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IEU GWAS information

Trait: Number of night shifts worked monthly during mixed shift periods.

name	value
id	ukb-d-22643_irnt
trait	Number of night shifts worked monthly during mixed shift periods
category	Continuous
sample_size	19998
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
mr	1
nsnp	13520087

Report information

name	value
gwas_id	ukb-d-22643_irnt
bcf_file	ukb-d-22643_irnt.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 23:23 BST
build_version	run_igd-8f4f4c9-2020-05-09

Summary

Summary {data-width=650}

Manhattan plot

$manhattan_plot$

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-22643_irnt/ukb-d-22643_irnt.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-22643_irnt/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 15:36:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22643_irnt/ukb-d-22643_irnt.vcf.gz ...
Read summary statistics for 13520086 SNPs.
Dropped 12637 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, 1283494 SNPs remain.
After merging with regression SNP LD, 1283494 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0086 (0.0234)
Lambda GC: 1.0058
Mean Chi^2: 1.0055
Intercept: 1.0089 (0.0063)
Ratio: 1.6109 (1.1449)
Analysis finished at Mon Nov 25 15:38:29 2019
Total time elapsed: 2.0m:24.43s

QC metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 0.9972,
    "mean_EFFECT": -0.0001,
    "n": 19998,
    "n_snps": 13520086,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1249369,
    "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": 552571,
    "n_est": 20156.5758,
    "ratio_se_n": 1.004,
    "mean_diff": 3.4526e-06,
    "ratio_diff": 1.1172,
    "sd_y_est1": 0.9994,
    "sd_y_est2": 1.0033,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283494,
    "ldsc_nsnp_merge_regression_ld": 1283494,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0089,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0058,
    "ldsc_mean_chisq": 1.0055,
    "ldsc_ratio": 1.6182
}

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	FALSE
miss_EFFECT	FALSE
miss_SE	FALSE
miss_PVAL	FALSE
ldsc_ratio	TRUE
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	13508112	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	56940	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	342	0	33307	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	9.051576e+00	6.184357e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.300000e+01	2.300000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.901714e+07	5.591780e+07	3.0200e+02	3.291809e+07	7.012251e+07	1.148512e+08	2.492309e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-1.099000e-04	5.746630e-02	-6.8789e-01	-1.534930e-02	-5.570000e-05	1.522400e-02	7.269770e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	4.145980e-02	3.990820e-02	7.8838e-03	1.193870e-02	2.185690e-02	5.936380e-02	2.090640e-01	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	5.003227e-01	2.889034e-01	1.0000e-07	2.499200e-01	5.005990e-01	7.503882e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	5.003147e-01	2.889081e-01	1.0000e-07	2.499057e-01	5.005911e-01	7.503857e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.916929e-01	2.546323e-01	1.0000e-03	7.658600e-03	6.103120e-02	2.970840e-01	9.990000e-01	▇▂▁▁▁
numeric	AF_reference	552571	0.9591296	NA	NA	NA	NA	NA	1.970011e-01	2.472534e-01	0.0000e+00	5.790700e-03	8.526360e-02	3.095050e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	1.999800e+04	0.000000e+00	1.9998e+04	1.999800e+04	1.999800e+04	1.999800e+04	1.999800e+04	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	0.0046149	0.0175058	0.7920726	0.7920705	0.1114010	0.1894970	19998
1	693731	rs12238997	A	G	-0.0035630	0.0166654	0.8307099	0.8307074	0.1160070	0.1417730	19998
1	707522	rs371890604	G	C	-0.0004205	0.0187515	0.9821090	0.9821093	0.0969876	0.1293930	19998
1	717587	rs144155419	G	A	-0.0071940	0.0444013	0.8712889	0.8712878	0.0158942	0.0045926	19998
1	723329	rs189787166	A	T	0.0219966	0.1223390	0.8573110	0.8573093	0.0019662	0.0003994	19998
1	730087	rs148120343	T	C	0.0248927	0.0228389	0.2757592	0.2757460	0.0576697	0.0127796	19998
1	731718	rs142557973	T	C	-0.0016752	0.0157948	0.9155359	0.9155351	0.1223110	0.1543530	19998
1	732032	rs61770163	A	C	0.0066940	0.0168056	0.6903972	0.6903924	0.1225520	0.1555510	19998
1	734349	rs141242758	T	C	-0.0013508	0.0158061	0.9318970	0.9318967	0.1215720	0.1525560	19998
1	740284	rs61770167	C	T	0.0526559	0.0743845	0.4790226	0.4790148	0.0054148	0.0023962	19998

