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-4990/ukb-d-4990.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-4990/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 17:20:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4990/ukb-d-4990.vcf.gz ...
Read summary statistics for 13565870 SNPs.
Dropped 12688 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0894 (0.0058)
Lambda GC: 1.1777
Mean Chi^2: 1.1851
Intercept: 1.0044 (0.0069)
Ratio: 0.0239 (0.0372)
Analysis finished at Mon Nov 25 17:22:18 2019
Total time elapsed: 2.0m:16.83s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1092,
    "mean_EFFECT": -0.0001,
    "n": 102181,
    "n_snps": 13565870,
    "n_clumped_hits": 2,
    "n_p_sig": 279,
    "n_mono": 0,
    "n_ns": 1251145,
    "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": 562679,
    "n_est": 102569.1947,
    "ratio_se_n": 1.0019,
    "mean_diff": -0.0001,
    "ratio_diff": 22.1847,
    "sd_y_est1": 0.4631,
    "sd_y_est2": 0.464,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0007,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.0894,
    "ldsc_observed_scale_h2_se": 0.0058,
    "ldsc_intercept_beta": 1.0044,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.1777,
    "ldsc_mean_chisq": 1.1851,
    "ldsc_ratio": 0.0238
}

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 13553846 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57049 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33328 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051474e+00 6.185060e+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 7.902510e+07 5.591684e+07 3.02000e+02 3.292812e+07 7.013826e+07 1.148571e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.800000e-05 1.200910e-02 -1.53692e-01 -3.408800e-03 -5.060000e-05 3.304600e-03 1.496430e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.570500e-03 8.258300e-03 1.68300e-03 2.448900e-03 4.503800e-03 1.230510e-02 4.180410e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.833437e-01 2.929234e-01 0.00000e+00 2.257532e-01 4.774787e-01 7.369415e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.833421e-01 2.929243e-01 0.00000e+00 2.257502e-01 4.774772e-01 7.369404e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910849e-01 2.544680e-01 1.00000e-03 7.513000e-03 6.034040e-02 2.958690e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 562679 0.9585225 NA NA NA NA NA 1.965304e-01 2.471451e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.021810e+05 0.000000e+00 1.02181e+05 1.021810e+05 1.021810e+05 1.021810e+05 1.021810e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0007338 0.0035747 0.8373650 0.8373649 0.1120500 0.1894970 102181
1 693731 rs12238997 A G -0.0005839 0.0033826 0.8629611 0.8629605 0.1172390 0.1417730 102181
1 707522 rs371890604 G C -0.0018333 0.0037940 0.6289513 0.6289519 0.0986131 0.1293930 102181
1 717587 rs144155419 G A 0.0006237 0.0091175 0.9454579 0.9454577 0.0157298 0.0045926 102181
1 723329 rs189787166 A T 0.0186515 0.0268681 0.4875655 0.4875646 0.0017151 0.0003994 102181
1 730087 rs148120343 T C 0.0037692 0.0047189 0.4244426 0.4244417 0.0569807 0.0127796 102181
1 731718 rs142557973 T C -0.0021929 0.0032115 0.4947229 0.4947206 0.1230590 0.1543530 102181
1 732032 rs61770163 A C -0.0032282 0.0034208 0.3453337 0.3453315 0.1226360 0.1555510 102181
1 734349 rs141242758 T C -0.0019002 0.0032137 0.5543295 0.5543283 0.1222720 0.1525560 102181
1 740284 rs61770167 C T -0.0175972 0.0144453 0.2231542 0.2231497 0.0059951 0.0023962 102181
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0023498 0.0037446 0.5303078 0.5303079 0.0552463 0.0309934 102181
23 154923374 rs111332691 T A -0.0012765 0.0041087 0.7560421 0.7560405 0.0440297 0.0116556 102181
23 154925045 rs509981 C T 0.0009667 0.0019685 0.6233486 0.6233473 0.2435530 0.3634440 102181
23 154925895 rs538470 C T 0.0010062 0.0020128 0.6171475 0.6171468 0.2400390 0.3634440 102181
23 154927581 rs644138 G A 0.0001556 0.0018508 0.9329960 0.9329961 0.2992230 0.4635760 102181
23 154929412 rs557132 C T 0.0009197 0.0019692 0.6404644 0.6404634 0.2433820 0.3568210 102181
23 154929637 rs35185538 CT C 0.0014370 0.0020538 0.4841255 0.4841235 0.2275790 0.3011920 102181
23 154929952 rs4012982 CAA C 0.0009686 0.0020715 0.6400929 0.6400915 0.2375740 0.3165560 102181
23 154930230 rs781880 A G 0.0008255 0.0019688 0.6750066 0.6750063 0.2438100 0.3618540 102181
23 154930487 rs781879 T A 0.0047441 0.0068331 0.4875038 0.4875028 0.0190663 0.1263580 102181

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11205  ES:SE:LP:AF:SS:ID   -0.000733768:0.00357473:0.0770852:0.11205:102181:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117239 ES:SE:LP:AF:SS:ID   -0.000583851:0.00338255:0.0640088:0.117239:102181:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0986131    ES:SE:LP:AF:SS:ID   -0.00183329:0.00379404:0.201383:0.0986131:102181:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157298    ES:SE:LP:AF:SS:ID   0.000623743:0.00911746:0.0243578:0.0157298:102181:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00171512   ES:SE:LP:AF:SS:ID   0.0186515:0.0268681:0.311967:0.00171512:102181:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0569807    ES:SE:LP:AF:SS:ID   0.00376917:0.0047189:0.372181:0.0569807:102181:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123059 ES:SE:LP:AF:SS:ID   -0.00219289:0.00321152:0.305638:0.123059:102181:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122636 