0.0422:159101:rs116801199

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