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IEU GWAS information

Trait: Urate.

name	value
id	ukb-d-30880_raw
trait	Urate
category	Metabolites
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
unit	umol/L
mr	1
nsnp	13585994

Report information

name	value
gwas_id	ukb-d-30880_raw
bcf_file	ukb-d-30880_raw.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 12:00 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

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-30880_raw/ukb-d-30880_raw.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-30880_raw/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 16:43:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30880_raw/ukb-d-30880_raw.vcf.gz ...
Read summary statistics for 13585993 SNPs.
Dropped 12709 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: 0.1955 (0.0362)
Lambda GC: 1.6242
Mean Chi^2: 3.48
Intercept: 1.1166 (0.0155)
Ratio: 0.047 (0.0063)
Analysis finished at Mon Nov 25 16:45:46 2019
Total time elapsed: 2.0m:17.07s

QC metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.379,
    "mean_EFFECT": 0,
    "n": 343836,
    "n_snps": 13585993,
    "n_clumped_hits": 250,
    "n_p_sig": 49506,
    "n_mono": 0,
    "n_ns": 1251781,
    "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": 569154,
    "n_est": 345174.1737,
    "ratio_se_n": 1.0019,
    "mean_diff": -0,
    "ratio_diff": 60.353,
    "sd_y_est1": 68.2385,
    "sd_y_est2": 68.3711,
    "r2_sum1": 365.9362,
    "r2_sum2": 0.0786,
    "r2_sum3": 0.0783,
    "r2_sum4": 0.0776,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1955,
    "ldsc_observed_scale_h2_se": 0.0362,
    "ldsc_intercept_beta": 1.1166,
    "ldsc_intercept_se": 0.0155,
    "ldsc_lambda_gc": 1.6242,
    "ldsc_mean_chisq": 3.48,
    "ldsc_ratio": 0.047
}

Flags

name	value
af_correlation	FALSE
inflation_factor	TRUE
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	TRUE
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	13573948	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	57080	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	9.051238e+00	6.184962e+00	1.00000	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.902571e+07	5.591523e+07	302.00000	3.293111e+07	7.013925e+07	1.148602e+08	2.492309e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	4.610000e-05	1.043076e+00	-34.45700	-3.134100e-01	-5.281000e-04	3.127300e-01	2.497400e+01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	6.914850e-01	6.670169e-01	0.13529	1.968800e-01	3.627900e-01	9.937200e-01	3.371400e+00	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.470768e-01	3.036697e-01	0.00000	1.706499e-01	4.283295e-01	7.103199e-01	1.000000e+00	▇▆▅▅▅
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.470764e-01	3.036699e-01	0.00000	1.706467e-01	4.283255e-01	7.103160e-01	9.999999e-01	▇▆▅▅▅
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.908099e-01	2.544045e-01	0.00100	7.431500e-03	6.004100e-02	2.953200e-01	9.989990e-01	▇▂▁▁▁
numeric	AF_reference	569154	0.9581073	NA	NA	NA	NA	NA	1.963392e-01	2.471027e-01	0.00000	5.591000e-03	8.426520e-02	3.081070e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.438360e+05	0.000000e+00	343836.00000	3.438360e+05	3.438360e+05	3.438360e+05	3.438360e+05	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	-0.213680	0.28823	0.4584901	0.4584798	0.1105200	0.1894970	343836
1	693731	rs12238997	A	G	-0.067409	0.27223	0.8044301	0.8044301	0.1158100	0.1417730	343836
1	707522	rs371890604	G	C	0.144820	0.30619	0.6362400	0.6362315	0.0972540	0.1293930	343836
1	717587	rs144155419	G	A	-1.017400	0.73096	0.1639699	0.1639623	0.0156620	0.0045926	343836
1	723329	rs189787166	A	T	-1.051100	2.15410	0.6255903	0.6255830	0.0017349	0.0003994	343836
1	730087	rs148120343	T	C	-0.323370	0.37939	0.3940297	0.3940243	0.0564260	0.0127796	343836
1	731718	rs142557973	T	C	-0.058916	0.25819	0.8195001	0.8194997	0.1217000	0.1543530	343836
1	732032	rs61770163	A	C	0.019684	0.27551	0.9430400	0.9430431	0.1211000	0.1555510	343836
1	734349	rs141242758	T	C	-0.048870	0.25833	0.8499600	0.8499544	0.1209200	0.1525560	343836
1	740284	rs61770167	C	T	1.839100	1.18490	0.1206499	0.1206349	0.0057564	0.0023962	343836

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	0.181200	0.29831	0.5435594	0.5435710	0.056204	0.0309934	343836
23	154923374	rs111332691	T	A	0.701090	0.32747	0.0322783	0.0322798	0.044880	0.0116556	343836
23	154925045	rs509981	C	T	0.142600	0.15775	0.3660100	0.3660156	0.245700	0.3634440	343836
23	154925895	rs538470	C	T	0.129360	0.16136	0.4227397	0.4227348	0.242030	0.3634440	343836
23	154927581	rs644138	G	A	0.172150	0.14836	0.2459003	0.2459050	0.302290	0.4635760	343836
23	154929412	rs557132	C	T	0.141410	0.15779	0.3701596	0.3701507	0.245560	0.3568210	343836
23	154929637	rs35185538	CT	C	0.096247	0.16468	0.5589295	0.5589185	0.229820	0.3011920	343836
23	154929952	rs4012982	CAA	C	0.110690	0.16595	0.5047705	0.5047669	0.239530	0.3165560	343836
23	154930230	rs781880	A	G	0.149690	0.15777	0.3427102	0.3427294	0.245960	0.3618540	343836
23	154930487	rs781879	T	A	0.511320	0.54079	0.3443999	0.3444008	0.019564	0.1263580	343836

