IEU GWAS QC Report

name	value
id	ieu-a-30
pmid	26192919
year	2015
mr	1
note	NULL
trait	Crohn’s disease
category	Disease
subcategory	Autoimmune / inflammatory
population	European
sex	Males and females
ncase	5956
ncontrol	14927
sample_size	20883
nsnp	12276506
sd	NULL
priority	1
author	Liu
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-30
bcf_file	ieu-a-30.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 07:23 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-30/ieu-a-30.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-30/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 09:23:07 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-30/ieu-a-30.vcf.gz ...
Read summary statistics for 11112707 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, 1289335 SNPs remain.
After merging with regression SNP LD, 1289335 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.4729 (0.0524)
Lambda GC: 1.1396
Mean Chi^2: 1.2271
Intercept: 1.0305 (0.0083)
Ratio: 0.1342 (0.0364)
Analysis finished at Wed Feb  5 09:24:45 2020
Total time elapsed: 1.0m:38.51s

{
    "af_correlation": 0.9552,
    "inflation_factor": 1.0846,
    "mean_EFFECT": 0.0472,
    "n": 20883,
    "n_snps": 11112707,
    "n_clumped_hits": 53,
    "n_p_sig": 5237,
    "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": 337907,
    "n_est": 20199.7143,
    "ratio_se_n": 0.9835,
    "mean_diff": -0.0458,
    "ratio_diff": 2.5516,
    "sd_y_est1": 2.4788,
    "sd_y_est2": 2.4379,
    "r2_sum1": 0.8914,
    "r2_sum2": 0.1451,
    "r2_sum3": 0.15,
    "r2_sum4": 0.1537,
    "ldsc_nsnp_merge_refpanel_ld": 1289335,
    "ldsc_nsnp_merge_regression_ld": 1289335,
    "ldsc_observed_scale_h2_beta": 0.4729,
    "ldsc_observed_scale_h2_se": 0.0524,
    "ldsc_intercept_beta": 1.0305,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.1396,
    "ldsc_mean_chisq": 1.2271,
    "ldsc_ratio": 0.1343
}

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	TRUE
miss_EFFECT	FALSE
miss_SE	FALSE
miss_PVAL	FALSE
ldsc_ratio	FALSE
ldsc_intercept_beta	FALSE
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	3	59	0	11112705	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	8.678906e+00	5.782672e+00	1.00000e+00	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.868417e+07	5.646563e+07	8.28000e+02	3.239124e+07	6.916853e+07	1.145303e+08	2.492395e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	4.720560e-02	3.479891e+00	-7.07933e+02	-3.640470e-02	1.199300e-03	4.039500e-02	7.085750e+02	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.370718e+00	1.620056e+02	2.18000e-02	2.810000e-02	5.140000e-02	1.355000e-01	5.276000e+04	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.876926e-01	2.917999e-01	0.00000e+00	2.330000e-01	4.823997e-01	7.406994e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.876922e-01	2.918002e-01	0.00000e+00	2.330341e-01	4.823477e-01	7.407163e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.952295e-01	2.549277e-01	2.28170e-03	1.100000e-02	6.600000e-02	2.980040e-01	9.977180e-01	▇▂▁▁▁
