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-100920_2104/ukb-d-100920_2104.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-100920_2104/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 14:57:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-100920_2104/ukb-d-100920_2104.vcf.gz ...
Read summary statistics for 11112376 SNPs.
Dropped 9220 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, 1282121 SNPs remain.
After merging with regression SNP LD, 1282121 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0257 (0.0092)
Lambda GC: 1.0214
Mean Chi^2: 1.0235
Intercept: 0.9972 (0.0062)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 14:58:47 2019
Total time elapsed: 1.0m:39.28s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9463,
    "inflation_factor": 1.0188,
    "mean_EFFECT": 9.8854e-07,
    "n": 51427,
    "n_snps": 11112376,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1143592,
    "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": 224584,
    "n_est": 51530.4697,
    "ratio_se_n": 1.001,
    "mean_diff": 3.7779e-06,
    "ratio_diff": 7.4108,
    "sd_y_est1": 0.232,
    "sd_y_est2": 0.2322,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282121,
    "ldsc_nsnp_merge_regression_ld": 1282121,
    "ldsc_observed_scale_h2_beta": 0.0257,
    "ldsc_observed_scale_h2_se": 0.0092,
    "ldsc_intercept_beta": 0.9972,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0214,
    "ldsc_mean_chisq": 1.0235,
    "ldsc_ratio": -0.1191
}

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 11103751 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 51353 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31412 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.074830e+00 6.181819e+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 7.881978e+07 5.601803e+07 3.02000e+02 3.260319e+07 6.979347e+07 1.147297e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.000000e-06 4.571300e-03 -4.27843e-02 -1.802200e-03 -1.170000e-05 1.769400e-03 5.697800e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.668500e-03 2.697400e-03 1.19150e-03 1.630300e-03 2.403600e-03 4.924900e-03 1.612750e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.971885e-01 2.896649e-01 1.00000e-07 2.455079e-01 4.960004e-01 7.480127e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.971854e-01 2.896667e-01 1.00000e-07 2.455026e-01 4.959966e-01 7.480106e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.308625e-01 2.615737e-01 4.26040e-03 2.314430e-02 1.154260e-01 3.693420e-01 9.957390e-01 ▇▂▂▁▁
numeric AF_reference 224584 0.9797897 NA NA NA NA NA 2.311743e-01 2.527032e-01 0.00000e+00 2.156550e-02 1.331870e-01 3.680110e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.142700e+04 0.000000e+00 5.14270e+04 5.142700e+04 5.142700e+04 5.142700e+04 5.142700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0027243 0.0025196 0.2795889 0.2795834 0.1121000 0.1894970 51427
1 693731 rs12238997 A G -0.0020111 0.0023943 0.4009378 0.4009331 0.1168090 0.1417730 51427
1 707522 rs371890604 G C -0.0039459 0.0026854 0.1417310 0.1417246 0.0982930 0.1293930 51427
1 717587 rs144155419 G A -0.0007550 0.0064921 0.9074220 0.9074220 0.0154808 0.0045926 51427
1 730087 rs148120343 T C -0.0053792 0.0033343 0.1066901 0.1066843 0.0570822 0.0127796 51427
1 731718 rs142557973 T C -0.0017940 0.0022753 0.4304245 0.4304233 0.1225210 0.1543530 51427
1 732032 rs61770163 A C -0.0029642 0.0024254 0.2216598 0.2216527 0.1216510 0.1555510 51427
1 734349 rs141242758 T C -0.0019769 0.0022765 0.3851811 0.3851775 0.1217650 0.1525560 51427
1 740284 rs61770167 C T -0.0064854 0.0099490 0.5144948 0.5144918 0.0062329 0.0023962 51427
1 749963 rs529266287 T TAA 0.0028247 0.0022410 0.2075181 0.2075125 0.8686130 0.7641770 51427
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0047085 0.0026768 0.0785814 0.0785760 0.0542488 0.0309934 51427
23 154923374 rs111332691 T A -0.0004681 0.0028997 0.8717471 0.8717461 0.0445389 0.0116556 51427
23 154925045 rs509981 C T -0.0018829 0.0013939 0.1767738 0.1767697 0.2434190 0.3634440 51427
23 154925895 rs538470 C T -0.0021311 0.0014239 0.1344950 0.1344907 0.2401390 0.3634440 51427
23 154927581 rs644138 G A -0.0005981 0.0013112 0.6483015 0.6483015 0.2981050 0.4635760 51427
23 154929412 rs557132 C T -0.0019178 0.0013944 0.1690468 0.1690406 0.2432580 0.3568210 51427
23 154929637 rs35185538 CT C -0.0035686 0.0014529 0.0140427 0.0140397 0.2278210 0.3011920 51427
23 154929952 rs4012982 CAA C -0.0018307 0.0014671 0.2120958 0.2120905 0.2374290 0.3165560 51427
23 154930230 rs781880 A G -0.0020665 0.0013938 0.1381888 0.1381841 0.2438260 0.3618540 51427
23 154930487 rs781879 T A -0.0145660 0.0048464 0.0026525 0.0026512 0.0189843 0.1263580 51427

