Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std 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-30140_irnt/ukb-d-30140_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-30140_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 15:35:37 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30140_irnt/ukb-d-30140_irnt.vcf.gz ...
Read summary statistics for 13586291 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: 0.148 (0.0111)
Lambda GC: 1.5996
Mean Chi^2: 2.2219
Intercept: 1.1555 (0.0173)
Ratio: 0.1272 (0.0142)
Analysis finished at Mon Nov 25 15:37:56 2019
Total time elapsed: 2.0m:19.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3765,
    "mean_EFFECT": 0.0001,
    "n": 349856,
    "n_snps": 13586291,
    "n_clumped_hits": 296,
    "n_p_sig": 70066,
    "n_mono": 0,
    "n_ns": 1251790,
    "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": 569188,
    "n_est": 351182.6665,
    "ratio_se_n": 1.0019,
    "mean_diff": 2.5554e-07,
    "ratio_diff": 1.4637,
    "sd_y_est1": 0.9973,
    "sd_y_est2": 0.9992,
    "r2_sum1": 0.0724,
    "r2_sum2": 0.0727,
    "r2_sum3": 0.0725,
    "r2_sum4": 0.0723,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.148,
    "ldsc_observed_scale_h2_se": 0.0111,
    "ldsc_intercept_beta": 1.1555,
    "ldsc_intercept_se": 0.0173,
    "ldsc_lambda_gc": 1.5996,
    "ldsc_mean_chisq": 2.2219,
    "ldsc_ratio": 0.1273
}

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 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 13574245 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 9.051330e+00 6.184986e+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 7.902511e+07 5.591484e+07 3.02000e+02 3.293100e+07 7.013867e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.023000e-04 1.493180e-02 -4.66746e-01 -4.478000e-03 5.020000e-05 4.636900e-03 3.406770e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.001900e-02 9.664700e-03 1.95970e-03 2.852400e-03 5.256400e-03 1.439810e-02 4.905640e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.465430e-01 3.040219e-01 0.00000e+00 1.694865e-01 4.287528e-01 7.092968e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.465425e-01 3.040221e-01 0.00000e+00 1.694855e-01 4.287522e-01 7.092963e-01 9.999999e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908058e-01 2.544033e-01 1.00000e-03 7.430400e-03 6.003380e-02 2.953175e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569188 0.9581057 NA NA NA NA NA 1.963354e-01 2.471013e-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 3.498560e+05 0.000000e+00 3.49856e+05 3.498560e+05 3.498560e+05 3.498560e+05 3.498560e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0044351 0.0041743 0.2880242 0.2880234 0.1106480 0.1894970 349856
1 693731 rs12238997 A G -0.0025180 0.0039445 0.5232365 0.5232368 0.1158220 0.1417730 349856
1 707522 rs371890604 G C -0.0027220 0.0044360 0.5394696 0.5394707 0.0972503 0.1293930 349856
1 717587 rs144155419 G A -0.0077816 0.0105700 0.4616140 0.4616121 0.0157180 0.0045926 349856
1 723329 rs189787166 A T 0.0186716 0.0313772 0.5517978 0.5517973 0.0017201 0.0003994 349856
1 730087 rs148120343 T C 0.0003879 0.0054930 0.9437079 0.9437084 0.0564790 0.0127796 349856
1 731718 rs142557973 T C -0.0024122 0.0037407 0.5190259 0.5190255 0.1217450 0.1543530 349856
1 732032 rs61770163 A C -0.0029380 0.0039908 0.4616193 0.4616195 0.1211440 0.1555510 349856
1 734349 rs141242758 T C -0.0026037 0.0037428 0.4866413 0.4866404 0.1209750 0.1525560 349856
1 740284 rs61770167 C T -0.0198569 0.0171224 0.2461699 0.2461697 0.0057856 0.0023962 349856
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0072266 0.0043200 0.0943604 0.0943604 0.0561631 0.0309934 349856
23 154923374 rs111332691 T A 0.0016014 0.0047491 0.7359732 0.7359730 0.0447941 0.0116556 349856
23 154925045 rs509981 C T -0.0040865 0.0022855 0.0737734 0.0737731 0.2454420 0.3634440 349856
23 154925895 rs538470 C T -0.0038295 0.0023378 0.1013960 0.1013953 0.2417880 0.3634440 349856
23 154927581 rs644138 G A -0.0017733 0.0021491 0.4092974 0.4092970 0.3020000 0.4635760 349856
23 154929412 rs557132 C T -0.0039805 0.0022862 0.0816582 0.0816586 0.2452960 0.3568210 349856
23 154929637 rs35185538 CT C -0.0017576 0.0023862 0.4613834 0.4613814 0.2295270 0.3011920 349856
23 154929952 rs4012982 CAA C -0.0036078 0.0024046 0.1335110 0.1335105 0.2392510 0.3165560 349856
23 154930230 rs781880 A G -0.0041009 0.0022858 0.0727947 0.0727940 0.2457070 0.3618540 349856
23 154930487 rs781879 T A -0.0070321 0.0078465 0.3701408 0.3701406 0.0195212 0.1263580 349856

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110648 ES:SE:LP:AF:SS:ID   -0.00443508:0.00417432:0.540571:0.110648:349856:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115822 ES:SE:LP:AF:SS:ID   -0.00251802:0.00394449:0.281302:0.115822:349856:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972503    ES:SE:LP:AF:SS:ID   -0.00272199:0.004436:0.268033:0.0972503:349856:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015718 ES:SE:LP:AF:SS:ID   -0.00778158:0.01057:0.335721:0.015718:349856:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00172006   ES:SE:LP:AF:SS:ID   0.0186716:0.0313772:0.25822:0.00172006:349856:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056479 ES:SE:LP:AF:SS:ID   0.000387857:0.00549297:0.0251624:0.056479:349856:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121745 ES:SE:LP:AF:SS:ID   -0.00241221:0.00374074:0.284811:0.121745:349856:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121144 ES:SE:LP:AF:SS:ID   -0.00293798:0.00399083:0.335716:0.121144:349856:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120975 ES:SE:LP:AF:SS:ID   -0.00260369:0.00374275:0.312791:0.120975:349856:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578559   ES:SE:LP:AF:SS:ID   -0.0198569:0.0171224:0.608765:0.00578559:349856:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188274   ES:SE:LP:AF:SS:ID   -0.0351515:0.0323364:0.5575:0.00188274:349856:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869759 ES:SE:LP:AF:SS:ID   0.00294266:0.00369015:0.371408:0.869759:349856:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153176   ES:SE:LP:AF:SS:ID   0.0286634:0.0333855:0.408284:0.00153176:349856:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122895 ES:SE:LP:AF:SS:ID   -0.0028005:0.00365434:0.353137:0.122895:349856:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142708 ES:SE:LP:AF:SS:ID   -0.0029119:0.00361219:0.376577:0.142708:349856:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123012 ES:SE:LP:AF:SS:ID   -0.00299085:0.00364922:0.384626:0.123012:349856:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870892 ES:SE:LP:AF:SS:ID   0.00214714:0.003556:0.26283:0.870892:349856:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875492 ES:SE:LP:AF:SS:ID   0.00351104:0.00361504:0.479604:0.875492:349856:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   -0.00180492:0.00356486:0.212795:0.128631:349856:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363478    ES:SE:LP:AF:SS:ID   -0.00358558:0.00647079:0.236947:0.0363478:349856:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870485 ES:SE:LP:AF:SS:ID   0.0020585:0.00355226:0.250064:0.870485:349856:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870587 ES:SE:LP:AF:SS:ID   0.00196491:0.00355383:0.236323:0.870587:349856:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870481 ES:SE:LP:AF:SS:ID   0.00206859:0.00355211:0.251558:0.870481:349856:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504553   ES:SE:LP:AF:SS:ID   0.0178745:0.018239:0.485347:0.00504553:349856:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501236   ES:SE:LP:AF:SS:ID   0.0177022:0.0182876:0.477488:0.00501236:349856:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558059   ES:SE:LP:AF:SS:ID   -0.00769245:0.0176719:0.178257:0.00558059:349856:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870565 ES:SE:LP:AF:SS:ID   0.00210211:0.00354589:0.257043:0.870565:349856:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125973 ES:SE:LP:AF:SS:ID   -0.00217869:0.00361839:0.261936:0.125973:349856:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870129 ES:SE:LP:AF:SS:ID   0.0023736:0.00353734:0.299112:0.870129:349856:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869408 ES:SE:LP:AF:SS:ID   0.00191933:0.00353399:0.23132:0.869408:349856:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870284 ES:SE:LP:AF:SS:ID   0.00229124:0.00354041:0.28607:0.870284:349856:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87029  ES:SE:LP:AF:SS:ID   0.00229972:0.00354066:0.287347:0.87029:349856:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870298 ES:SE:LP:AF:SS:ID   0.00229536:0.00354078:0.286666:0.870298:349856:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87074  ES:SE:LP:AF:SS:ID   0.00222076:0.00354978:0.274436:0.87074:349856:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0987996    ES:SE:LP:AF:SS:ID   -0.0034343:0.00412631:0.392283:0.0987996:349856:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647264   ES:SE:LP:AF:SS:ID   -0.0125853:0.015965:0.366008:0.00647264:349856:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874649 ES:SE:LP:AF:SS:ID   0.00300991:0.00360283:0.394182:0.874649:349856:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864035 ES:SE:LP:AF:SS:ID   0.00223685:0.00353299:0.27848:0.864035:349856:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   0.00253213:0.00356731:0.320736:0.869419:349856:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866376 ES:SE:LP:AF:SS:ID   0.00248084:0.00356812:0.312577:0.866376:349856:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987131    ES:SE:LP:AF:SS:ID   0.000254663:0.00427318:0.021145:0.0987131:349856:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.00312596:0.00360876:0.412993:0.87156:349856:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.00312611:0.00360876:0.413018:0.87156:349856:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.00312516:0.00360883:0.412845:0.87156:349856:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871932 ES:SE:LP:AF:SS:ID   0.00306164:0.00361088:0.401759:0.871932:349856:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125555 ES:SE:LP:AF:SS:ID   -0.00262211:0.0036137:0.329677:0.125555:349856:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105385 ES:SE:LP:AF:SS:ID   -0.00342698:0.00393485:0.415903:0.105385:349856:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855371 ES:SE:LP:AF:SS:ID   0.00142143:0.003532:0.162816:0.855371:349856:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164256   ES:SE:LP:AF:SS:ID   0.00644702:0.0314317:0.077023:0.00164256:349856:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838282 ES:SE:LP:AF:SS:ID   0.000135097:0.00347884:0.0136659:0.838282:349856:rs376645387