numeric	AF_reference	337907	0.9695927	NA	NA	NA	NA	NA	2.000123e-01	2.492573e-01	0.00000e+00	1.058310e-02	8.686100e-02	3.071090e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	2.088300e+04	0.000000e+00	2.08830e+04	2.088300e+04	2.088300e+04	2.088300e+04	2.088300e+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	10611	rs189107123	C	G	-0.2040020	0.1497	0.1728001	0.1729648	0.0207150	NA	20883
1	51479	rs116400033	T	A	-0.0826971	0.0528	0.1173000	0.1172941	0.1905740	0.1281950	20883
1	52058	rs62637813	G	C	-0.1638960	0.1095	0.1343999	0.1344539	0.0426866	NA	20883
1	52144	rs190291950	T	A	-0.1436970	0.2006	0.4737999	0.4737839	0.0123430	0.0009984	20883
1	54421	rs146477069	A	G	0.1184010	0.0870	0.1732000	0.1735355	0.0640000	NA	20883
1	54490	rs141149254	G	A	-0.0411971	0.0593	0.4874005	0.4872286	0.1417150	0.0960463	20883
1	54676	rs2462492	C	T	-0.0903953	0.0565	0.1097999	0.1096170	0.1665740	NA	20883
1	54753	rs143174675	T	G	-0.1670980	0.1282	0.1925001	0.1924326	0.0307150	NA	20883
1	55164	rs3091274	C	A	0.0594003	0.1028	0.5634002	0.5633830	0.9497150	0.9233230	20883
1	55299	rs10399749	C	T	0.0467977	0.0550	0.3951000	0.3948431	0.1755700	NA	20883

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	51227937	rs6009970	A	C	-0.7670990	1.9330	0.6914997	0.6914827	0.9949310	1.0000000	20883
22	51229805	rs9616985	T	C	-0.0197046	0.0538	0.7136003	0.7141737	0.0758590	0.0730831	20883
22	51229855	rs144549712	G	A	0.0239021	0.0561	0.6697998	0.6700624	0.0984722	0.1160140	20883
22	51234159	rs8138356	T	A	-0.2968980	0.2918	0.3089001	0.3089295	0.0067144	0.0215655	20883
22	51234677	rs189571549	A	C	-0.2981990	0.2856	0.2963999	0.2964326	0.0070000	0.0227636	20883
22	51234799	rs191117135	G	A	0.2549990	0.2066	0.2171001	0.2171044	0.0067952	0.0059904	20883
22	51237063	rs3896457	T	C	-0.0003999	0.0378	0.9925000	0.9915586	0.2430000	0.2050720	20883
22	51238249	rs149733995	A	C	-0.0739008	0.0571	0.1958001	0.1955844	0.0815740	NA	20883
23	50040891	rs192267219	C	T	-0.0966981	0.1525	0.5257000	0.5260248	0.9870000	0.0222517	20883
23	100784211	rs188350543	C	A	0.0075018	0.0290	0.7954000	0.7958803	0.7374300	0.6498010	20883

1   10611   rs189107123 C   G   .   PASS    AF=0.020715 ES:SE:LP:AF:SS:ID   -0.204002:0.1497:0.762456:0.020715:20883:rs189107123
1   51479   rs116400033 T   A   .   PASS    AF=0.190574 ES:SE:LP:AF:SS:ID   -0.0826971:0.0528:0.930702:0.190574:20883:rs116400033
1   52058   rs62637813  G   C   .   PASS    AF=0.0426866    ES:SE:LP:AF:SS:ID   -0.163896:0.1095:0.871601:0.0426866:20883:rs62637813
1   52144   rs190291950 T   A   .   PASS    AF=0.012343 ES:SE:LP:AF:SS:ID   -0.143697:0.2006:0.324405:0.012343:20883:rs190291950
1   54421   rs146477069 A   G   .   PASS    AF=0.064    ES:SE:LP:AF:SS:ID   0.118401:0.087:0.761452:0.064:20883:rs146477069
