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-20117_2/ukb-d-20117_2.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-20117_2/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 16:39:57 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20117_2/ukb-d-20117_2.vcf.gz ...
Read summary statistics for 13586590 SNPs.
Dropped 12711 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: 0.0204 (0.0018)
Lambda GC: 1.1537
Mean Chi^2: 1.1633
Intercept: 1.0218 (0.0074)
Ratio: 0.1337 (0.0451)
Analysis finished at Mon Nov 25 16:42:42 2019
Total time elapsed: 2.0m:45.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0882,
    "mean_EFFECT": -3.0358e-06,
    "n": 360726,
    "n_snps": 13586590,
    "n_clumped_hits": 3,
    "n_p_sig": 4,
    "n_mono": 0,
    "n_ns": 1251806,
    "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": 569300,
    "n_est": 362096.1441,
    "ratio_se_n": 1.0019,
    "mean_diff": -8.3009e-06,
    "ratio_diff": 9.6036,
    "sd_y_est1": 0.2483,
    "sd_y_est2": 0.2488,
    "r2_sum1": 0,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0204,
    "ldsc_observed_scale_h2_se": 0.0018,
    "ldsc_intercept_beta": 1.0218,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.1537,
    "ldsc_mean_chisq": 1.1633,
    "ldsc_ratio": 0.1335
}

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 1.0000000 3 94 0 13574543 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57083 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 9.051331e+00 6.184966e+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 7.902498e+07 5.591474e+07 3.02000e+02 3.293098e+07 7.013851e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.000000e-06 3.442400e-03 -4.85067e-02 -9.425000e-04 4.000000e-06 9.521000e-04 3.929270e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.457100e-03 2.370200e-03 4.80800e-04 6.995000e-04 1.289100e-03 3.531200e-03 1.191700e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.865156e-01 2.923449e-01 0.00000e+00 2.303918e-01 4.816849e-01 7.398676e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.865152e-01 2.923452e-01 0.00000e+00 2.303907e-01 4.816841e-01 7.398669e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908016e-01 2.544020e-01 1.00000e-03 7.429600e-03 6.003010e-02 2.953060e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569300 0.9580984 NA NA NA NA NA 1.963331e-01 2.471006e-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 3.607260e+05 0.000000e+00 3.60726e+05 3.607260e+05 3.607260e+05 3.607260e+05 3.607260e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0006167 0.0010240 0.5469883 0.5469875 0.1106510 0.1894970 360726
1 693731 rs12238997 A G 0.0004832 0.0009675 0.6174645 0.6174634 0.1158340 0.1417730 360726
1 707522 rs371890604 G C 0.0007503 0.0010877 0.4903227 0.4903225 0.0973094 0.1293930 360726
1 717587 rs144155419 G A 0.0031156 0.0025956 0.2300170 0.2300173 0.0156871 0.0045926 360726
1 723329 rs189787166 A T 0.0103853 0.0076565 0.1749722 0.1749721 0.0017341 0.0003994 360726
1 730087 rs148120343 T C -0.0000683 0.0013479 0.9595749 0.9595748 0.0564653 0.0127796 360726
1 731718 rs142557973 T C 0.0004833 0.0009176 0.5983744 0.5983746 0.1217390 0.1543530 360726
1 732032 rs61770163 A C 0.0004904 0.0009788 0.6163281 0.6163268 0.1211760 0.1555510 360726
1 734349 rs141242758 T C 0.0005425 0.0009181 0.5546206 0.5546201 0.1209670 0.1525560 360726
1 740284 rs61770167 C T 0.0004828 0.0042000 0.9084819 0.9084823 0.0057864 0.0023962 360726
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0012395 0.0010602 0.2423511 0.2423493 0.0561610 0.0309934 360726
23 154923374 rs111332691 T A 0.0006904 0.0011650 0.5534368 0.5534364 0.0447902 0.0116556 360726
23 154925045 rs509981 C T 0.0001727 0.0005605 0.7580031 0.7580033 0.2456260 0.3634440 360726
23 154925895 rs538470 C T 0.0003659 0.0005734 0.5233545 0.5233542 0.2419340 0.3634440 360726
23 154927581 rs644138 G A -0.0001601 0.0005272 0.7613003 0.7612999 0.3021740 0.4635760 360726
23 154929412 rs557132 C T 0.0001633 0.0005607 0.7709194 0.7709197 0.2454780 0.3568210 360726
23 154929637 rs35185538 CT C 0.0005940 0.0005852 0.3100538 0.3100535 0.2297170 0.3011920 360726
23 154929952 rs4012982 CAA C 0.0002334 0.0005897 0.6922676 0.6922668 0.2394400 0.3165560 360726
23 154930230 rs781880 A G 0.0002502 0.0005606 0.6554024 0.6554014 0.2458870 0.3618540 360726
23 154930487 rs781879 T A -0.0010853 0.0019234 0.5725890 0.5725910 0.0195609 0.1263580 360726

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110651 ES:SE:LP:AF:SS:ID   0.000616711:0.00102396:0.262022:0.110651:360726:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115834 ES:SE:LP:AF:SS:ID   0.000483217:0.000967501:0.209388:0.115834:360726:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973094    ES:SE:LP:AF:SS:ID   0.000750291:0.0010877:0.309518:0.0973094:360726:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156871    ES:SE:LP:AF:SS:ID   0.00311556:0.00259562:0.63824:0.0156871:360726:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173413   ES:SE:LP:AF:SS:ID   0.0103853:0.00765652:0.757031:0.00173413:360726:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564653    ES:SE:LP:AF:SS:ID   -6.83198e-05:0.00134787:0.0179211:0.0564653:360726:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121739 ES:SE:LP:AF:SS:ID   0.000483336:0.0009176:0.223027:0.121739:360726:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121176 ES:SE:LP:AF:SS:ID   