IEU GWAS QC Report

name	value
id	ieu-a-31
pmid	26192919
year	2015
mr	1
note	NULL
trait	Inflammatory bowel disease
category	Disease
subcategory	Autoimmune / inflammatory
population	European
sex	Males and females
ncase	12882
ncontrol	21770
sample_size	34652
nsnp	12716084
sd	NULL
priority	1
author	Liu
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-31
bcf_file	ieu-a-31.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 09:55 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-31/ieu-a-31.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-31/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 08:26:53 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-31/ieu-a-31.vcf.gz ...
Read summary statistics for 11534250 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, 1289453 SNPs remain.
After merging with regression SNP LD, 1289453 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.3163 (0.0295)
Lambda GC: 1.1749
Mean Chi^2: 1.2762
Intercept: 1.0602 (0.0076)
Ratio: 0.2179 (0.0275)
Analysis finished at Wed Feb  5 08:28:43 2020
Total time elapsed: 1.0m:50.21s

{
    "af_correlation": 0.9559,
    "inflation_factor": 1.0976,
    "mean_EFFECT": 0.0376,
    "n": 34652,
    "n_snps": 11534250,
    "n_clumped_hits": 65,
    "n_p_sig": 10299,
    "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": 355237,
    "n_est": 33627.5926,
    "ratio_se_n": 0.9851,
    "mean_diff": -0.0366,
    "ratio_diff": 2.3984,
    "sd_y_est1": 2.3472,
    "sd_y_est2": 2.3123,
    "r2_sum1": 0.6222,
    "r2_sum2": 0.1129,
    "r2_sum3": 0.1164,
    "r2_sum4": 0.1171,
    "ldsc_nsnp_merge_refpanel_ld": 1289453,
    "ldsc_nsnp_merge_regression_ld": 1289453,
    "ldsc_observed_scale_h2_beta": 0.3163,
    "ldsc_observed_scale_h2_se": 0.0295,
    "ldsc_intercept_beta": 1.0602,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.1749,
    "ldsc_mean_chisq": 1.2762,
    "ldsc_ratio": 0.218
}

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	11534248	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	8.676938e+00	5.781265e+00	1.000000	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.870886e+07	5.643752e+07	828.000000	3.245809e+07	6.921221e+07	1.145149e+08	2.492395e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	3.756900e-02	2.970484e+00	-693.057000	-2.840280e-02	9.995000e-04	3.189590e-02	7.072520e+02	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.201192e+00	1.468969e+02	0.016200	2.090000e-02	4.020000e-02	1.117000e-01	5.249000e+04	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.853253e-01	2.924002e-01	0.000000	2.295002e-01	4.797997e-01	7.381999e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.853249e-01	2.924015e-01	0.000000	2.295479e-01	4.798016e-01	7.381944e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.887332e-01	2.532762e-01	0.001744	9.473200e-03	5.774870e-02	2.842560e-01	9.976280e-01	▇▂▁▁▁
numeric	AF_reference	355237	0.9692016	NA	NA	NA	NA	NA	1.935612e-01	2.477206e-01	0.000000	8.785900e-03	7.847440e-02	2.943290e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.465200e+04	0.000000e+00	34652.000000	3.465200e+04	3.465200e+04	3.465200e+04	3.465200e+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	-0.0352996	0.1125	0.7533001	0.7536925	0.0190000	NA	34652
1	51479	rs116400033	T	A	-0.0700041	0.0383	0.0673705	0.0675821	0.1951410	0.1281950	34652
1	52058	rs62637813	G	C	-0.0096969	0.0767	0.8994000	0.8993949	0.0429513	NA	34652
1	52144	rs190291950	T	A	0.0746992	0.1420	0.5988003	0.5988530	0.0118000	0.0009984	34652
1	54421	rs146477069	A	G	-0.0071047	0.0672	0.9161000	0.9158008	0.0590000	NA	34652
1	54490	rs141149254	G	A	-0.0591027	0.0427	0.1662000	0.1663162	0.1465130	0.0960463	34652
1	54676	rs2462492	C	T	-0.0411971	0.0406	0.3100002	0.3102456	0.1692560	NA	34652
1	54753	rs143174675	T	G	-0.2109980	0.0908	0.0201298	0.0201380	0.0306280	NA	34652
1	55164	rs3091274	C	A	-0.0019018	0.0716	0.9785000	0.9788094	0.9500000	0.9233230	34652
1	55299	rs10399749	C	T	0.0371994	0.0405	0.3580997	0.3583552	0.1717440	NA	34652