1   54490   rs141149254 G   A   .   PASS    AF=0.141715 ES:SE:LP:AF:SS:ID   -0.0411971:0.0593:0.312114:0.141715:20883:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.166574 ES:SE:LP:AF:SS:ID   -0.0903953:0.0565:0.959398:0.166574:20883:rs2462492
1   54753   rs143174675 T   G   .   PASS    AF=0.030715 ES:SE:LP:AF:SS:ID   -0.167098:0.1282:0.715569:0.030715:20883:rs143174675
1   55164   rs3091274   C   A   .   PASS    AF=0.949715 ES:SE:LP:AF:SS:ID   0.0594003:0.1028:0.249183:0.949715:20883:rs3091274
1   55299   rs10399749  C   T   .   PASS    AF=0.17557  ES:SE:LP:AF:SS:ID   0.0467977:0.055:0.403293:0.17557:20883:rs10399749
1   55326   rs3107975   T   C   .   PASS    AF=0.021285 ES:SE:LP:AF:SS:ID   0.214394:0.1348:0.951947:0.021285:20883:rs3107975
1   55394   rs2949420   T   A   .   PASS    AF=0.013457 ES:SE:LP:AF:SS:ID   -0.012599:0.1843:0.0243385:0.013457:20883:rs2949420
1   55850   rs191890754 C   G   .   PASS    AF=0.008    ES:SE:LP:AF:SS:ID   0.0628972:0.1919:0.128953:0.008:20883:rs191890754
1   55852   rs184233019 G   C   .   PASS    AF=0.00519943   ES:SE:LP:AF:SS:ID   0.395698:0.6303:0.275642:0.00519943:20883:rs184233019
1   58814   rs114420996 G   A   .   PASS    AF=0.0827412    ES:SE:LP:AF:SS:ID   0.130396:0.0752:1.08071:0.0827412:20883:rs114420996
1   61462   rs56992750  T   A   .   PASS    AF=0.00659141   ES:SE:LP:AF:SS:ID   -0.333796:0.3461:0.475085:0.00659141:20883:rs56992750
1   61987   rs76735897  A   G   .   PASS    AF=0.335715 ES:SE:LP:AF:SS:ID   -0.0425038:0.044:0.475864:0.335715:20883:rs76735897
1   61989   rs77573425  G   C   .   PASS    AF=0.335715 ES:SE:LP:AF:SS:ID   -0.0423962:0.0439:0.475994:0.335715:20883:rs77573425
1   64649   rs181431124 A   C   .   PASS    AF=0.02057  ES:SE:LP:AF:SS:ID   0.279304:0.1362:1.39491:0.02057:20883:rs181431124
1   66162   rs62639105  A   T   .   PASS    AF=0.327715 ES:SE:LP:AF:SS:ID   -0.0537967:0.0442:0.650917:0.327715:20883:rs62639105
1   66176   rs28552463  T   A   .   PASS    AF=0.00815528   ES:SE:LP:AF:SS:ID   0.457298:0.2437:1.21789:0.00815528:20883:rs28552463
1   66219   rs181028663 A   T   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.248205:0.1522:0.987163:0.021:20883:rs181028663
1   66331   rs186063952 A   C   .   PASS    AF=0.006715 ES:SE:LP:AF:SS:ID   -0.511697:0.3437:0.864549:0.006715:20883:rs186063952
1   66442   rs192044252 T   A   .   PASS    AF=0.0198852    ES:SE:LP:AF:SS:ID   0.108397:0.1541:0.317133:0.0198852:20883:rs192044252
1   66457   rs13328655  T   A   .   PASS    AF=0.0106856    ES:SE:LP:AF:SS:ID   -0.0540972:0.1989:0.104799:0.0106856:20883:rs13328655
1   66507   rs12401368  T   A   .   PASS    AF=0.0951866    ES:SE:LP:AF:SS:ID   -0.00290421:0.0716:0.014349:0.0951866:20883:rs12401368
1   73841   rs143773730 C   T   .   PASS    AF=0.231    ES:SE:LP:AF:SS:ID   0.00420116:0.0492:0.0303977:0.231:20883:rs143773730
1   77961   rs78385339  G   A   .   PASS    AF=0.0644137    ES:SE:LP:AF:SS:ID   0.109697:0.0872:0.681311:0.0644137:20883:rs78385339
