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-680_2/ukb-d-680_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-680_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 17:15:34 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-680_2/ukb-d-680_2.vcf.gz ...
Read summary statistics for 13586422 SNPs.
Dropped 12710 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: 0.0112 (0.0014)
Lambda GC: 1.0748
Mean Chi^2: 1.0791
Intercept: 1.0005 (0.0068)
Ratio: 0.0066 (0.0856)
Analysis finished at Mon Nov 25 17:17:53 2019
Total time elapsed: 2.0m:18.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0459,
    "mean_EFFECT": -0,
    "n": 356340,
    "n_snps": 13586422,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1251804,
    "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": 569270,
    "n_est": 357694.7159,
    "ratio_se_n": 1.0019,
    "mean_diff": -0,
    "ratio_diff": 71.9928,
    "sd_y_est1": 0.4231,
    "sd_y_est2": 0.424,
    "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": 0.0112,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0005,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0748,
    "ldsc_mean_chisq": 1.0791,
    "ldsc_ratio": 0.0063
}

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 13574376 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57082 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33338 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051366e+00 6.184982e+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 7.902493e+07 5.591491e+07 3.02000e+02 3.293086e+07 7.013794e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.030000e-05 5.887400e-03 -7.31876e-02 -1.596600e-03 -8.600000e-06 1.574500e-03 7.091240e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.212200e-03 4.063100e-03 8.24300e-04 1.199200e-03 2.209900e-03 6.053500e-03 2.040570e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.927621e-01 2.907560e-01 2.00000e-07 2.393321e-01 4.903227e-01 7.448486e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.927616e-01 2.907563e-01 2.00000e-07 2.393315e-01 4.903223e-01 7.448492e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908044e-01 2.544032e-01 1.00000e-03 7.429700e-03 6.003140e-02 2.953050e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569270 0.9581001 NA NA NA NA NA 1.963353e-01 2.471016e-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 3.563400e+05 0.000000e+00 3.56340e+05 3.563400e+05 3.563400e+05 3.563400e+05 3.563400e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0013289 0.0017555 0.4490575 0.4490571 0.1106480 0.1894970 356340
1 693731 rs12238997 A G -0.0012441 0.0016592 0.4533702 0.4533700 0.1157970 0.1417730 356340
1 707522 rs371890604 G C 0.0006221 0.0018651 0.7387134 0.7387127 0.0972849 0.1293930 356340
1 717587 rs144155419 G A -0.0075783 0.0044504 0.0885952 0.0885950 0.0156800 0.0045926 356340
1 723329 rs189787166 A T -0.0167908 0.0130784 0.1991939 0.1991919 0.0017455 0.0003994 356340
1 730087 rs148120343 T C -0.0004968 0.0023111 0.8298061 0.8298061 0.0564590 0.0127796 356340
1 731718 rs142557973 T C -0.0004841 0.0015734 0.7583278 0.7583280 0.1217310 0.1543530 356340
1 732032 rs61770163 A C 0.0003109 0.0016784 0.8530380 0.8530382 0.1211470 0.1555510 356340
1 734349 rs141242758 T C -0.0004528 0.0015742 0.7736116 0.7736128 0.1209580 0.1525560 356340
1 740284 rs61770167 C T 0.0037971 0.0071870 0.5972690 0.5972687 0.0058056 0.0023962 356340
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0017255 0.0018166 0.3421787 0.3421769 0.0562156 0.0309934 356340
23 154923374 rs111332691 T A 0.0013902 0.0019974 0.4864128 0.4864133 0.0448027 0.0116556 356340
23 154925045 rs509981 C T -0.0006870 0.0009614 0.4748331 0.4748320 0.2454610 0.3634440 356340
23 154925895 rs538470 C T -0.0004947 0.0009834 0.6149248 0.6149245 0.2417790 0.3634440 356340
23 154927581 rs644138 G A -0.0009997 0.0009040 0.2687652 0.2687637 0.3020610 0.4635760 356340
23 154929412 rs557132 C T -0.0006537 0.0009617 0.4966621 0.4966614 0.2453120 0.3568210 356340
23 154929637 rs35185538 CT C -0.0002145 0.0010036 0.8307929 0.8307920 0.2295890 0.3011920 356340
23 154929952 rs4012982 CAA C -0.0004368 0.0010114 0.6657957 0.6657952 0.2392680 0.3165560 356340
23 154930230 rs781880 A G -0.0005910 0.0009615 0.5387509 0.5387505 0.2457230 0.3618540 356340
23 154930487 rs781879 T A 0.0002469 0.0032999 0.9403530 0.9403527 0.0195351 0.1263580 356340

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110648 ES:SE:LP:AF:SS:ID   -0.0013289:0.00175551:0.347698:0.110648:356340:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115797 ES:SE:LP:AF:SS:ID   -0.00124406:0.00165917:0.343547:0.115797:356340:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972849    ES:SE:LP:AF:SS:ID   0.00062213:0.00186513:0.131524:0.0972849:356340:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.01568  ES:SE:LP:AF:SS:ID   -0.00757834:0.00445037:1.05259:0.01568:356340:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00174548   ES:SE:LP:AF:SS:ID   -0.0167908:0.0130784:0.700724:0.00174548:356340:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056459 ES:SE:LP:AF:SS:ID   -0.000496778:0.00231113:0.0810234:0.056459:356340:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121731 ES:SE:LP:AF:SS:ID   -0.000484087:0.00157336:0.120143:0.121731:356340:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121147 