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-30110_irnt/ukb-d-30110_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-30110_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 15:03:44 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30110_irnt/ukb-d-30110_irnt.vcf.gz ...
Read summary statistics for 13586284 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: 0.2066 (0.0204)
Lambda GC: 1.4533
Mean Chi^2: 2.7196
Intercept: 1.1874 (0.0207)
Ratio: 0.109 (0.012)
Analysis finished at Mon Nov 25 15:06:27 2019
Total time elapsed: 2.0m:43.66s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3002,
    "mean_EFFECT": -0,
    "n": 350470,
    "n_snps": 13586284,
    "n_clumped_hits": 354,
    "n_p_sig": 86337,
    "n_mono": 0,
    "n_ns": 1251793,
    "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": 569192,
    "n_est": 351803.918,
    "ratio_se_n": 1.0019,
    "mean_diff": 6.9536e-07,
    "ratio_diff": 0.7858,
    "sd_y_est1": 0.9924,
    "sd_y_est2": 0.9942,
    "r2_sum1": 0.1502,
    "r2_sum2": 0.1526,
    "r2_sum3": 0.152,
    "r2_sum4": 0.1509,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.2066,
    "ldsc_observed_scale_h2_se": 0.0204,
    "ldsc_intercept_beta": 1.1874,
    "ldsc_intercept_se": 0.0207,
    "ldsc_lambda_gc": 1.4533,
    "ldsc_mean_chisq": 2.7196,
    "ldsc_ratio": 0.109
}

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 13574238 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 9.051337e+00 6.184983e+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 7.902520e+07 5.591482e+07 3.02000e+02 3.293108e+07 7.013883e+07 1.148590e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.270000e-05 1.494850e-02 -2.85129e-01 -4.409900e-03 -1.580000e-05 4.336500e-03 1.458480e+00 ▇▁▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.960400e-03 9.608100e-03 1.94820e-03 2.835700e-03 5.225600e-03 1.431420e-02 4.871050e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.554739e-01 3.029984e-01 0.00000e+00 1.821728e-01 4.418298e-01 7.184292e-01 1.000000e+00 ▇▆▆▆▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.554735e-01 3.029986e-01 0.00000e+00 1.821716e-01 4.418293e-01 7.184302e-01 9.999999e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908060e-01 2.544034e-01 1.00000e-03 7.430500e-03 6.003400e-02 2.953170e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569192 0.9581054 NA NA NA NA NA 1.963357e-01 2.471015e-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 3.504700e+05 0.000000e+00 3.50470e+05 3.504700e+05 3.504700e+05 3.504700e+05 3.504700e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0062568 0.0041495 0.1315970 0.1315959 0.1106750 0.1894970 350470
1 693731 rs12238997 A G -0.0071136 0.0039208 0.0696306 0.0696299 0.1158560 0.1417730 350470
1 707522 rs371890604 G C -0.0031320 0.0044092 0.4775095 0.4775097 0.0972819 0.1293930 350470
1 717587 rs144155419 G A -0.0096254 0.0105091 0.3597137 0.3597121 0.0157163 0.0045926 350470
1 723329 rs189787166 A T -0.0432211 0.0311431 0.1651931 0.1651911 0.0017252 0.0003994 350470
1 730087 rs148120343 T C 0.0019354 0.0054606 0.7230211 0.7230199 0.0564930 0.0127796 350470
1 731718 rs142557973 T C -0.0044204 0.0037184 0.2345238 0.2345226 0.1217780 0.1543530 350470
1 732032 rs61770163 A C -0.0042632 0.0039670 0.2825160 0.2825149 0.1211730 0.1555510 350470
1 734349 rs141242758 T C -0.0042647 0.0037204 0.2516668 0.2516655 0.1210080 0.1525560 350470
1 740284 rs61770167 C T -0.0022606 0.0170229 0.8943549 0.8943544 0.0057859 0.0023962 350470
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0027253 0.0042950 0.5257291 0.5257291 0.0561538 0.0309934 350470
23 154923374 rs111332691 T A -0.0019307 0.0047214 0.6825886 0.6825870 0.0447913 0.0116556 350470
23 154925045 rs509981 C T -0.0071814 0.0022720 0.0015737 0.0015735 0.2454620 0.3634440 350470
23 154925895 rs538470 C T -0.0074578 0.0023240 0.0013319 0.0013318 0.2418090 0.3634440 350470
23 154927581 rs644138 G A -0.0057305 0.0021365 0.0073143 0.0073138 0.3020110 0.4635760 350470
23 154929412 rs557132 C T -0.0072690 0.0022727 0.0013821 0.0013820 0.2453170 0.3568210 350470
23 154929637 rs35185538 CT C -0.0075399 0.0023722 0.0014808 0.0014807 0.2295390 0.3011920 350470
23 154929952 rs4012982 CAA C -0.0068986 0.0023904 0.0039022 0.0039020 0.2392720 0.3165560 350470
23 154930230 rs781880 A G -0.0072645 0.0022723 0.0013889 0.0013887 0.2457280 0.3618540 350470
23 154930487 rs781879 T A 0.0073364 0.0077980 0.3468063 0.3468054 0.0195298 0.1263580 350470

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110675 ES:SE:LP:AF:SS:ID   -0.00625682:0.00414953:0.880754:0.110675:350470:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115856 ES:SE:LP:AF:SS:ID   -0.00711355:0.0039208:1.1572:0.115856:350470:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972819    ES:SE:LP:AF:SS:ID   -0.00313195:0.00440925:0.321018:0.0972819:350470:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157163    ES:SE:LP:AF:SS:ID   -0.00962543:0.0105091:0.444043:0.0157163:350470:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017252    ES:SE:LP:AF:SS:ID   -0.0432211:0.0311431:0.782008:0.0017252:350470:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056493 ES:SE:LP:AF:SS:ID   0.00193537:0.00546058:0.140849:0.056493:350470:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121778 ES:SE:LP:AF:SS:ID   -0.00442037:0.00371838:0.629813:0.121778:350470:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121173 