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-20536_1/ukb-d-20536_1.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-20536_1/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 16:39:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20536_1/ukb-d-20536_1.vcf.gz ...
Read summary statistics for 13215787 SNPs.
Dropped 12186 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, 1283435 SNPs remain.
After merging with regression SNP LD, 1283435 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0584 (0.0084)
Lambda GC: 1.0544
Mean Chi^2: 1.0626
Intercept: 0.9974 (0.0064)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:42:08 2019
Total time elapsed: 2.0m:15.0s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9515,
    "inflation_factor": 1.0282,
    "mean_EFFECT": -0,
    "n": 56571,
    "n_snps": 13215787,
    "n_clumped_hits": 1,
    "n_p_sig": 71,
    "n_mono": 0,
    "n_ns": 1238267,
    "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": 476875,
    "n_est": 56700.5505,
    "ratio_se_n": 1.0011,
    "mean_diff": -0,
    "ratio_diff": 11.0358,
    "sd_y_est1": 0.3758,
    "sd_y_est2": 0.3763,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0006,
    "r2_sum3": 0.0006,
    "r2_sum4": 0.0007,
    "ldsc_nsnp_merge_refpanel_ld": 1283435,
    "ldsc_nsnp_merge_regression_ld": 1283435,
    "ldsc_observed_scale_h2_beta": 0.0584,
    "ldsc_observed_scale_h2_se": 0.0084,
    "ldsc_intercept_beta": 0.9974,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0544,
    "ldsc_mean_chisq": 1.0626,
    "ldsc_ratio": -0.0415
}

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 13204257 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56326 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33114 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.055765e+00 6.185281e+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 7.898821e+07 5.592590e+07 3.02000e+02 3.286892e+07 7.007602e+07 1.148232e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.720000e-05 1.190040e-02 -1.28119e-01 -3.443900e-03 -3.530000e-05 3.337200e-03 1.583950e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.684900e-03 8.119100e-03 1.90460e-03 2.647800e-03 4.701100e-03 1.238180e-02 4.332530e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.953640e-01 2.902172e-01 0.00000e+00 2.427482e-01 4.940183e-01 7.468425e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.953612e-01 2.902189e-01 0.00000e+00 2.427432e-01 4.940152e-01 7.468420e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.958657e-01 2.556220e-01 1.28760e-03 8.794100e-03 6.648880e-02 3.053520e-01 9.987120e-01 ▇▂▁▁▁
numeric AF_reference 476875 0.9639163 NA NA NA NA NA 2.001612e-01 2.479395e-01 0.00000e+00 6.589500e-03 8.945690e-02 3.152960e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.657100e+04 0.000000e+00 5.65710e+04 5.657100e+04 5.657100e+04 5.657100e+04 5.657100e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0009140 0.0038869 0.8140881 0.8140870 0.1120070 0.1894970 56571
1 693731 rs12238997 A G -0.0029015 0.0036766 0.4300213 0.4300165 0.1168710 0.1417730 56571
1 707522 rs371890604 G C -0.0056018 0.0041286 0.1748441 0.1748392 0.0983231 0.1293930 56571
1 717587 rs144155419 G A 0.0044338 0.0098491 0.6525879 0.6525865 0.0158084 0.0045926 56571
1 723329 rs189787166 A T -0.0180500 0.0280162 0.5194025 0.5194003 0.0018800 0.0003994 56571
1 730087 rs148120343 T C -0.0068025 0.0051199 0.1839780 0.1839724 0.0569925 0.0127796 56571
1 731718 rs142557973 T C -0.0019107 0.0034884 0.5838778 0.5838749 0.1228370 0.1543530 56571
1 732032 rs61770163 A C -0.0041538 0.0037165 0.2637200 0.2637151 0.1222970 0.1555510 56571
1 734349 rs141242758 T C -0.0016485 0.0034900 0.6366797 0.6366781 0.1221100 0.1525560 56571
1 740284 rs61770167 C T -0.0068615 0.0156254 0.6605733 0.6605711 0.0060746 0.0023962 56571
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0004379 0.0042287 0.9175239 0.9175234 0.0559256 0.0309934 56571
23 154923374 rs111332691 T A -0.0050901 0.0046768 0.2764369 0.2764318 0.0437061 0.0116556 56571
23 154925045 rs509981 C T 0.0006695 0.0022226 0.7632574 0.7632555 0.2456330 0.3634440 56571
23 154925895 rs538470 C T 0.0006009 0.0022728 0.7914874 0.7914871 0.2420240 0.3634440 56571
23 154927581 rs644138 G A 0.0007324 0.0020905 0.7260742 0.7260727 0.3019940 0.4635760 56571
23 154929412 rs557132 C T 0.0006421 0.0022231 0.7727037 0.7727030 0.2455120 0.3568210 56571
23 154929637 rs35185538 CT C -0.0009897 0.0023237 0.6701623 0.6701617 0.2288990 0.3011920 56571
23 154929952 rs4012982 CAA C 0.0002931 0.0023432 0.9004510 0.9004506 0.2391570 0.3165560 56571
23 154930230 rs781880 A G 0.0008766 0.0022228 0.6933125 0.6933107 0.2458300 0.3618540 56571
23 154930487 rs781879 T A 0.0028856 0.0075852 0.7036359 0.7036347 0.0194161 0.1263580 56571

