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IEU GWAS information

Trait: Disorders of gallbladder, biliary tract and pancreas.

name	value
id	ukb-d-K11_GALLBILPANC
trait	Disorders of gallbladder, biliary tract and pancreas
category	Binary
ncase	13922
ncontrol	347272
sample_size	361194
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
mr	1
nsnp	13586589

Report information

name	value
gwas_id	ukb-d-K11_GALLBILPANC
bcf_file	ukb-d-K11_GALLBILPANC.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-09 17:45 BST
build_version	run_igd-8f4f4c9-2020-05-09

Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

$af_plot$

af_plot

P-Z plot

pz_plot

beta_std plot

beta_std_plot

Metadata

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}

LDSC

*********************************************************************
* 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/ukb-d-import/processed/ukb-d-K11_GALLBILPANC/ukb-d-K11_GALLBILPANC.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/ukb-d-import/processed/ukb-d-K11_GALLBILPANC/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 15:35:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-K11_GALLBILPANC/ukb-d-K11_GALLBILPANC.vcf.gz ...
Read summary statistics for 13586588 SNPs.
Dropped 12710 SNPs with duplicated rs numbers.
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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0163 (0.0021)
Lambda GC: 1.1065
Mean Chi^2: 1.1337
Intercept: 1.0206 (0.0066)
Ratio: 0.1537 (0.0495)
Analysis finished at Mon Nov 25 15:37:45 2019
Total time elapsed: 2.0m:18.37s

QC metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0646,
    "mean_EFFECT": 5.5676e-06,
    "n": 361194,
    "n_snps": 13586588,
    "n_clumped_hits": 19,
    "n_p_sig": 1349,
    "n_mono": 0,
    "n_ns": 1251809,
    "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": 569299,
    "n_est": 362577.4768,
    "ratio_se_n": 1.0019,
    "mean_diff": 0,
    "ratio_diff": 50.1784,
    "sd_y_est1": 0.1927,
    "sd_y_est2": 0.1931,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0051,
    "r2_sum3": 0.0051,
    "r2_sum4": 0.0051,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0163,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.0206,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.1065,
    "ldsc_mean_chisq": 1.1337,
    "ldsc_ratio": 0.1541
}

Flags

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	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	FALSE
r2_sum2	FALSE
r2_sum3	FALSE
r2_sum4	FALSE

Definitions

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 $\beta_j$

Diagnostics

Details

Summary stats

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	94	0	13574542	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	57083	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	342	0	33337	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	9.051333e+00	6.184971e+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	7.902505e+07	5.591478e+07	3.02000e+02	3.293100e+07	7.013845e+07	1.148590e+08	2.492309e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	5.600000e-06	2.657900e-03	-2.74279e-02	-7.322000e-04	-3.400000e-06	7.223000e-04	4.272760e-02	▁▇▃▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.905800e-03	1.838400e-03	3.72900e-04	5.426000e-04	9.998000e-04	2.738800e-03	9.248800e-03	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.898963e-01	2.913334e-01	0.00000e+00	2.349492e-01	4.864755e-01	7.422753e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.898959e-01	2.913336e-01	0.00000e+00	2.349477e-01	4.864757e-01	7.422760e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.908016e-01	2.544020e-01	1.00000e-03	7.429000e-03	6.002940e-02	2.953060e-01	9.989990e-01	▇▂▁▁▁
numeric	AF_reference	569299	0.9580985	NA	NA	NA	NA	NA	1.963330e-01	2.471005e-01	0.00000e+00	5.591000e-03	8.426520e-02	3.081070e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.611940e+05	0.000000e+00	3.61194e+05	3.611940e+05	3.611940e+05	3.611940e+05	3.611940e+05	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	0.0004273	0.0007942	0.5905518	0.5905510	0.1106400	0.1894970	361194
1	693731	rs12238997	A	G	0.0000102	0.0007504	0.9891400	0.9891399	0.1158300	0.1417730	361194
1	707522	rs371890604	G	C	0.0000335	0.0008436	0.9683091	0.9683094	0.0973034	0.1293930	361194
1	717587	rs144155419	G	A	-0.0016979	0.0020131	0.3989964	0.3989971	0.0156880	0.0045926	361194
1	723329	rs189787166	A	T	0.0052036	0.0059395	0.3809746	0.3809740	0.0017336	0.0003994	361194
1	730087	rs148120343	T	C	-0.0004490	0.0010454	0.6675534	0.6675537	0.0564602	0.0127796	361194
1	731718	rs142557973	T	C	0.0000257	0.0007117	0.9711871	0.9711872	0.1217380	0.1543530	361194
1	732032	rs61770163	A	C	0.0001805	0.0007592	0.8121060	0.8121052	0.1211710	0.1555510	361194
1	734349	rs141242758	T	C	-0.0000053	0.0007121	0.9940860	0.9940862	0.1209650	0.1525560	361194
1	740284	rs61770167	C	T	0.0033910	0.0032578	0.2979312	0.2979299	0.0057851	0.0023962	361194