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	51229855	rs144549712	G	A	0.0471984	0.0423	0.2642001	0.2645071	0.0948011	0.1160140	34652
22	51234159	rs8138356	T	A	0.0650009	0.2443	0.7902000	0.7901853	0.0068012	0.0215655	34652
22	51234199	rs6010092	T	C	0.9686110	0.6474	0.1346000	0.1346132	0.0053720	0.0313498	34652
22	51234677	rs189571549	A	C	0.1959050	0.2048	0.3387997	0.3387857	0.0070000	0.0227636	34652
22	51234799	rs191117135	G	A	0.3782990	0.1510	0.0122101	0.0122351	0.0079141	0.0059904	34652
22	51237063	rs3896457	T	C	0.0009004	0.0259	0.9708001	0.9722674	0.2596280	0.2050720	34652
22	51238249	rs149733995	A	C	-0.0082955	0.0444	0.8516999	0.8517895	0.0732560	NA	34652
23	50040891	rs192267219	C	T	-0.1788040	0.1152	0.1205999	0.1206340	0.9876280	0.0222517	34652
23	51866774	rs150899468	C	A	0.2887960	0.5595	0.6057996	0.6057371	0.9953720	0.9965560	34652
23	100784211	rs188350543	C	A	-0.0098988	0.0212	0.6418004	0.6405529	0.7386280	0.6498010	34652