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112007 ES:SE:LP:AF:SS:ID   -0.000914036:0.00388692:0.0893286:0.112007:56571:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116871 ES:SE:LP:AF:SS:ID   -0.00290147:0.00367664:0.36651:0.116871:56571:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983231    ES:SE:LP:AF:SS:ID   -0.00560177:0.00412861:0.757349:0.0983231:56571:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158084    ES:SE:LP:AF:SS:ID   0.00443377:0.00984906:0.185361:0.0158084:56571:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00187996   ES:SE:LP:AF:SS:ID   -0.01805:0.0280162:0.284496:0.00187996:56571:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0569925    ES:SE:LP:AF:SS:ID   -0.00680247:0.00511994:0.735234:0.0569925:56571:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122837 ES:SE:LP:AF:SS:ID   -0.00191073:0.00348843:0.233678:0.122837:56571:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122297 ES:SE:LP:AF:SS:ID   -0.00415377:0.00371651:0.578857:0.122297:56571:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12211  ES:SE:LP:AF:SS:ID   -0.00164851:0.00349003:0.196079:0.12211:56571:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00607462   ES:SE:LP:AF:SS:ID   -0.0068615:0.0156254:0.180079:0.00607462:56571:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187725   ES:SE:LP:AF:SS:ID   0.0141216:0.0302127:0.193677:0.00187725:56571:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869034 ES:SE:LP:AF:SS:ID   0.00157711:0.00344031:0.189329:0.869034:56571:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152552   ES:SE:LP:AF:SS:ID   -0.0277596:0.0312173:0.42727:0.00152552:56571:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123945 ES:SE:LP:AF:SS:ID   -0.00163904:0.00340681:0.200355:0.123945:56571:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143307 ES:SE:LP:AF:SS:ID   -0.0020993:0.00337294:0.272715:0.143307:56571:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12403  ES:SE:LP:AF:SS:ID   -0.00163163:0.00340243:0.199592:0.12403:56571:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869798 ES:SE:LP:AF:SS:ID   0.000552773:0.00331772:0.0616424:0.869798:56571:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874432 ES:SE:LP:AF:SS:ID   0.00152159:0.00337077:0.185954:0.874432:56571:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129654 ES:SE:LP:AF:SS:ID   -0.000508441:0.00332571:0.0562622:0.129654:56571:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0366265    ES:SE:LP:AF:SS:ID   0.00375005:0.00603732:0.272047:0.0366265:56571:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8694   ES:SE:LP:AF:SS:ID   0.000595609:0.00331403:0.0668317:0.8694:56571:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86946  ES:SE:LP:AF:SS:ID   0.000599781:0.00331473:0.0673173:0.86946:56571:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869403 ES:SE:LP:AF:SS:ID   0.000592344:0.00331392:0.0664424:0.869403:56571:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00495789   ES:SE:LP:AF:SS:ID   -0.00117665:0.0172727:0.0242517:0.00495789:56571:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00492638   ES:SE:LP:AF:SS:ID   -0.00110045:0.0173103:0.0225915:0.00492638:56571:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00576142   ES:SE:LP:AF:SS:ID   -0.00104418:0.0163111:0.0227535:0.00576142:56571:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869451 ES:SE:LP:AF:SS:ID   0.000473424:0.00330831:0.0524629:0.869451:56571:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127054 ES:SE:LP:AF:SS:ID   -0.000666209:0.00337471:0.0739118:0.127054:56571:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:SS:ID   0.000404843:0.00329945:0.0446274:0.868952:56571:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868377 ES:SE:LP:AF:SS:ID   0.000306533:0.00329748:0.033419:0.868377:56571:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86916  ES:SE:LP:AF:SS:ID   0.000438908:0.00330275:0.0485265:0.86916:56571:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869166 ES:SE:LP:AF:SS:ID   0.000437059:0.00330298:0.048308:0.869166:56571:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86917  ES:SE:LP:AF:SS:ID   0.000441345:0.00330301:0.0488063:0.86917:56571:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869567 ES:SE:LP:AF:SS:ID   0.000604437:0.00331106:0.0679572:0.869567:56571:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0998903    ES:SE:LP:AF:SS:ID   -0.00335913:0.00384076:0.418169:0.0998903:56571:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00671909   ES:SE:LP:AF:SS:ID   0.00551916:0.0146325:0.151173:0.00671909:56571:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87357  ES:SE:LP:AF:SS:ID   0.00138036:0.00336167:0.166627:0.87357:56571:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862977 ES:SE:LP:AF:SS:ID   0.00013397:0.0032966:0.0143113:0.862977:56571:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868296 ES:SE:LP:AF:SS:ID   0.000799425:0.00332976:0.0913729:0.868296:56571:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865477 ES:SE:LP:AF:SS:ID   0.000933127:0.00333295:0.108183:0.865477:56571:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100288 ES:SE:LP:AF:SS:ID   -0.000777242:0.00396907:0.0732728:0.100288:56571:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870571 ES:SE:LP:AF:SS:ID   0.0011417:0.00336902:0.13389:0.870571:56571:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870571 ES:SE:LP:AF:SS:ID   0.00114143:0.00336902:0.133854:0.870571:56571:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870568 ES:SE:LP:AF:SS:ID   0.00114172:0.00336903:0.133893:0.870568:56571:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870876 ES:SE:LP:AF:SS:ID   0.00123257:0.00337:0.145965:0.870876:56571:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126626 ES:SE:LP:AF:SS:ID   -0.00108403:0.0033714:0.126212:0.126626:56571:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106451 ES:SE:LP:AF:SS:ID   -0.00225503:0.00366588:0.268843:0.106451:56571:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85426  ES:SE:LP:AF:SS:ID   0.00120448:0.00329538:0.145855:0.85426:56571:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00178176   ES:SE:LP:AF:SS:ID   -0.0239003:0.0281908:0.401703:0.00178176:56571:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837605 ES:SE:LP:AF:SS:ID   -0.00139304:0.00325995:0.174478:0.837605:56571:rs376645387