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-30670_irnt/ukb-d-30670_irnt.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-30670_irnt/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 14:50:42 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30670_irnt/ukb-d-30670_irnt.vcf.gz ...
Read summary statistics for 13586011 SNPs.
Dropped 12711 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: 0.1052 (0.0058)
Lambda GC: 1.4703
Mean Chi^2: 1.8116
Intercept: 1.0889 (0.013)
Ratio: 0.1095 (0.016)
Analysis finished at Mon Nov 25 14:53:28 2019
Total time elapsed: 2.0m:46.35s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2845,
    "mean_EFFECT": -0,
    "n": 344052,
    "n_snps": 13586011,
    "n_clumped_hits": 172,
    "n_p_sig": 22669,
    "n_mono": 0,
    "n_ns": 1251781,
    "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": 569182,
    "n_est": 345386.5451,
    "ratio_se_n": 1.0019,
    "mean_diff": -4.2315e-07,
    "ratio_diff": 0.9281,
    "sd_y_est1": 0.955,
    "sd_y_est2": 0.9569,
    "r2_sum1": 0.0388,
    "r2_sum2": 0.0425,
    "r2_sum3": 0.0424,
    "r2_sum4": 0.0424,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1052,
    "ldsc_observed_scale_h2_se": 0.0058,
    "ldsc_intercept_beta": 1.0889,
    "ldsc_intercept_se": 0.013,
    "ldsc_lambda_gc": 1.4703,
    "ldsc_mean_chisq": 1.8116,
    "ldsc_ratio": 0.1095
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 13573964 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 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051243e+00 6.184968e+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 7.902585e+07 5.591525e+07 3.02000e+02 3.293112e+07 7.013954e+07 1.148605e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.950000e-05 1.397420e-02 -1.80350e-01 -4.192700e-03 -1.580000e-05 4.185000e-03 2.171600e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.674600e-03 9.332200e-03 1.89290e-03 2.754500e-03 5.075800e-03 1.390300e-02 4.715900e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.587980e-01 3.011509e-01 0.00000e+00 1.877500e-01 4.446098e-01 7.202695e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.587975e-01 3.011511e-01 0.00000e+00 1.877466e-01 4.446163e-01 7.202723e-01 9.999997e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908095e-01 2.544043e-01 1.00000e-03 7.431400e-03 6.004000e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569182 0.9581053 NA NA NA NA NA 1.963391e-01 2.471025e-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 3.440520e+05 0.000000e+00 3.44052e+05 3.440520e+05 3.440520e+05 3.440520e+05 3.440520e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0007790 0.0040323 0.8468200 0.8468199 0.1105300 0.1894970 344052
1 693731 rs12238997 A G -0.0004825 0.0038084 0.8991901 0.8991912 0.1158200 0.1417730 344052
1 707522 rs371890604 G C 0.0021410 0.0042837 0.6172101 0.6172148 0.0972580 0.1293930 344052
1 717587 rs144155419 G A -0.0140740 0.0102270 0.1687800 0.1687717 0.0156620 0.0045926 344052
1 723329 rs189787166 A T -0.0189800 0.0301160 0.5285402 0.5285443 0.0017374 0.0003994 344052
1 730087 rs148120343 T C 0.0032458 0.0053074 0.5408303 0.5408281 0.0564400 0.0127796 344052
1 731718 rs142557973 T C 0.0002744 0.0036121 0.9394399 0.9394432 0.1217100 0.1543530 344052
1 732032 rs61770163 A C 0.0002153 0.0038543 0.9554501 0.9554536 0.1211100 0.1555510 344052
1 734349 rs141242758 T C 0.0001734 0.0036140 0.9617199 0.9617211 0.1209300 0.1525560 344052
1 740284 rs61770167 C T -0.0233730 0.0165790 0.1585901 0.1586001 0.0057558 0.0023962 344052
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0081612 0.0041743 0.0505720 0.0505705 0.056187 0.0309934 344052
23 154923374 rs111332691 T A 0.0086036 0.0045822 0.0604366 0.0604341 0.044867 0.0116556 344052
23 154925045 rs509981 C T 0.0007443 0.0022071 0.7359495 0.7359505 0.245680 0.3634440 344052
23 154925895 rs538470 C T 0.0008726 0.0022577 0.6991398 0.6991366 0.242020 0.3634440 344052
23 154927581 rs644138 G A 0.0027917 0.0020757 0.1786500 0.1786434 0.302260 0.4635760 344052
23 154929412 rs557132 C T 0.0006601 0.0022077 0.7649305 0.7649305 0.245540 0.3568210 344052
23 154929637 rs35185538 CT C 0.0014861 0.0023043 0.5189697 0.5189760 0.229780 0.3011920 344052
23 154929952 rs4012982 CAA C 0.0009467 0.0023218 0.6834803 0.6834743 0.239510 0.3165560 344052
23 154930230 rs781880 A G 0.0008360 0.0022074 0.7049105 0.7049081 0.245940 0.3618540 344052
23 154930487 rs781879 T A 0.0104140 0.0075670 0.1687699 0.1687477 0.019561 0.1263580 344052