ES:SE:LP:AF:SS:ID   -0.00426324:0.00396696:0.548957:0.121173:350470:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121008 ES:SE:LP:AF:SS:ID   -0.00426471:0.00372037:0.599174:0.121008:350470:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578594   ES:SE:LP:AF:SS:ID   -0.00226058:0.0170229:0.0484901:0.00578594:350470:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188268   ES:SE:LP:AF:SS:ID   0.0408352:0.0321415:0.690553:0.00188268:350470:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869716 ES:SE:LP:AF:SS:ID   0.0074293:0.00366801:1.36831:0.869716:350470:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153087   ES:SE:LP:AF:SS:ID   -0.0405277:0.0332004:0.653254:0.00153087:350470:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122935 ES:SE:LP:AF:SS:ID   -0.00537207:0.00363248:0.856461:0.122935:350470:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142736 ES:SE:LP:AF:SS:ID   -0.00516626:0.00359074:0.823284:0.142736:350470:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123052 ES:SE:LP:AF:SS:ID   -0.00532413:0.0036274:0.847186:0.123052:350470:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870853 ES:SE:LP:AF:SS:ID   0.00462297:0.00353478:0.719139:0.870853:350470:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875452 ES:SE:LP:AF:SS:ID   0.00443535:0.0035934:0.66336:0.875452:350470:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128669 ES:SE:LP:AF:SS:ID   -0.00523083:0.00354362:0.854148:0.128669:350470:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363383    ES:SE:LP:AF:SS:ID   0.0130461:0.00643365:1.37077:0.0363383:350470:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870447 ES:SE:LP:AF:SS:ID   0.00473974:0.00353106:0.745936:0.870447:350470:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870548 ES:SE:LP:AF:SS:ID   0.00468673:0.00353261:0.73375:0.870548:350470:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870442 ES:SE:LP:AF:SS:ID   0.00472023:0.00353092:0.741652:0.870442:350470:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504302   ES:SE:LP:AF:SS:ID   -0.00923049:0.0181387:0.214076:0.00504302:350470:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500989   ES:SE:LP:AF:SS:ID   -0.00977347:0.0181871:0.228411:0.00500989:350470:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558062   ES:SE:LP:AF:SS:ID   -0.00129267:0.0175686:0.0262507:0.00558062:350470:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870526 ES:SE:LP:AF:SS:ID   0.00498214:0.00352473:0.802678:0.870526:350470:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126012 ES:SE:LP:AF:SS:ID   -0.00601534:0.00359679:1.02483:0.126012:350470:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870089 ES:SE:LP:AF:SS:ID   0.00508848:0.00351623:0.830155:0.870089:350470:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869367 ES:SE:LP:AF:SS:ID   0.00504015:0.00351289:0.819997:0.869367:350470:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870243 ES:SE:LP:AF:SS:ID   0.0052068:0.00351927:0.85697:0.870243:350470:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870249 ES:SE:LP:AF:SS:ID   0.00520668:0.00351952:0.856854:0.870249:350470:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870258 ES:SE:LP:AF:SS:ID   0.00522263:0.00351963:0.8606:0.870258:350470:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8707   ES:SE:LP:AF:SS:ID   0.00490248:0.00352859:0.783243:0.8707:350470:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098836 ES:SE:LP:AF:SS:ID   -0.00631193:0.00410146:0.907216:0.098836:350470:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647163   ES:SE:LP:AF:SS:ID   0.00418424:0.0158722:0.101235:0.00647163:350470:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874608 ES:SE:LP:AF:SS:ID   0.0053153:0.00358126:0.860883:0.874608:350470:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863997 ES:SE:LP:AF:SS:ID   0.0043942:0.00351194:0.676012:0.863997:350470:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86938  ES:SE:LP:AF:SS:ID   0.00531957:0.00354601:0.874275:0.86938:350470:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866339 ES:SE:LP:AF:SS:ID   0.00532236:0.00354684:0.874646:0.866339:350470:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098748 ES:SE:LP:AF:SS:ID   -0.00712784:0.00424746:1.03002:0.098748:350470:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871522 ES:SE:LP:AF:SS:ID   0.00567578:0.00358718:0.944637:0.871522:350470:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871522 ES:SE:LP:AF:SS:ID   0.00567557:0.00358718:0.944587:0.871522:350470:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871522 ES:SE:LP:AF:SS:ID   0.0056783:0.00358725:0.945226:0.871522:350470:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871893 ES:SE:LP:AF:SS:ID   0.00570932:0.00358928:0.951997:0.871893:350470:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125593 ES:SE:LP:AF:SS:ID   -0.00586068:0.00359212:0.9881:0.125593:350470:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105422 ES:SE:LP:AF:SS:ID   -0.00520385:0.00391117:0.736714:0.105422:350470:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855338 ES:SE:LP:AF:SS:ID   0.00521636:0.00351102:0.862149:0.855338:350470:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164753   ES:SE:LP:AF:SS:ID   -0.0433912:0.031197:0.784458:0.00164753:350470:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83829  ES:SE:LP:AF:SS:ID   -0.00194276:0.00345845:0.240868:0.83829:350470:rs376645387