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-22609_1/ukb-d-22609_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-22609_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 16:37:37 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22609_1/ukb-d-22609_1.vcf.gz ...
Read summary statistics for 13566661 SNPs.
Dropped 12680 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: 0.0217 (0.005)
Lambda GC: 1.0524
Mean Chi^2: 1.0501
Intercept: 1.012 (0.0057)
Ratio: 0.2386 (0.1148)
Analysis finished at Mon Nov 25 16:39:54 2019
Total time elapsed: 2.0m:16.4s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0329,
    "mean_EFFECT": 0,
    "n": 89562,
    "n_snps": 13566661,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1251230,
    "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": 563165,
    "n_est": 89889.4191,
    "ratio_se_n": 1.0018,
    "mean_diff": 0,
    "ratio_diff": 18.3581,
    "sd_y_est1": 0.4747,
    "sd_y_est2": 0.4756,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0217,
    "ldsc_observed_scale_h2_se": 0.005,
    "ldsc_intercept_beta": 1.012,
    "ldsc_intercept_se": 0.0057,
    "ldsc_lambda_gc": 1.0524,
    "ldsc_mean_chisq": 1.0501,
    "ldsc_ratio": 0.2395
}

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 1.000000 3 94 0 13554645 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 57046 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33333 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.051295e+00 6.184988e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.902445e+07 5.591679e+07 3.02000e+02 3.292726e+07 7.013420e+07 1.148613e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 4.390000e-05 1.308410e-02 -1.64492e-01 -3.492500e-03 1.300000e-05 3.536900e-03 1.689360e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 9.387100e-03 9.046400e-03 1.84950e-03 2.682100e-03 4.933300e-03 1.347870e-02 4.534400e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.951482e-01 2.900127e-01 2.00000e-07 2.422947e-01 4.930364e-01 7.464453e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.951465e-01 2.900137e-01 2.00000e-07 2.422918e-01 4.930346e-01 7.464450e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 1.910634e-01 2.544666e-01 1.00000e-03 7.499500e-03 6.029800e-02 2.957620e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563165 0.958489 NA NA NA NA NA 1.965199e-01 2.471384e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 8.956200e+04 0.000000e+00 8.95620e+04 8.956200e+04 8.956200e+04 8.956200e+04 8.956200e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0028432 0.0039189 0.4681457 0.4681449 0.1113090 0.1894970 89562
1 693731 rs12238997 A G -0.0019590 0.0037124 0.5977203 0.5977188 0.1162770 0.1417730 89562
1 707522 rs371890604 G C -0.0019207 0.0041709 0.6451564 0.6451562 0.0977315 0.1293930 89562
1 717587 rs144155419 G A -0.0024109 0.0099311 0.8081889 0.8081881 0.0158008 0.0045926 89562
1 723329 rs189787166 A T -0.0074029 0.0290310 0.7987230 0.7987224 0.0017729 0.0003994 89562
1 730087 rs148120343 T C -0.0039870 0.0051514 0.4389631 0.4389609 0.0568096 0.0127796 89562
1 731718 rs142557973 T C -0.0017512 0.0035230 0.6191373 0.6191362 0.1221450 0.1543530 89562
1 732032 rs61770163 A C -0.0023834 0.0037557 0.5256903 0.5256898 0.1218650 0.1555510 89562
1 734349 rs141242758 T C -0.0014728 0.0035258 0.6761468 0.6761466 0.1213800 0.1525560 89562
1 740284 rs61770167 C T 0.0087730 0.0161500 0.5869782 0.5869776 0.0057610 0.0023962 89562
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0044726 0.0041179 0.2774138 0.2774110 0.0552866 0.0309934 89562
23 154923374 rs111332691 T A 0.0024888 0.0044767 0.5782585 0.5782570 0.0449019 0.0116556 89562
23 154925045 rs509981 C T -0.0024916 0.0021583 0.2483379 0.2483336 0.2446180 0.3634440 89562
23 154925895 rs538470 C T -0.0023958 0.0022064 0.2775447 0.2775436 0.2411630 0.3634440 89562
23 154927581 rs644138 G A -0.0010109 0.0020304 0.6185574 0.6185567 0.3003140 0.4635760 89562
23 154929412 rs557132 C T -0.0025326 0.0021589 0.2407709 0.2407670 0.2444790 0.3568210 89562
23 154929637 rs35185538 CT C -0.0033545 0.0022546 0.1367921 0.1367878 0.2288450 0.3011920 89562
23 154929952 rs4012982 CAA C -0.0021502 0.0022723 0.3440290 0.3440262 0.2384420 0.3165560 89562
23 154930230 rs781880 A G -0.0024451 0.0021582 0.2572367 0.2572336 0.2449390 0.3618540 89562
23 154930487 rs781879 T A -0.0056238 0.0073164 0.4420964 0.4420949 0.0196612 0.1263580 89562

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111309 ES:SE:LP:AF:SS:ID   -0.00284315:0.00391888:0.329619:0.111309:89562:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116277 ES:SE:LP:AF:SS:ID   -0.001959:0.00371245:0.223502:0.116277:89562:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977315    ES:SE:LP:AF:SS:ID   -0.00192072:0.00417093:0.190335:0.0977315:89562:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158008    ES:SE:LP:AF:SS:ID   -0.00241091:0.00993108:0.0924871:0.0158008:89562:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00177288   ES:SE:LP:AF:SS:ID   -0.00740293:0.029031:0.0976038:0.00177288:89562:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568096    ES:SE:LP:AF:SS:ID   -0.00398696:0.00515145:0.357572:0.0568096:89562:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122145 ES:SE:LP:AF:SS:ID   -0.00175121:0.00352303:0.208213:0.122145:89562:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121865 