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.1121   ES:SE:LP:AF:SS:ID   -0.00272431:0.00251958:0.55348:0.1121:51427:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116809 ES:SE:LP:AF:SS:ID   -0.00201114:0.00239434:0.396923:0.116809:51427:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098293 ES:SE:LP:AF:SS:ID   -0.00394588:0.00268537:0.848535:0.098293:51427:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154808    ES:SE:LP:AF:SS:ID   -0.000754969:0.00649207:0.0421907:0.0154808:51427:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0570822    ES:SE:LP:AF:SS:ID   -0.00537915:0.0033343:0.971876:0.0570822:51427:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122521 ES:SE:LP:AF:SS:ID   -0.001794:0.0022753:0.366103:0.122521:51427:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121651 ES:SE:LP:AF:SS:ID   -0.00296424:0.00242544:0.654313:0.121651:51427:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121765 ES:SE:LP:AF:SS:ID   -0.00197693:0.00227653:0.414335:0.121765:51427:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0062329    ES:SE:LP:AF:SS:ID   -0.00648537:0.00994903:0.288619:0.0062329:51427:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.868613 ES:SE:LP:AF:SS:ID   0.00282466:0.00224102:0.682944:0.868613:51427:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123957 ES:SE:LP:AF:SS:ID   -0.00224134:0.00222006:0.504874:0.123957:51427:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143385 ES:SE:LP:AF:SS:ID   -0.00313908:0.00220261:0.812149:0.143385:51427:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124126 ES:SE:LP:AF:SS:ID   -0.00223922:0.00221637:0.505356:0.124126:51427:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869933 ES:SE:LP:AF:SS:ID   0.00194428:0.00216007:0.434068:0.869933:51427:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874426 ES:SE:LP:AF:SS:ID   0.00192005:0.00219441:0.418401:0.874426:51427:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129659 ES:SE:LP:AF:SS:ID   -0.00218382:0.00216538:0.50416:0.129659:51427:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0369164    ES:SE:LP:AF:SS:ID   0.0068345:0.00390006:1.09849:0.0369164:51427:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869554 ES:SE:LP:AF:SS:ID   0.00201068:0.00215805:0.454086:0.869554:51427:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869648 ES:SE:LP:AF:SS:ID   0.00196151:0.00215917:0.439326:0.869648:51427:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   0.00200585:0.00215804:0.452659:0.86957:51427:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00531261   ES:SE:LP:AF:SS:ID   -0.0100821:0.0108162:0.454354:0.00531261:51427:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00527727   ES:SE:LP:AF:SS:ID   -0.00989625:0.0108446:0.441911:0.00527727:51427:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0057746    ES:SE:LP:AF:SS:ID   -0.00148263:0.010577:0.0513313:0.0057746:51427:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869706 ES:SE:LP:AF:SS:ID   0.00195973:0.00215479:0.439969:0.869706:51427:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12702  ES:SE:LP:AF:SS:ID   -0.00245076:0.00219764:0.577116:0.12702:51427:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   0.00199591:0.00214913:0.452169:0.869213:51427:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868449 ES:SE:LP:AF:SS:ID   0.00238849:0.00214704:0.575205:0.868449:51427:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   0.00204647:0.00215149:0.466591:0.869419:51427:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869426 ES:SE:LP:AF:SS:ID   0.00204245:0.00215163:0.465346:0.869426:51427:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   0.00203782:0.00215174:0.463929:0.869437:51427:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869848 ES:SE:LP:AF:SS:ID   0.00197003:0.00215676:0.442463:0.869848:51427:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0999077    ES:SE:LP:AF:SS:ID   -0.00256823:0.0025011:0.516411:0.0999077:51427:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00659027   ES:SE:LP:AF:SS:ID   -0.000571855:0.00960695:0.0211195:0.00659027:51427:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87358  ES:SE:LP:AF:SS:ID   0.00215639:0.00218791:0.489002:0.87358:51427:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86295  ES:SE:LP:AF:SS:ID   0.00202491:0.00214646:0.461557:0.86295:51427:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868667 ES:SE:LP:AF:SS:ID   0.00207371:0.00216752:0.470171:0.868667:51427:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.8652   ES:SE:LP:AF:SS:ID   0.00177219:0.00216656:0.383656:0.8652:51427:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0992889    ES:SE:LP:AF:SS:ID   -0.00167691:0.00260025:0.284838:0.0992889:51427:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   0.00187135:0.00219091:0.405574:0.870459:51427:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   0.00187137:0.00219091:0.405581:0.870459:51427:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870456 ES:SE:LP:AF:SS:ID   0.00187154:0.00219092:0.405624:0.870456:51427:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870829 ES:SE:LP:AF:SS:ID   0.001908:0.00219217:0.415555:0.870829:51427:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126636 ES:SE:LP:AF:SS:ID   -0.00220806:0.00219461:0.502574:0.126636:51427:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106247 ES:SE:LP:AF:SS:ID   -0.00293219:0.00238995:0.657828:0.106247:51427:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854084 ES:SE:LP:AF:SS:ID   0.00297285:0.00214622:0.779866:0.854084:51427:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836377 ES:SE:LP:AF:SS:ID   0.0019154:0.00210189:0.441107:0.836377:51427:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.76015  ES:SE:LP:AF:SS:ID   0.00296922:0.00168972:1.10301:0.76015:51427:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108173 ES:SE:LP:AF:SS:ID   -0.00276183:0.00231926:0.631289:0.108173:51427:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00771274   ES:SE:LP:AF:SS:ID   -0.00241249:0.00875532:0.106294:0.00771274:51427:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129757 ES:SE:LP:AF:SS:ID   -0.00207389:0.0021656:0.470771:0.129757:51427:rs762168062