0.000490434:0.000978787:0.210188:0.121176:360726:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120967 ES:SE:LP:AF:SS:ID   0.000542457:0.000918094:0.256004:0.120967:360726:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578638   ES:SE:LP:AF:SS:ID   0.000482802:0.00419999:0.0416837:0.00578638:360726:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187521   ES:SE:LP:AF:SS:ID   0.00194653:0.00794004:0.0934829:0.00187521:360726:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86974  ES:SE:LP:AF:SS:ID   -0.000653556:0.000905106:0.327673:0.86974:360726:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015294    ES:SE:LP:AF:SS:ID   0.00299349:0.0081969:0.145716:0.0015294:360726:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122924 ES:SE:LP:AF:SS:ID   0.000674597:0.000896381:0.345146:0.122924:360726:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142719 ES:SE:LP:AF:SS:ID   0.000667144:0.000886012:0.345375:0.142719:360726:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123039 ES:SE:LP:AF:SS:ID   0.000675244:0.000895133:0.346171:0.123039:360726:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870887 ES:SE:LP:AF:SS:ID   -0.000738466:0.000872296:0.400957:0.870887:360726:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875465 ES:SE:LP:AF:SS:ID   -0.000819317:0.000886747:0.449151:0.875465:360726:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128635 ES:SE:LP:AF:SS:ID   0.000582101:0.000874471:0.296169:0.128635:360726:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363642    ES:SE:LP:AF:SS:ID   0.000912546:0.00158643:0.247842:0.0363642:360726:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870482 ES:SE:LP:AF:SS:ID   -0.000596032:0.000871392:0.306294:0.870482:360726:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870588 ES:SE:LP:AF:SS:ID   -0.000595987:0.000871791:0.306092:0.870588:360726:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870479 ES:SE:LP:AF:SS:ID   -0.000568825:0.00087136:0.289134:0.870479:360726:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504607   ES:SE:LP:AF:SS:ID   0.00212912:0.00447222:0.197896:0.00504607:360726:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501303   ES:SE:LP:AF:SS:ID   0.00199843:0.00448419:0.183201:0.00501303:360726:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558184   ES:SE:LP:AF:SS:ID   -0.0042928:0.00433449:0.492159:0.00558184:360726:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870561 ES:SE:LP:AF:SS:ID   -0.000732241:0.000869826:0.398063:0.870561:360726:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12599  ES:SE:LP:AF:SS:ID   0.000750327:0.000887527:0.400247:0.12599:360726:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870124 ES:SE:LP:AF:SS:ID   -0.000727593:0.000867732:0.396043:0.870124:360726:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869413 ES:SE:LP:AF:SS:ID   -0.00065941:0.000866942:0.349802:0.869413:360726:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870279 ES:SE:LP:AF:SS:ID   -0.00073345:0.00086848:0.399705:0.870279:360726:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870285 ES:SE:LP:AF:SS:ID   -0.000734542:0.000868542:0.400433:0.870285:360726:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870293 ES:SE:LP:AF:SS:ID   -0.000728829:0.000868569:0.396417:0.870293:360726:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870737 ES:SE:LP:AF:SS:ID   -0.000767784:0.000870781:0.422589:0.870737:360726:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988512    ES:SE:LP:AF:SS:ID   0.000784904:0.00101186:0.358599:0.0988512:360726:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064715    ES:SE:LP:AF:SS:ID   -0.0030066:0.00391553:0.354019:0.0064715:360726:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874629 ES:SE:LP:AF:SS:ID   -0.000834801:0.000883751:0.46236:0.874629:360726:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864024 ES:SE:LP:AF:SS:ID   -0.000667633:0.000866654:0.355474:0.864024:360726:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869421 ES:SE:LP:AF:SS:ID   -0.000736844:0.000875061:0.3982:0.869421:360726:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866367 ES:SE:LP:AF:SS:ID   -0.000709001:0.000875239:0.378925:0.866367:360726:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987825    ES:SE:LP:AF:SS:ID   0.0010877:0.00104787:0.52394:0.0987825:360726:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871551 ES:SE:LP:AF:SS:ID   -0.000768376:0.000885212:0.414103:0.871551:360726:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871551 ES:SE:LP:AF:SS:ID   -0.000768361:0.000885212:0.414092:0.871551:360726:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87155  ES:SE:LP:AF:SS:ID   -0.000768015:0.000885229:0.41384:0.87155:360726:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871925 ES:SE:LP:AF:SS:ID   -0.000783901:0.000885735:0.424648:0.871925:360726:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125568 ES:SE:LP:AF:SS:ID   0.000785174:0.00088642:0.425117:0.125568:360726:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105431 ES:SE:LP:AF:SS:ID   0.000421132:0.000965003:0.178786:0.105431:360726:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855373 ES:SE:LP:AF:SS:ID   -0.000587898:0.000866316:0.303312:0.855373:360726:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165496   ES:SE:LP:AF:SS:ID   0.00998022:0.00767298:0.713627:0.00165496:360726:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838367 ES:SE:LP:AF:SS:ID   0.000900836:0.000853507:0.53578:0.838367:360726:rs376645387