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	0.0002232	0.0008222	0.7860008	0.7860007	0.0561667	0.0309934	361194
23	154923374	rs111332691	T	A	0.0017095	0.0009036	0.0585167	0.0585155	0.0447862	0.0116556	361194
23	154925045	rs509981	C	T	-0.0003598	0.0004348	0.4079360	0.4079358	0.2456060	0.3634440	361194
23	154925895	rs538470	C	T	-0.0004706	0.0004448	0.2900628	0.2900618	0.2419150	0.3634440	361194
23	154927581	rs644138	G	A	-0.0002604	0.0004089	0.5241770	0.5241760	0.3021620	0.4635760	361194
23	154929412	rs557132	C	T	-0.0003494	0.0004349	0.4217043	0.4217047	0.2454590	0.3568210	361194
23	154929637	rs35185538	CT	C	-0.0001867	0.0004539	0.6808101	0.6808111	0.2296970	0.3011920	361194
23	154929952	rs4012982	CAA	C	-0.0003279	0.0004574	0.4734739	0.4734745	0.2394250	0.3165560	361194
23	154930230	rs781880	A	G	-0.0004038	0.0004348	0.3531449	0.3531444	0.2458690	0.3618540	361194
23	154930487	rs781879	T	A	-0.0002017	0.0014918	0.8924360	0.8924360	0.0195623	0.1263580	361194