1   79137   rs143777184 A   T   .   PASS    AF=0.006856 ES:SE:LP:AF:SS:ID   0.282204:0.4248:0.295421:0.006856:20883:rs143777184
1   79772   rs147215883 C   G   .   PASS    AF=0.080715 ES:SE:LP:AF:SS:ID   -0.0158044:0.0811:0.0727323:0.080715:20883:rs147215883
1   82163   rs139113303 G   A   .   PASS    AF=0.0526   ES:SE:LP:AF:SS:ID   0.0133011:0.0975:0.0498299:0.0526:20883:rs139113303
1   82249   rs1851945   A   G   .   PASS    AF=0.036    ES:SE:LP:AF:SS:ID   0.0628972:0.1186:0.224535:0.036:20883:rs1851945
1   82609   rs149189449 C   G   .   PASS    AF=0.056    ES:SE:LP:AF:SS:ID   -0.00370313:0.0945:0.0138107:0.056:20883:rs149189449
1   82676   rs185237834 T   G   .   PASS    AF=0.086715 ES:SE:LP:AF:SS:ID   -0.0273038:0.0788:0.137332:0.086715:20883:rs185237834
1   82734   rs4030331   T   C   .   PASS    AF=0.18357  ES:SE:LP:AF:SS:ID   0.0216016:0.0557:0.15602:0.18357:20883:rs4030331
1   83771   rs189906733 T   G   .   PASS    AF=0.003711 ES:SE:LP:AF:SS:ID   4.32754:4.652:0.453211:0.003711:20883:rs189906733
1   84002   rs28850140  G   A   .   PASS    AF=0.109715 ES:SE:LP:AF:SS:ID   -0.00930314:0.0676:0.0502685:0.109715:20883:rs28850140
1   84010   rs186443818 G   A   .   PASS    AF=0.0515415    ES:SE:LP:AF:SS:ID   0.169802:0.0997:1.0532:0.0515415:20883:rs186443818
1   84139   rs183605470 A   T   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.1994:0.2642:0.346305:0.01:20883:rs183605470
1   84244   rs191297051 A   C   .   PASS    AF=0.09843  ES:SE:LP:AF:SS:ID   -0.0613961:0.075:0.383735:0.09843:20883:rs191297051
1   84295   rs183209871 G   A   .   PASS    AF=0.00541306   ES:SE:LP:AF:SS:ID   -0.413396:0.4262:0.478731:0.00541306:20883:rs183209871
1   85063   rs187802690 T   C   .   PASS    AF=0.026    ES:SE:LP:AF:SS:ID   -0.0558982:0.1336:0.170118:0.026:20883:rs187802690
1   85597   rs192472955 A   C   .   PASS    AF=0.076715 ES:SE:LP:AF:SS:ID   -0.0260965:0.0811:0.126389:0.076715:20883:rs192472955
1   86018   rs142878000 C   G   .   PASS    AF=0.098    ES:SE:LP:AF:SS:ID   -0.00929665:0.0745:0.0455645:0.098:20883:rs142878000
1   86028   rs114608975 T   C   .   PASS    AF=0.058    ES:SE:LP:AF:SS:ID   -0.00750179:0.0924:0.0289098:0.058:20883:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0607144    ES:SE:LP:AF:SS:ID   -0.00399798:0.0897:0.0156077:0.0607144:20883:rs116504101
1   86303   rs2949417   G   T   .   PASS    AF=0.0987437    ES:SE:LP:AF:SS:ID   -0.0293979:0.0726:0.163676:0.0987437:20883:rs2949417
1   86331   rs115209712 A   G   .   PASS    AF=0.099715 ES:SE:LP:AF:SS:ID   -0.0227004:0.0724:0.122974:0.099715:20883:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.01257  ES:SE:LP:AF:SS:ID   0.188597:0.1866:0.505567:0.01257:20883:rs188486692
1   87190   rs1524602   G   A   .   PASS    AF=0.152711 ES:SE:LP:AF:SS:ID   0.140996:0.06:1.72469:0.152711:20883:rs1524602

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