1   10611   rs189107123 C   G   .   PASS    AF=0.019    ES:SE:LP:AF:SS:ID   -0.0352996:0.1125:0.123032:0.019:34652:rs189107123
1   51479   rs116400033 T   A   .   PASS    AF=0.195141 ES:SE:LP:AF:SS:ID   -0.0700041:0.0383:1.17153:0.195141:34652:rs116400033
1   52058   rs62637813  G   C   .   PASS    AF=0.0429513    ES:SE:LP:AF:SS:ID   -0.00969686:0.0767:0.0460471:0.0429513:34652:rs62637813
1   52144   rs190291950 T   A   .   PASS    AF=0.0118   ES:SE:LP:AF:SS:ID   0.0746992:0.142:0.222718:0.0118:34652:rs190291950
1   54421   rs146477069 A   G   .   PASS    AF=0.059    ES:SE:LP:AF:SS:ID   -0.0071047:0.0672:0.0380571:0.059:34652:rs146477069
1   54490   rs141149254 G   A   .   PASS    AF=0.146513 ES:SE:LP:AF:SS:ID   -0.0591027:0.0427:0.779369:0.146513:34652:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.169256 ES:SE:LP:AF:SS:ID   -0.0411971:0.0406:0.508638:0.169256:34652:rs2462492
1   54753   rs143174675 T   G   .   PASS    AF=0.030628 ES:SE:LP:AF:SS:ID   -0.210998:0.0908:1.69616:0.030628:34652:rs143174675
1   55164   rs3091274   C   A   .   PASS    AF=0.95 ES:SE:LP:AF:SS:ID   -0.00190181:0.0716:0.00943917:0.95:34652:rs3091274
1   55299   rs10399749  C   T   .   PASS    AF=0.171744 ES:SE:LP:AF:SS:ID   0.0371994:0.0405:0.445996:0.171744:34652:rs10399749
1   55326   rs3107975   T   C   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.129505:0.0998:0.71108:0.021:34652:rs3107975
1   55394   rs2949420   T   A   .   PASS    AF=0.0129115    ES:SE:LP:AF:SS:ID   0.142003:0.1316:0.552067:0.0129115:34652:rs2949420
1   55850   rs191890754 C   G   .   PASS    AF=0.007372 ES:SE:LP:AF:SS:ID   0.0398017:0.1785:0.0842837:0.007372:34652:rs191890754
1   55852   rs184233019 G   C   .   PASS    AF=0.00552242   ES:SE:LP:AF:SS:ID   0.223599:0.4708:0.197363:0.00552242:34652:rs184233019
1   58814   rs114420996 G   A   .   PASS    AF=0.0846922    ES:SE:LP:AF:SS:ID   0.0893013:0.0543:1.0013:0.0846922:34652:rs114420996
1   61462   rs56992750  T   A   .   PASS    AF=0.00706164   ES:SE:LP:AF:SS:ID   0.123199:0.2292:0.22856:0.00706164:34652:rs56992750
1   61987   rs76735897  A   G   .   PASS    AF=0.339628 ES:SE:LP:AF:SS:ID   -0.026603:0.0322:0.389446:0.339628:34652:rs76735897
1   61989   rs77573425  G   C   .   PASS    AF=0.339628 ES:SE:LP:AF:SS:ID   -0.0267958:0.0321:0.393081:0.339628:34652:rs77573425
1   64649   rs181431124 A   C   .   PASS    AF=0.019744 ES:SE:LP:AF:SS:ID   0.194204:0.1034:1.21889:0.019744:34652:rs181431124
1   66162   rs62639105  A   T   .   PASS    AF=0.331628 ES:SE:LP:AF:SS:ID   -0.0501036:0.0322:0.92336:0.331628:34652:rs62639105
1   66176   rs28552463  T   A   .   PASS    AF=0.0080106    ES:SE:LP:AF:SS:ID   0.484498:0.1828:2.09469:0.0080106:34652:rs28552463
1   66219   rs181028663 A   T   .   PASS    AF=0.018372 ES:SE:LP:AF:SS:ID   0.158597:0.1208:0.722849:0.018372:34652:rs181028663
1   66331   rs186063952 A   C   .   PASS    AF=0.006372 ES:SE:LP:AF:SS:ID   0.256003:0.2654:0.475474:0.006372:34652:rs186063952
1   66442   rs192044252 T   A   .   PASS    AF=0.0191859    ES:SE:LP:AF:SS:ID   0.037604:0.1186:0.124302:0.0191859:34652:rs192044252
1   66457   rs13328655  T   A   .   PASS    AF=0.0109744    ES:SE:LP:AF:SS:ID   -0.0982966:0.1473:0.296967:0.0109744:34652:rs13328655
1   66507   rs12401368  T   A   .   PASS    AF=0.0983513    ES:SE:LP:AF:SS:ID   0.041497:0.0507:0.38363:0.0983513:34652:rs12401368
1   73841   rs143773730 C   T   .   PASS    AF=0.231628 ES:SE:LP:AF:SS:ID   -0.0316971:0.0359:0.423313:0.231628:34652:rs143773730
1   77961   rs78385339  G   A   .   PASS    AF=0.0599141    ES:SE:LP:AF:SS:ID   -0.00859685:0.0677:0.0460471:0.0599141:34652:rs78385339
1   79137   rs143777184 A   T   .   PASS    AF=0.006372 ES:SE:LP:AF:SS:ID   0.0346018:0.3756:0.0331077:0.006372:34652:rs143777184
1   79772   rs147215883 C   G   .   PASS    AF=0.080628 ES:SE:LP:AF:SS:ID   -0.0680044:0.0587:0.607655:0.080628:34652:rs147215883
1   82163   rs139113303 G   A   .   PASS    AF=0.0541141    ES:SE:LP:AF:SS:ID   0.043902:0.0706:0.272134:0.0541141:34652:rs139113303
1   82249   rs1851945   A   G   .   PASS    AF=0.035    ES:SE:LP:AF:SS:ID   -0.0377003:0.09:0.170696:0.035:34652:rs1851945
1   82609   rs149189449 C   G   .   PASS    AF=0.058    ES:SE:LP:AF:SS:ID   0.0542028:0.0685:0.367948:0.058:34652:rs149189449
1   82676   rs185237834 T   G   .   PASS    AF=0.087    ES:SE:LP:AF:SS:ID   -0.0204985:0.0561:0.145815:0.087:34652:rs185237834
1   82734   rs4030331   T   C   .   PASS    AF=0.181    ES:SE:LP:AF:SS:ID   0.0307995:0.0412:0.34218:0.181:34652:rs4030331
1   83771   rs189906733 T   G   .   PASS    AF=0.004231 ES:SE:LP:AF:SS:ID   3.9954:4.163:0.472241:0.004231:34652:rs189906733
1   84002   rs28850140  G   A   .   PASS    AF=0.106    ES:SE:LP:AF:SS:ID   0.00590255:0.0501:0.0425364:0.106:34652:rs28850140
1   84010   rs186443818 G   A   .   PASS    AF=0.053332 ES:SE:LP:AF:SS:ID   0.0954011:0.0702:0.7597:0.053332:34652:rs186443818
1   84139   rs183605470 A   T   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   -0.155002:0.1879:0.387746:0.01:34652:rs183605470
1   84244   rs191297051 A   C   .   PASS    AF=0.099256 ES:SE:LP:AF:SS:ID   -0.0708964:0.0538:0.726536:0.099256:34652:rs191297051
1   84295   rs183209871 G   A   .   PASS    AF=0.00574268   ES:SE:LP:AF:SS:ID   0.226801:0.2988:0.348819:0.00574268:34652:rs183209871
1   85063   rs187802690 T   C   .   PASS    AF=0.025    ES:SE:LP:AF:SS:ID   0.028595:0.1008:0.109914:0.025:34652:rs187802690
1   85597   rs192472955 A   C   .   PASS    AF=0.077628 ES:SE:LP:AF:SS:ID   -0.0657035:0.0585:0.583359:0.077628:34652:rs192472955
1   86018   rs142878000 C   G   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.0352996:0.0531:0.295764:0.1:34652:rs142878000
1   86028   rs114608975 T   C   .   PASS    AF=0.059628 ES:SE:LP:AF:SS:ID   -0.0147014:0.0673:0.0824945:0.059628:34652:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.0623654    ES:SE:LP:AF:SS:ID   0.0141987:0.0653:0.0818648:0.0623654:34652:rs116504101
1   86303   rs2949417   G   T   .   PASS    AF=0.100628 ES:SE:LP:AF:SS:ID   -0.0289964:0.0521:0.238674:0.100628:34652:rs2949417
1   86331   rs115209712 A   G   .   PASS    AF=0.102628 ES:SE:LP:AF:SS:ID   -0.0289955:0.0515:0.242225:0.102628:34652:rs115209712
1   87021   rs188486692 T   C   .   PASS    AF=0.014    ES:SE:LP:AF:SS:ID   -0.0291024:0.1312:0.0837567:0.014:34652:rs188486692
1   87190   rs1524602   G   A   .   PASS    AF=0.151372 ES:SE:LP:AF:SS:ID   0.0356953:0.0446:0.373249:0.151372:34652:rs1524602

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