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11064  ES:SE:LP:AF:SS:ID   0.000427315:0.00079421:0.228742:0.11064:361194:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11583  ES:SE:LP:AF:SS:ID   1.02145e-05:0.000750432:0.00474224:0.11583:361194:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973034    ES:SE:LP:AF:SS:ID   3.35167e-05:0.00084364:0.013986:0.0973034:361194:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015688 ES:SE:LP:AF:SS:ID   -0.00169791:0.00201314:0.399031:0.015688:361194:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173363   ES:SE:LP:AF:SS:ID   0.00520364:0.00593953:0.419104:0.00173363:361194:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564602    ES:SE:LP:AF:SS:ID   -0.000449029:0.00104545:0.175514:0.0564602:361194:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121738 ES:SE:LP:AF:SS:ID   2.57065e-05:0.000711711:0.0126971:0.121738:361194:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121171 ES:SE:LP:AF:SS:ID   0.000180465:0.000759178:0.0903873:0.121171:361194:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120965 ES:SE:LP:AF:SS:ID   -5.27802e-06:0.000712094:0.00257604:0.120965:361194:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578512   ES:SE:LP:AF:SS:ID   0.00339103:0.00325784:0.525884:0.00578512:361194:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187787   ES:SE:LP:AF:SS:ID   -0.0128712:0.00615272:1.43838:0.00187787:361194:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869742 ES:SE:LP:AF:SS:ID   -0.000122808:0.000702012:0.0649318:0.869742:361194:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153021   ES:SE:LP:AF:SS:ID   -0.000635235:0.00635529:0.0360324:0.00153021:361194:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122916 ES:SE:LP:AF:SS:ID   0.000320489:0.00069525:0.190561:0.122916:361194:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142712 ES:SE:LP:AF:SS:ID   0.000131967:0.000687217:0.0717486:0.142712:361194:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123031 ES:SE:LP:AF:SS:ID   0.000322822:0.000694282:0.192497:0.123031:361194:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87089  ES:SE:LP:AF:SS:ID   -7.70529e-05:0.000676556:0.0412809:0.87089:361194:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875472 ES:SE:LP:AF:SS:ID   -0.000178803:0.000687767:0.0996968:0.875472:361194:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   0.000199315:0.000678252:0.114153:0.128631:361194:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363613    ES:SE:LP:AF:SS:ID   -0.000616731:0.00123051:0.210257:0.0363613:361194:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870484 ES:SE:LP:AF:SS:ID   -8.86568e-05:0.000675852:0.0478689:0.870484:361194:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870589 ES:SE:LP:AF:SS:ID   -0.000103984:0.000676161:0.0566148:0.870589:361194:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870481 ES:SE:LP:AF:SS:ID   -0.000106933:0.000675827:0.0583495:0.870481:361194:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504367   ES:SE:LP:AF:SS:ID   -0.000607243:0.00346958:0.0649641:0.00504367:361194:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501064   ES:SE:LP:AF:SS:ID   -0.000494279:0.00347887:0.0520681:0.00501064:361194:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558665   ES:SE:LP:AF:SS:ID   0.0020935:0.00336037:0.273039:0.00558665:361194:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870563 ES:SE:LP:AF:SS:ID   -7.31863e-05:0.000674638:0.0392377:0.870563:361194:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125985 ES:SE:LP:AF:SS:ID   0.00022197:0.000688378:0.126616:0.125985:361194:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870127 ES:SE:LP:AF:SS:ID   -7.95027e-05:0.000673014:0.0428886:0.870127:361194:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869414 ES:SE:LP:AF:SS:ID   -0.000179634:0.000672401:0.10273:0.869414:361194:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870281 ES:SE:LP:AF:SS:ID   -0.000103126:0.000673593:0.0563467:0.870281:361194:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   -0.000103002:0.000673641:0.0562706:0.870287:361194:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870295 ES:SE:LP:AF:SS:ID   -9.9823e-05:0.000673662:0.0544325:0.870295:361194:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870739 ES:SE:LP:AF:SS:ID   -9.85898e-05:0.000675378:0.0535777:0.870739:361194:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988442    ES:SE:LP:AF:SS:ID   0.000366129:0.00078483:0.193242:0.0988442:361194:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647588   ES:SE:LP:AF:SS:ID   0.000600103:0.00303577:0.0740194:0.00647588:361194:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874635 ES:SE:LP:AF:SS:ID   -0.000156743:0.000685443:0.0866514:0.874635:361194:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864027 ES:SE:LP:AF:SS:ID   -3.37016e-05:0.000672179:0.0177229:0.864027:361194:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869425 ES:SE:LP:AF:SS:ID   -7.09451e-05:0.000678705:0.0377496:0.869425:361194:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866371 ES:SE:LP:AF:SS:ID   -3.09645e-05:0.000678842:0.0160951:0.866371:361194:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987831    ES:SE:LP:AF:SS:ID   0.000797747:0.0008127:0.486387:0.0987831:361194:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871556 ES:SE:LP:AF:SS:ID   -3.09448e-05:0.000686576:0.0159:0.871556:361194:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871556 ES:SE:LP:AF:SS:ID   -3.09268e-05:0.000686576:0.015891:0.871556:361194:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871555 ES:SE:LP:AF:SS:ID   -3.13566e-05:0.000686589:0.0161154:0.871555:361194:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871929 ES:SE:LP:AF:SS:ID   -3.05461e-05:0.000686981:0.0156825:0.871929:361194:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125562 ES:SE:LP:AF:SS:ID   0.00012559:0.000687523:0.0680049:0.125562:361194:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105428 ES:SE:LP:AF:SS:ID   0.000371454:0.000748462:0.207826:0.105428:361194:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855376 ES:SE:LP:AF:SS:ID   -4.30416e-05:0.000671927:0.0227681:0.855376:361194:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165444   ES:SE:LP:AF:SS:ID   0.00410435:0.0059523:0.309375:0.00165444:361194:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838358 ES:SE:LP:AF:SS:ID   -0.000377844:0.000661968:0.245542:0.838358:361194:rs376645387