ES:SE:LP:AF:SS:ID   -0.00322818:0.00342083:0.461761:0.122636:102181:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122272 ES:SE:LP:AF:SS:ID   -0.00190023:0.00321372:0.256232:0.122272:102181:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00599507   ES:SE:LP:AF:SS:ID   -0.0175972:0.0144453:0.651395:0.00599507:102181:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00181859   ES:SE:LP:AF:SS:ID   -0.000120349:0.0286542:0.00145776:0.00181859:102181:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868304 ES:SE:LP:AF:SS:ID   0.00164932:0.00316812:0.219937:0.868304:102181:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00160263   ES:SE:LP:AF:SS:ID   -0.0273037:0.0279122:0.484154:0.00160263:102181:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12439  ES:SE:LP:AF:SS:ID   -0.00148299:0.0031367:0.196292:0.12439:102181:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144065 ES:SE:LP:AF:SS:ID   0.000833483:0.0031061:0.103231:0.144065:102181:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124516 ES:SE:LP:AF:SS:ID   -0.00147296:0.00313204:0.195077:0.124516:102181:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869386 ES:SE:LP:AF:SS:ID   0.00115812:0.00305107:0.152267:0.869386:102181:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874026 ES:SE:LP:AF:SS:ID   0.0013536:0.00310174:0.178783:0.874026:102181:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130201 ES:SE:LP:AF:SS:ID   -0.000932588:0.00305791:0.118966:0.130201:102181:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0366213    ES:SE:LP:AF:SS:ID   -0.00293551:0.00553876:0.224668:0.0366213:102181:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86899  ES:SE:LP:AF:SS:ID   0.000880826:0.00304807:0.112046:0.86899:102181:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869125 ES:SE:LP:AF:SS:ID   0.000932815:0.0030498:0.119352:0.869125:102181:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86899  ES:SE:LP:AF:SS:ID   0.000953861:0.00304793:0.122447:0.86899:102181:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00521255   ES:SE:LP:AF:SS:ID   0.017632:0.0154526:0.595411:0.00521255:102181:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0051782    ES:SE:LP:AF:SS:ID   0.0176385:0.0154938:0.59355:0.0051782:102181:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055223    ES:SE:LP:AF:SS:ID   0.0156847:0.0152621:0.516986:0.0055223:102181:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869132 ES:SE:LP:AF:SS:ID   0.000828015:0.00304308:0.104828:0.869132:102181:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127454 ES:SE:LP:AF:SS:ID   -0.00101947:0.00310507:0.129206:0.127454:102181:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868713 ES:SE:LP:AF:SS:ID   0.000603156:0.00303622:0.0744126:0.868713:102181:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867889 ES:SE:LP:AF:SS:ID   0.000163243:0.00303239:0.0190572:0.867889:102181:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868858 ES:SE:LP:AF:SS:ID   0.00057001:0.00303858:0.0699694:0.868858:102181:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868865 ES:SE:LP:AF:SS:ID   0.000567249:0.0030388:0.0696007:0.868865:102181:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868874 ES:SE:LP:AF:SS:ID   0.000564937:0.00303891:0.0692939:0.868874:102181:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869311 ES:SE:LP:AF:SS:ID   0.000763839:0.00304662:0.0958072:0.869311:102181:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100108 ES:SE:LP:AF:SS:ID   -0.00214216:0.00353438:0.264038:0.100108:102181:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00632211   ES:SE:LP:AF:SS:ID   0.0146378:0.0138569:0.536389:0.00632211:102181:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87316  ES:SE:LP:AF:SS:ID   0.000929867:0.00309188:0.117129:0.87316:102181:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862548 ES:SE:LP:AF:SS:ID   0.000447812:0.003033:0.0542253:0.862548:102181:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868016 ES:SE:LP:AF:SS:ID   0.000752152:0.00306192:0.0936887:0.868016:102181:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864817 ES:SE:LP:AF:SS:ID   0.00101299:0.00306183:0.130321:0.864817:102181:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0998789    ES:SE:LP:AF:SS:ID   -0.00202318:0.00366977:0.235508:0.0998789:102181:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870041 ES:SE:LP:AF:SS:ID   0.00113458:0.00309617:0.146281:0.870041:102181:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870041 ES:SE:LP:AF:SS:ID   0.00113468:0.00309617:0.146296:0.870041:102181:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870043 ES:SE:LP:AF:SS:ID   0.00110231:0.00309635:0.14156:0.870043:102181:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870415 ES:SE:LP:AF:SS:ID   0.00105725:0.00309794:0.134957:0.870415:102181:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127065 ES:SE:LP:AF:SS:ID   -0.00107272:0.00310056:0.137057:0.127065:102181:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106556 ES:SE:LP:AF:SS:ID   -0.00152811:0.00337276:0.186756:0.106556:102181:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853894 ES:SE:LP:AF:SS:ID   0.000249933:0.00303204:0.0295118:0.853894:102181:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00161421   ES:SE:LP:AF:SS:ID   0.0194108:0.0270601:0.324975:0.00161421:102181:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837456 ES:SE:LP:AF:SS:ID   0.00164706:0.0029846:0.235786:0.837456:102181:rs376645387