ES:SE:LP:AF:SS:ID   -0.00238339:0.00375574:0.27927:0.121865:89562:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12138  ES:SE:LP:AF:SS:ID   -0.00147281:0.00352577:0.169959:0.12138:89562:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00576098   ES:SE:LP:AF:SS:ID   0.00877302:0.01615:0.231378:0.00576098:89562:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00181104   ES:SE:LP:AF:SS:ID   -0.0271711:0.031051:0.418449:0.00181104:89562:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869125 ES:SE:LP:AF:SS:ID   0.00161776:0.00346764:0.193253:0.869125:89562:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00158168   ES:SE:LP:AF:SS:ID   0.0396041:0.0308253:0.701433:0.00158168:89562:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12349  ES:SE:LP:AF:SS:ID   -0.00255992:0.00343784:0.340562:0.12349:89562:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142997 ES:SE:LP:AF:SS:ID   -0.00103142:0.00340336:0.118133:0.142997:89562:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123626 ES:SE:LP:AF:SS:ID   -0.0025944:0.00343286:0.346982:0.123626:89562:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870103 ES:SE:LP:AF:SS:ID   0.00305628:0.00334463:0.442696:0.870103:89562:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874761 ES:SE:LP:AF:SS:ID   0.00318737:0.00339906:0.457933:0.874761:89562:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12933  ES:SE:LP:AF:SS:ID   -0.00270242:0.00335514:0.376174:0.12933:89562:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.035735 ES:SE:LP:AF:SS:ID   0.00939597:0.00613294:0.901311:0.035735:89562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86975  ES:SE:LP:AF:SS:ID   0.00294418:0.00334183:0.422145:0.86975:89562:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869821 ES:SE:LP:AF:SS:ID   0.00288787:0.00334308:0.411525:0.869821:89562:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869746 ES:SE:LP:AF:SS:ID   0.00293731:0.00334169:0.420891:0.869746:89562:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0053199    ES:SE:LP:AF:SS:ID   -0.00771553:0.0166811:0.191316:0.0053199:89562:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00528515   ES:SE:LP:AF:SS:ID   -0.00713744:0.0167222:0.174244:0.00528515:89562:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00567824   ES:SE:LP:AF:SS:ID   -0.0220194:0.0164185:0.745012:0.00567824:89562:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869731 ES:SE:LP:AF:SS:ID   0.00294155:0.00333475:0.422817:0.869731:89562:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126712 ES:SE:LP:AF:SS:ID   -0.00251901:0.00340424:0.337881:0.126712:89562:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869258 ES:SE:LP:AF:SS:ID   0.00273927:0.00332606:0.387023:0.869258:89562:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868646 ES:SE:LP:AF:SS:ID   0.00299563:0.00332391:0.434784:0.868646:89562:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869412 ES:SE:LP:AF:SS:ID   0.002911:0.00332913:0.418049:0.869412:89562:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869418 ES:SE:LP:AF:SS:ID   0.00291361:0.00332935:0.418499:0.869418:89562:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86942  ES:SE:LP:AF:SS:ID   0.00291795:0.00332937:0.419303:0.86942:89562:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869902 ES:SE:LP:AF:SS:ID   0.00295952:0.00333834:0.425577:0.869902:89562:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0990065    ES:SE:LP:AF:SS:ID   -0.0019208:0.00388523:0.206883:0.0990065:89562:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00651815   ES:SE:LP:AF:SS:ID   -0.0246994:0.0149507:1.00645:0.00651815:89562:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873896 ES:SE:LP:AF:SS:ID   0.00289762:0.00338793:0.406272:0.873896:89562:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863289 ES:SE:LP:AF:SS:ID   0.00215082:0.00332307:0.286106:0.863289:89562:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868694 ES:SE:LP:AF:SS:ID   0.00278887:0.00335601:0.391505:0.868694:89562:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865572 ES:SE:LP:AF:SS:ID   0.00311268:0.00335646:0.45132:0.865572:89562:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993349    ES:SE:LP:AF:SS:ID   -0.00271252:0.00401889:0.301278:0.0993349:89562:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870874 ES:SE:LP:AF:SS:ID   0.00278757:0.00339524:0.385488:0.870874:89562:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870874 ES:SE:LP:AF:SS:ID   0.00278708:0.00339524:0.385401:0.870874:89562:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870871 ES:SE:LP:AF:SS:ID   0.0027872:0.00339525:0.38542:0.870871:89562:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87123  ES:SE:LP:AF:SS:ID   0.00295964:0.00339685:0.416125:0.87123:89562:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126307 ES:SE:LP:AF:SS:ID   -0.00278864:0.00340048:0.384917:0.126307:89562:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10582  ES:SE:LP:AF:SS:ID   -0.00191239:0.00369711:0.218265:0.10582:89562:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85461  ES:SE:LP:AF:SS:ID   0.00326023:0.00332196:0.486263:0.85461:89562:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00168487   ES:SE:LP:AF:SS:ID   -0.00875158:0.02912:0.117037:0.00168487:89562:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839219 ES:SE:LP:AF:SS:ID   0.00154238:0.00328091:0.194989:0.839219:89562:rs376645387