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11052  ES:SE:LP:AF:SS:ID   -0.21368:0.28823:0.33867:0.11052:343836:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   -0.067409:0.27223:0.0945117:0.11581:343836:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097254 ES:SE:LP:AF:SS:ID   0.14482:0.30619:0.196379:0.097254:343836:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015662 ES:SE:LP:AF:SS:ID   -1.0174:0.73096:0.785236:0.015662:343836:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017349    ES:SE:LP:AF:SS:ID   -1.0511:2.1541:0.20371:0.0017349:343836:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056426 ES:SE:LP:AF:SS:ID   -0.32337:0.37939:0.404471:0.056426:343836:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1217   ES:SE:LP:AF:SS:ID   -0.058916:0.25819:0.086451:0.1217:343836:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.1211   ES:SE:LP:AF:SS:ID   0.019684:0.27551:0.0254699:0.1211:343836:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12092  ES:SE:LP:AF:SS:ID   -0.04887:0.25833:0.0706015:0.12092:343836:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057564    ES:SE:LP:AF:SS:ID   1.8391:1.1849:0.918473:0.0057564:343836:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018612    ES:SE:LP:AF:SS:ID   2.1467:2.2465:0.469429:0.0018612:343836:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   -0.024775:0.25469:0.0350289:0.8698:343836:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015221    ES:SE:LP:AF:SS:ID   0.99425:2.313:0.175679:0.0015221:343836:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12288  ES:SE:LP:AF:SS:ID   -0.0091389:0.25222:0.012736:0.12288:343836:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14268  ES:SE:LP:AF:SS:ID   -0.051019:0.24927:0.0768441:0.14268:343836:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   -0.0016497:0.25186:0.00227732:0.12299:343836:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87096  ES:SE:LP:AF:SS:ID   -0.018333:0.24547:0.0266551:0.87096:343836:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87552  ES:SE:LP:AF:SS:ID   -0.044651:0.24951:0.0665279:0.87552:343836:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12857  ES:SE:LP:AF:SS:ID   -0.012146:0.24607:0.0174439:0.12857:343836:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036315 ES:SE:LP:AF:SS:ID   0.10483:0.44678:0.0891142:0.036315:343836:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   -0.0059204:0.24521:0.00844611:0.87056:343836:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   -0.011115:0.24533:0.015986:0.87066:343836:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87055  ES:SE:LP:AF:SS:ID   -0.0045489:0.24521:0.0064756:0.87055:343836:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050494    ES:SE:LP:AF:SS:ID   0.61706:1.2577:0.205031:0.0050494:343836:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050163    ES:SE:LP:AF:SS:ID   0.61625:1.261:0.204078:0.0050163:343836:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055482    ES:SE:LP:AF:SS:ID   0.87923:1.2237:0.325653:0.0055482:343836:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   -0.028976:0.24478:0.0429821:0.87064:343836:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   0.054879:0.24975:0.0829779:0.12592:343836:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   -0.052235:0.2442:0.0805976:0.87021:343836:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   -0.033358:0.24398:0.0500005:0.86949:343836:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   -0.034121:0.2444:0.0511129:0.87036:343836:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   -0.03454:0.24442:0.0517729:0.87036:343836:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   -0.030876:0.24443:0.0460085:0.87037:343836:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87081  ES:SE:LP:AF:SS:ID   -0.027344:0.24505:0.0404101:0.87081:343836:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098797 ES:SE:LP:AF:SS:ID   -0.0065904:0.28479:0.008092:0.098797:343836:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.006435 ES:SE:LP:AF:SS:ID   1.0996:1.1055:0.494986:0.006435:343836:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.8747   ES:SE:LP:AF:SS:ID   0.0030676:0.24868:0.00429462:0.8747:343836:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86411  ES:SE:LP:AF:SS:ID   0.028709:0.24392:0.0427232:0.86411:343836:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   -0.0075467:0.24624:0.0107505:0.8695:343836:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.030222:0.2463:0.0446298:0.86644:343836:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098742 ES:SE:LP:AF:SS:ID   -0.011915:0.29484:0.0142323:0.098742:343836:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.015109:0.24911:0.0215273:0.87161:343836:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.015118:0.24911:0.021541:0.87161:343836:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.014709:0.24911:0.0209436:0.87161:343836:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87199  ES:SE:LP:AF:SS:ID   -0.0048345:0.24925:0.00677105:0.87199:343836:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12551  ES:SE:LP:AF:SS:ID   -0.0089463:0.24942:0.0126064:0.12551:343836:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   0.095007:0.2716:0.13877:0.10539:343836:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85547  ES:SE:LP:AF:SS:ID   -0.042346:0.24382:0.0644323:0.85547:343836:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016536    ES:SE:LP:AF:SS:ID   -1.889:2.1596:0.418255:0.0016536:343836:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83828  ES:SE:LP:AF:SS:ID   -0.33633:0.24008:0.792554:0.83828:343836:rs376645387