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-20426/ukb-d-20426.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-20426/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 17:13:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20426/ukb-d-20426.vcf.gz ...
Read summary statistics for 13540991 SNPs.
Dropped 12655 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, 1283495 SNPs remain.
After merging with regression SNP LD, 1283495 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0321 (0.0146)
Lambda GC: 1.0261
Mean Chi^2: 1.0238
Intercept: 1.0022 (0.0059)
Ratio: 0.093 (0.2492)
Analysis finished at Mon Nov 25 17:15:51 2019
Total time elapsed: 2.0m:18.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0236,
    "mean_EFFECT": 6.3155e-06,
    "n": 33864,
    "n_snps": 13540991,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250195,
    "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": 557347,
    "n_est": 33976.5171,
    "ratio_se_n": 1.0017,
    "mean_diff": 4.285e-06,
    "ratio_diff": 1.9108,
    "sd_y_est1": 0.4909,
    "sd_y_est2": 0.4917,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283495,
    "ldsc_nsnp_merge_regression_ld": 1283495,
    "ldsc_observed_scale_h2_beta": 0.0321,
    "ldsc_observed_scale_h2_se": 0.0146,
    "ldsc_intercept_beta": 1.0022,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0261,
    "ldsc_mean_chisq": 1.0238,
    "ldsc_ratio": 0.0924
}

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 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 1.00000 3 94 0 13529000 0 NA NA NA NA NA NA NA NA
character REF 0 1.00000 1 100 0 57004 0 NA NA NA NA NA NA NA NA
character ALT 0 1.00000 1 342 0 33313 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.00000 NA NA NA NA NA 9.051629e+00 6.185104e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 <U+2587><U+2585><U+2585><U+2582><U+2582>
numeric POS 0 1.00000 NA NA NA NA NA 7.902442e+07 5.591566e+07 3.02000e+02 3.292530e+07 7.014076e+07 1.148571e+08 2.492309e+08 <U+2587><U+2586><U+2585><U+2582><U+2581>
numeric EFFECT 0 1.00000 NA NA NA NA NA 6.300000e-06 2.185450e-02 -2.67087e-01 -5.809500e-03 1.260000e-05 5.881900e-03 2.561790e-01 <U+2581><U+2581><U+2587><U+2581><U+2581>
numeric SE 0 1.00000 NA NA NA NA NA 1.571500e-02 1.512610e-02 3.20030e-03 4.506600e-03 8.267600e-03 2.254220e-02 8.222410e-02 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric PVAL 0 1.00000 NA NA NA NA NA 4.965665e-01 2.891681e-01 2.00000e-07 2.459620e-01 4.949884e-01 7.468631e-01 1.000000e+00 <U+2587><U+2587><U+2587><U+2587><U+2587>
numeric PVAL_ztest 0 1.00000 NA NA NA NA NA 4.965617e-01 2.891709e-01 2.00000e-07 2.459536e-01 4.949827e-01 7.468613e-01 9.999998e-01 <U+2587><U+2587><U+2587><U+2587><U+2587>
numeric AF 0 1.00000 NA NA NA NA NA 1.914093e-01 2.545530e-01 1.00000e-03 7.589400e-03 6.074150e-02 2.965700e-01 9.990000e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric AF_reference 557347 0.95884 NA NA NA NA NA 1.967759e-01 2.471993e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric N 0 1.00000 NA NA NA NA NA 3.386400e+04 0.000000e+00 3.38640e+04 3.386400e+04 3.386400e+04 3.386400e+04 3.386400e+04 <U+2581><U+2581><U+2587><U+2581><U+2581>

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0046388 0.0065742 0.4804431 0.4804385 0.1122380 0.1894970 33864
1 693731 rs12238997 A G -0.0028362 0.0062037 0.6475406 0.6475379 0.1174480 0.1417730 33864
1 707522 rs371890604 G C -0.0022400 0.0069753 0.7481092 0.7481066 0.0992014 0.1293930 33864
1 717587 rs144155419 G A -0.0204557 0.0162793 0.2089258 0.2089178 0.0164911 0.0045926 33864
1 723329 rs189787166 A T -0.0333658 0.0486480 0.4928060 0.4928003 0.0017982 0.0003994 33864
1 730087 rs148120343 T C -0.0000492 0.0086383 0.9954580 0.9954575 0.0570180 0.0127796 33864