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	-0.0001064	0.0174156	0.9951260	0.9951259	0.0566091	0.0309934	19998
23	154923374	rs111332691	T	A	0.0167708	0.0191922	0.3822179	0.3822086	0.0447045	0.0116556	19998
23	154925045	rs509981	C	T	0.0050120	0.0093161	0.5905885	0.5905828	0.2399560	0.3634440	19998
23	154925895	rs538470	C	T	0.0034309	0.0095242	0.7186774	0.7186735	0.2364890	0.3634440	19998
23	154927581	rs644138	G	A	0.0038565	0.0087249	0.6584852	0.6584797	0.2971690	0.4635760	19998
23	154929412	rs557132	C	T	0.0048668	0.0093211	0.6015905	0.6015843	0.2397400	0.3568210	19998
23	154929637	rs35185538	CT	C	0.0089772	0.0097062	0.3550316	0.3550203	0.2257860	0.3011920	19998
23	154929952	rs4012982	CAA	C	0.0064483	0.0098150	0.5112025	0.5111943	0.2337120	0.3165560	19998
23	154930230	rs781880	A	G	0.0045994	0.0093130	0.6213996	0.6213947	0.2402730	0.3618540	19998
23	154930487	rs781879	T	A	-0.0029602	0.0319503	0.9261819	0.9261805	0.0190903	0.1263580	19998