ES:SE:LP:AF:SS:ID   0.000310905:0.00167836:0.0690316:0.121147:356340:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120958 ES:SE:LP:AF:SS:ID   -0.000452831:0.00157423:0.111477:0.120958:356340:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0058056    ES:SE:LP:AF:SS:ID   0.00379714:0.00718703:0.22383:0.0058056:356340:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187615   ES:SE:LP:AF:SS:ID   0.000147048:0.0136061:0.00376116:0.00187615:356340:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869751 ES:SE:LP:AF:SS:ID   0.000412524:0.00155199:0.102158:0.869751:356340:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152269   ES:SE:LP:AF:SS:ID   -0.00790184:0.0140855:0.240479:0.00152269:356340:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122921 ES:SE:LP:AF:SS:ID   -0.000209943:0.00153693:0.0499527:0.122921:356340:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142704 ES:SE:LP:AF:SS:ID   -0.000300821:0.0015192:0.0741544:0.142704:356340:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123036 ES:SE:LP:AF:SS:ID   -0.000252422:0.00153479:0.0607983:0.123036:356340:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870892 ES:SE:LP:AF:SS:ID   0.000369344:0.00149559:0.0942349:0.870892:356340:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875468 ES:SE:LP:AF:SS:ID   7.89636e-05:0.0015204:0.0183716:0.875468:356340:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   -0.00036814:0.00149932:0.0936434:0.128631:356340:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363599    ES:SE:LP:AF:SS:ID   -0.00160702:0.0027198:0.256009:0.0363599:356340:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870484 ES:SE:LP:AF:SS:ID   0.000344892:0.00149403:0.0875473:0.870484:356340:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870586 ES:SE:LP:AF:SS:ID   0.00030756:0.00149468:0.0772896:0.870586:356340:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870482 ES:SE:LP:AF:SS:ID   0.000364668:0.00149397:0.0930409:0.870482:356340:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504061   ES:SE:LP:AF:SS:ID   -0.00154922:0.00767188:0.0757378:0.00504061:356340:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500754   ES:SE:LP:AF:SS:ID   -0.00170569:0.00769243:0.0837993:0.00500754:356340:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00555675   ES:SE:LP:AF:SS:ID   -0.000893365:0.0074486:0.0435756:0.00555675:356340:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870565 ES:SE:LP:AF:SS:ID   0.000385224:0.00149134:0.0989942:0.870565:356340:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125983 ES:SE:LP:AF:SS:ID   -0.000452598:0.00152176:0.115688:0.125983:356340:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870131 ES:SE:LP:AF:SS:ID   0.000301571:0.00148777:0.0760466:0.870131:356340:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869417 ES:SE:LP:AF:SS:ID   0.000368928:0.0014864:0.0947558:0.869417:356340:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   0.000410561:0.00148906:0.106369:0.870287:356340:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870293 ES:SE:LP:AF:SS:ID   0.000407016:0.00148917:0.105347:0.870293:356340:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870301 ES:SE:LP:AF:SS:ID   0.000413483:0.00148922:0.107193:0.870301:356340:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870742 ES:SE:LP:AF:SS:ID   0.000455607:0.00149299:0.119049:0.870742:356340:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988331    ES:SE:LP:AF:SS:ID   0.000363591:0.0017351:0.0788241:0.0988331:356340:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00645051   ES:SE:LP:AF:SS:ID   -0.00657124:0.00672464:0.483496:0.00645051:356340:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87464  ES:SE:LP:AF:SS:ID   0.0003977:0.00151529:0.100744:0.87464:356340:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864041 ES:SE:LP:AF:SS:ID   0.000601856:0.00148595:0.164022:0.864041:356340:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869434 ES:SE:LP:AF:SS:ID   0.000202256:0.00150041:0.0492609:0.869434:356340:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866374 ES:SE:LP:AF:SS:ID   0.000165872:0.00150067:0.0400114:0.866374:356340:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098777 ES:SE:LP:AF:SS:ID   -0.00149485:0.00179677:0.392085:0.098777:356340:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000254222:0.00151781:0.0619899:0.87156:356340:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000254265:0.00151781:0.0620009:0.87156:356340:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000261072:0.00151783:0.0637704:0.87156:356340:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871936 ES:SE:LP:AF:SS:ID   0.000278756:0.0015187:0.0683555:0.871936:356340:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12556  ES:SE:LP:AF:SS:ID   -0.000428908:0.00151986:0.109138:0.12556:356340:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10543  ES:SE:LP:AF:SS:ID   0.000715404:0.00165455:0.176877:0.10543:356340:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855374 ES:SE:LP:AF:SS:ID   0.000210837:0.00148533:0.0520162:0.855374:356340:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00166613   ES:SE:LP:AF:SS:ID   -0.0133901:0.0131064:0.51293:0.00166613:356340:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838431 ES:SE:LP:AF:SS:ID   -0.0001963:0.00146363:0.0489983:0.838431:356340:rs376645387