1 731718 rs142557973 T C -0.0025310 0.0058799 0.6668697 0.6668668 0.1241230 0.1543530 33864
1 732032 rs61770163 A C -0.0039447 0.0062689 0.5291941 0.5291896 0.1237280 0.1555510 33864
1 734349 rs141242758 T C -0.0023152 0.0058842 0.6939865 0.6939832 0.1233540 0.1525560 33864
1 740284 rs61770167 C T 0.0010455 0.0273372 0.9694919 0.9694924 0.0057063 0.0023962 33864
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0011662 0.0070484 0.8685919 0.8685903 0.0566626 0.0309934 33864
23 154923374 rs111332691 T A -0.0063843 0.0078340 0.4151089 0.4151033 0.0441915 0.0116556 33864
23 154925045 rs509981 C T -0.0061354 0.0037499 0.1018151 0.1018063 0.2430570 0.3634440 33864
23 154925895 rs538470 C T -0.0057426 0.0038350 0.1342910 0.1342817 0.2394440 0.3634440 33864
23 154927581 rs644138 G A -0.0058516 0.0035180 0.0962565 0.0962461 0.3001700 0.4635760 33864
23 154929412 rs557132 C T -0.0063658 0.0037511 0.0896954 0.0896873 0.2428840 0.3568210 33864
23 154929637 rs35185538 CT C -0.0053347 0.0039169 0.1732140 0.1732055 0.2274550 0.3011920 33864
23 154929952 rs4012982 CAA C -0.0070868 0.0039516 0.0729172 0.0729083 0.2373370 0.3165560 33864
23 154930230 rs781880 A G -0.0063487 0.0037505 0.0905107 0.0905012 0.2431990 0.3618540 33864
23 154930487 rs781879 T A -0.0145232 0.0124378 0.2429501 0.2429414 0.0203274 0.1263580 33864

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112238 ES:SE:LP:AF:SS:ID   -0.00463876:0.00657423:0.318358:0.112238:33864:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117448 ES:SE:LP:AF:SS:ID   -0.00283624:0.0062037:0.188733:0.117448:33864:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0992014    ES:SE:LP:AF:SS:ID   -0.00224003:0.00697531:0.126035:0.0992014:33864:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0164911    ES:SE:LP:AF:SS:ID   -0.0204557:0.0162793:0.680008:0.0164911:33864:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00179825   ES:SE:LP:AF:SS:ID   -0.0333658:0.048648:0.307324:0.00179825:33864:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.057018 ES:SE:LP:AF:SS:ID   -4.91794e-05:0.00863827:0.00197706:0.057018:33864:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124123 ES:SE:LP:AF:SS:ID   -0.00253102:0.00587991:0.175959:0.124123:33864:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123728 ES:SE:LP:AF:SS:ID   -0.00394469:0.00626894:0.276385:0.123728:33864:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123354 ES:SE:LP:AF:SS:ID   -0.00231517:0.0058842:0.158649:0.123354:33864:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00570633   ES:SE:LP:AF:SS:ID   0.00104551:0.0273372:0.0134558:0.00570633:33864:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00204023   ES:SE:LP:AF:SS:ID   0.0874375:0.0483726:1.1507:0.00204023:33864:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867135 ES:SE:LP:AF:SS:ID   0.00339293:0.00578255:0.253853:0.867135:33864:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0014337    ES:SE:LP:AF:SS:ID   -0.0158334:0.0548001:0.112025:0.0014337:33864:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12554  ES:SE:LP:AF:SS:ID   -0.00250226:0.00573242:0.178834:0.12554:33864:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145642 ES:SE:LP:AF:SS:ID   -0.0052878:0.00566771:0.454887:0.145642:33864:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125615 ES:SE:LP:AF:SS:ID   -0.00246761:0.00572498:0.17623:0.125615:33864:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867662 ES:SE:LP:AF:SS:ID   0.00221504:0.00558126:0.16023:0.867662:33864:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872737 ES:SE:LP:AF:SS:ID   0.00257794:0.00567076:0.187488:0.872737:33864:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131769 ES:SE:LP:AF:SS:ID   -0.00220535:0.00559487:0.158982:0.131769:33864:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363513    ES:SE:LP:AF:SS:ID   