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111401 ES:SE:LP:AF:SS:ID   0.00461493:0.0175058:0.101235:0.111401:19998:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116007 ES:SE:LP:AF:SS:ID   -0.00356297:0.0166654:0.0805506:0.116007:19998:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0969876    ES:SE:LP:AF:SS:ID   -0.000420494:0.0187515:0.00784031:0.0969876:19998:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158942    ES:SE:LP:AF:SS:ID   -0.00719403:0.0444013:0.0598378:0.0158942:19998:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00196618   ES:SE:LP:AF:SS:ID   0.0219966:0.122339:0.0668616:0.00196618:19998:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0576697    ES:SE:LP:AF:SS:ID   0.0248927:0.0228389:0.55947:0.0576697:19998:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:SS:ID   -0.00167519:0.0157948:0.0383246:0.122311:19998:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122552 ES:SE:LP:AF:SS:ID   0.00669405:0.0168056:0.160901:0.122552:19998:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121572 ES:SE:LP:AF:SS:ID   -0.00135077:0.0158061:0.0306321:0.121572:19998:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00541476   ES:SE:LP:AF:SS:ID   0.0526559:0.0743845:0.319644:0.00541476:19998:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00171988   ES:SE:LP:AF:SS:ID   -0.134617:0.142996:0.460284:0.00171988:19998:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868647 ES:SE:LP:AF:SS:ID   0.00583961:0.0155232:0.150713:0.868647:19998:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00175302   ES:SE:LP:AF:SS:ID   -0.143787:0.129946:0.57103:0.00175302:19998:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123953 ES:SE:LP:AF:SS:ID   -0.000633568:0.01538:0.0145102:0.123953:19998:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143364 ES:SE:LP:AF:SS:ID   0.00239646:0.0152619:0.0578783:0.143364:19998:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124106 ES:SE:LP:AF:SS:ID   -0.000874534:0.0153587:0.0201818:0.124106:19998:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869714 ES:SE:LP:AF:SS:ID   0.00318384:0.0149759:0.0800631:0.869714:19998:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874426 ES:SE:LP:AF:SS:ID   0.00265134:0.0152242:0.0646202:0.874426:19998:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129736 ES:SE:LP:AF:SS:ID   -0.00213794:0.0150283:0.0521371:0.129736:19998:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0360536    ES:SE:LP:AF:SS:ID   -0.0110496:0.027246:0.164259:0.0360536:19998:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869406 ES:SE:LP:AF:SS:ID   0.0030279:0.0149704:0.0758676:0.869406:19998:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869511 ES:SE:LP:AF:SS:ID   0.00282368:0.0149752:0.0703553:0.869511:19998:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869405 ES:SE:LP:AF:SS:ID   0.0030259:0.0149698:0.0758169:0.869405:19998:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00498266   ES:SE:LP:AF:SS:ID   0.000339662:0.0776267:0.00151877:0.00498266:19998:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00495412   ES:SE:LP:AF:SS:ID   0.000213629:0.0778255:0.000952148:0.00495412:19998:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0056992    ES:SE:LP:AF:SS:ID   -0.00167968:0.0725507:0.00809686:0.0056992:19998:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869394 ES:SE:LP:AF:SS:ID   0.00253949:0.0149336:0.0629985:0.869394:19998:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127042 ES:SE:LP:AF:SS:ID   -0.00314675:0.0152378:0.0775886:0.127042:19998:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868862 ES:SE:LP:AF:SS:ID   0.00259741:0.014893:0.06472:0.868862:19998:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868446 ES:SE:LP:AF:SS:ID   0.00209309:0.0148962:0.0514614:0.868446:19998:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869066 ES:SE:LP:AF:SS:ID   0.00294541:0.0149044:0.0739952:0.869066:19998:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869071 ES:SE:LP:AF:SS:ID   0.00293581:0.0149052:0.0737311:0.869071:19998:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869071 ES:SE:LP:AF:SS:ID   0.00294537:0.0149053:0.0739896:0.869071:19998:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869555 ES:SE:LP:AF:SS:ID   0.0030028:0.0149491:0.0753052:0.869555:19998:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0989074    ES:SE:LP:AF:SS:ID   -0.00675951:0.0174355:0.155987:0.0989074:19998:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0066389    ES:SE:LP:AF:SS:ID   0.0343215:0.0655108:0.221595:0.0066389:19998:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873563 ES:SE:LP:AF:SS:ID   0.00420984:0.0151717:0.107118:0.873563:19998:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862991 ES:SE:LP:AF:SS:ID   0.00228707:0.0148808:0.0565777:0.862991:19998:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868344 ES:SE:LP:AF:SS:ID   0.000977618:0.0150229:0.023139:0.868344:19998:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865172 ES:SE:LP:AF:SS:ID   0.00164412:0.0150273:0.0395868:0.865172:19998:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0988167    ES:SE:LP:AF:SS:ID   -0.00503959:0.0180559:0.107815:0.0988167:19998:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870587 ES:SE:LP:AF:SS:ID   0.0052782:0.0152083:0.137541:0.870587:19998:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870587 ES:SE:LP:AF:SS:ID   0.00527854:0.0152083:0.137551:0.870587:19998:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870584 ES:SE:LP:AF:SS:ID   0.00528162:0.0152083:0.137642:0.870584:19998:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870877 ES:SE:LP:AF:SS:ID   0.0047085:0.0152104:0.120961:0.870877:19998:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126652 ES:SE:LP:AF:SS:ID   -0.00189647:0.0152288:0.0453253:0.126652:19998:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106116 ES:SE:LP:AF:SS:ID   -0.00242601:0.0165246:0.0539006:0.106116:19998:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854258 ES:SE:LP:AF:SS:ID   -0.00161076:0.0148238:0.0393043:0.854258:19998:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00184224   ES:SE:LP:AF:SS:ID   0.0199646:0.123267:0.0598138:0.00184224:19998:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838312 ES:SE:LP:AF:SS:ID   0.0145917:0.0146591:0.495457:0.838312:19998:rs376645387