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11053  ES:SE:LP:AF:SS:ID   0.00077895:0.0040323:0.0722089:0.11053:344052:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11582  ES:SE:LP:AF:SS:ID   -0.00048246:0.0038084:0.0461485:0.11582:344052:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097258 ES:SE:LP:AF:SS:ID   0.002141:0.0042837:0.209567:0.097258:344052:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015662 ES:SE:LP:AF:SS:ID   -0.014074:0.010227:0.772679:0.015662:344052:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017374    ES:SE:LP:AF:SS:ID   -0.01898:0.030116:0.276922:0.0017374:344052:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.05644  ES:SE:LP:AF:SS:ID   0.0032458:0.0053074:0.266939:0.05644:344052:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12171  ES:SE:LP:AF:SS:ID   0.00027441:0.0036121:0.027131:0.12171:344052:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12111  ES:SE:LP:AF:SS:ID   0.0002153:0.0038543:0.019792:0.12111:344052:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12093  ES:SE:LP:AF:SS:ID   0.00017345:0.003614:0.0169514:0.12093:344052:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057558    ES:SE:LP:AF:SS:ID   -0.023373:0.016579:0.799724:0.0057558:344052:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018603    ES:SE:LP:AF:SS:ID   -0.028442:0.03144:0.436934:0.0018603:344052:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86979  ES:SE:LP:AF:SS:ID   0.00047351:0.0035631:0.0485265:0.86979:344052:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015199    ES:SE:LP:AF:SS:ID   -0.056617:0.032389:1.09443:0.0015199:344052:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12289  ES:SE:LP:AF:SS:ID   -0.00053002:0.0035285:0.0552213:0.12289:344052:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14271  ES:SE:LP:AF:SS:ID   0.00061913:0.0034874:0.0659613:0.14271:344052:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12301  ES:SE:LP:AF:SS:ID   -0.00047758:0.0035235:0.0495475:0.12301:344052:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87095  ES:SE:LP:AF:SS:ID   0.00066223:0.0034342:0.0720704:0.87095:344052:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87551  ES:SE:LP:AF:SS:ID   0.00038282:0.0034906:0.0396862:0.87551:344052:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12859  ES:SE:LP:AF:SS:ID   -7.7265e-05:0.0034426:0.00784871:0.12859:344052:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036311 ES:SE:LP:AF:SS:ID   0.0015242:0.0062512:0.0929274:0.036311:344052:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.00051437:0.0034306:0.0551178:0.87054:344052:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   0.00053715:0.0034322:0.0576744:0.87064:344052:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.00048128:0.0034304:0.0513817:0.87054:344052:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050489    ES:SE:LP:AF:SS:ID   0.0012052:0.017597:0.0243844:0.0050489:344052:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050159    ES:SE:LP:AF:SS:ID   0.0013319:0.017644:0.0269507:0.0050159:344052:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055497    ES:SE:LP:AF:SS:ID   -0.0045599:0.017118:0.102406:0.0055497:344052:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87063  ES:SE:LP:AF:SS:ID   0.0006432:0.0034245:0.0700602:0.87063:344052:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12593  ES:SE:LP:AF:SS:ID   -0.00047156:0.003494:0.0493237:0.12593:344052:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.8702   ES:SE:LP:AF:SS:ID   0.00084335:0.0034164:0.0941933:0.8702:344052:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   0.00035163:0.0034133:0.037181:0.86948:344052:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   0.00061632:0.0034192:0.0670395:0.87035:344052:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   0.00061173:0.0034195:0.0665026:0.87035:344052:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   0.00064471:0.0034196:0.0703461:0.87036:344052:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8708   ES:SE:LP:AF:SS:ID   0.00051102:0.0034282:0.0547777:0.8708:344052:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098802 ES:SE:LP:AF:SS:ID   -0.00043221:0.0039843:0.0392344:0.098802:344052:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064355    ES:SE:LP:AF:SS:ID   0.0045942:0.015465:0.115533:0.0064355:344052:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87469  ES:SE:LP:AF:SS:ID   0.00074311:0.0034791:0.0804721:0.87469:344052:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   0.00072301:0.0034125:0.0797671:0.8641:344052:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   0.00037581:0.003445:0.0394674:0.86948:344052:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86642  ES:SE:LP:AF:SS:ID   0.00076303:0.0034457:0.0836829:0.86642:344052:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.09875  ES:SE:LP:AF:SS:ID   -0.0030315:0.0041248:0.335001:0.09875:344052:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.0007041:0.003485:0.0757776:0.8716:344052:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.00070381:0.003485:0.0757466:0.8716:344052:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.00071738:0.0034851:0.0773212:0.8716:344052:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87197  ES:SE:LP:AF:SS:ID   0.00049895:0.003487:0.0524585:0.87197:344052:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12553  ES:SE:LP:AF:SS:ID   -0.00030561:0.0034895:0.031419:0.12553:344052:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.1054   ES:SE:LP:AF:SS:ID   0.0023515:0.0037996:0.270843:0.1054:344052:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85545  ES:SE:LP:AF:SS:ID   -4.8685e-05:0.003411:0.004975:0.85545:344052:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016561    ES:SE:LP:AF:SS:ID   -0.021961:0.030192:0.330683:0.0016561:344052:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83824  ES:SE:LP:AF:SS:ID   0.0046134:0.0033589:0.770574:0.83824:344052:rs376645387