0.0143664:0.0102312:0.795137:0.0363513:33864:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867205 ES:SE:LP:AF:SS:ID   0.00193366:0.00557334:0.137491:0.867205:33864:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867281 ES:SE:LP:AF:SS:ID   0.0020625:0.00557455:0.147889:0.867281:33864:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867199 ES:SE:LP:AF:SS:ID   0.00195371:0.00557306:0.139112:0.867199:33864:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00558758   ES:SE:LP:AF:SS:ID   -0.00148689:0.0272907:0.0192923:0.00558758:33864:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00556129   ES:SE:LP:AF:SS:ID   -0.00126603:0.0273458:0.0163403:0.00556129:33864:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00591877   ES:SE:LP:AF:SS:ID   0.0244765:0.0269637:0.438883:0.00591877:33864:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.867319 ES:SE:LP:AF:SS:ID   0.00216429:0.00556558:0.156534:0.867319:33864:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129019 ES:SE:LP:AF:SS:ID   -0.00283351:0.00567584:0.209274:0.129019:33864:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866805 ES:SE:LP:AF:SS:ID   0.00225631:0.00555053:0.164706:0.866805:33864:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866247 ES:SE:LP:AF:SS:ID   0.00252033:0.00554588:0.187416:0.866247:33864:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866996 ES:SE:LP:AF:SS:ID   0.00254263:0.00555591:0.188954:0.866996:33864:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867003 ES:SE:LP:AF:SS:ID   0.00254316:0.00555628:0.188986:0.867003:33864:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867006 ES:SE:LP:AF:SS:ID   0.0025476:0.0055563:0.18937:0.867006:33864:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867458 ES:SE:LP:AF:SS:ID   0.00227027:0.00557069:0.165188:0.867458:33864:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100652 ES:SE:LP:AF:SS:ID   -0.000827395:0.00647703:0.046553:0.100652:33864:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00681463   ES:SE:LP:AF:SS:ID   0.0298093:0.0244972:0.65039:0.00681463:33864:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.871829 ES:SE:LP:AF:SS:ID   0.00296202:0.00565605:0.221488:0.871829:33864:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860683 ES:SE:LP:AF:SS:ID   0.00119126:0.00553879:0.0810742:0.860683:33864:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866425 ES:SE:LP:AF:SS:ID   0.00284944:0.00560577:0.213787:0.866425:33864:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.863483 ES:SE:LP:AF:SS:ID   0.00490056:0.0056024:0.418244:0.863483:33864:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.10133  ES:SE:LP:AF:SS:ID   -0.00574414:0.00667919:0.409167:0.10133:33864:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.868702 ES:SE:LP:AF:SS:ID   0.00529612:0.00566299:0.456325:0.868702:33864:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.868702 ES:SE:LP:AF:SS:ID   0.00529593:0.00566299:0.456304:0.868702:33864:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.868699 ES:SE:LP:AF:SS:ID   0.00529555:0.005663:0.45626:0.868699:33864:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869099 ES:SE:LP:AF:SS:ID   0.0049569:0.00566685:0.41824:0.869099:33864:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128398 ES:SE:LP:AF:SS:ID   -0.00333019:0.00567513:0.253881:0.128398:33864:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107115 ES:SE:LP:AF:SS:ID   -0.000226776:0.00618837:0.0128845:0.107115:33864:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852347 ES:SE:LP:AF:SS:ID   0.00289669:0.00553744:0.221197:0.852347:33864:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00173178   ES:SE:LP:AF:SS:ID   -0.0298455:0.0486406:0.268017:0.00173178:33864:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837162 ES:SE:LP:AF:SS:ID   0.0045462:0.00550087:0.388751:0.837162:33864:rs376645387