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-1707_1/ukb-d-1707_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-1707_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 17:02:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1707_1/ukb-d-1707_1.vcf.gz ...
Read summary statistics for 13586569 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: 0.0093 (0.0015)
Lambda GC: 1.0705
Mean Chi^2: 1.0725
Intercept: 1.0071 (0.0065)
Ratio: 0.0977 (0.0902)
Analysis finished at Mon Nov 25 17:04:36 2019
Total time elapsed: 2.0m:7.33s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0411,
    "mean_EFFECT": -9.1562e-07,
    "n": 360913,
    "n_snps": 13586569,
    "n_clumped_hits": 2,
    "n_p_sig": 138,
    "n_mono": 0,
    "n_ns": 1251809,
    "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": 569299,
    "n_est": 362292.3296,
    "ratio_se_n": 1.0019,
    "mean_diff": -1.1129e-06,
    "ratio_diff": 1.3029,
    "sd_y_est1": 0.317,
    "sd_y_est2": 0.3176,
    "r2_sum1": 0,
    "r2_sum2": 0.0001,
    "r2_sum3": 0.0001,
    "r2_sum4": 0.0001,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0093,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0071,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0705,
    "ldsc_mean_chisq": 1.0725,
    "ldsc_ratio": 0.0979
}

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 13574522 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57084 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 9.051334e+00 6.184972e+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 7.902501e+07 5.591481e+07 3.02000e+02 3.293092e+07 7.013843e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -9.000000e-07 4.367600e-03 -6.05705e-02 -1.166400e-03 1.080000e-05 1.188300e-03 4.813700e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.135900e-03 3.025000e-03 6.13600e-04 8.928000e-04 1.645200e-03 4.506600e-03 1.521300e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.933525e-01 2.906381e-01 0.00000e+00 2.400502e-01 4.913195e-01 7.450682e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.933520e-01 2.906383e-01 0.00000e+00 2.400493e-01 4.913190e-01 7.450682e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908020e-01 2.544022e-01 1.00000e-03 7.429200e-03 6.003070e-02 2.953070e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569299 0.9580984 NA NA NA NA NA 1.963333e-01 2.471007e-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 3.609130e+05 0.000000e+00 3.60913e+05 3.609130e+05 3.609130e+05 3.609130e+05 3.609130e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0024626 0.0013069 0.0595169 0.0595146 0.1106440 0.1894970 360913
1 693731 rs12238997 A G 0.0023975 0.0012348 0.0521843 0.0521834 0.1158360 0.1417730 360913
1 707522 rs371890604 G C 0.0020960 0.0013882 0.1310741 0.1310741 0.0973058 0.1293930 360913
1 717587 rs144155419 G A 0.0044185 0.0033126 0.1822628 0.1822621 0.0156880 0.0045926 360913
1 723329 rs189787166 A T 0.0007763 0.0097742 0.9366991 0.9366990 0.0017334 0.0003994 360913
1 730087 rs148120343 T C 0.0017930 0.0017202 0.2972823 0.2972798 0.0564617 0.0127796 360913
1 731718 rs142557973 T C 0.0016452 0.0011711 0.1600601 0.1600587 0.1217420 0.1543530 360913
1 732032 rs61770163 A C 0.0022292 0.0012492 0.0743447 0.0743434 0.1211750 0.1555510 360913
1 734349 rs141242758 T C 0.0017273 0.0011717 0.1404430 0.1404427 0.1209700 0.1525560 360913
1 740284 rs61770167 C T 0.0013908 0.0053601 0.7952790 0.7952788 0.0057866 0.0023962 360913
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0012713 0.0013530 0.3474201 0.3474188 0.0561638 0.0309934 360913
23 154923374 rs111332691 T A 0.0043558 0.0014868 0.0033950 0.0033949 0.0447864 0.0116556 360913
23 154925045 rs509981 C T -0.0001065 0.0007154 0.8816380 0.8816379 0.2456310 0.3634440 360913
23 154925895 rs538470 C T -0.0000710 0.0007318 0.9226881 0.9226881 0.2419380 0.3634440 360913
23 154927581 rs644138 G A -0.0003695 0.0006728 0.5828234 0.5828231 0.3021800 0.4635760 360913
23 154929412 rs557132 C T -0.0000845 0.0007156 0.9060451 0.9060445 0.2454840 0.3568210 360913
23 154929637 rs35185538 CT C -0.0001241 0.0007468 0.8680459 0.8680459 0.2297280 0.3011920 360913
23 154929952 rs4012982 CAA C -0.0001255 0.0007527 0.8675839 0.8675839 0.2394450 0.3165560 360913
23 154930230 rs781880 A G -0.0001062 0.0007155 0.8819799 0.8819796 0.2458930 0.3618540 360913
23 154930487 rs781879 T A -0.0007529 0.0024547 0.7590511 0.7590507 0.0195630 0.1263580 360913

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110644 ES:SE:LP:AF:SS:ID   0.00246263:0.00130687:1.22536:0.110644:360913:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115836 ES:SE:LP:AF:SS:ID   0.00239749:0.00123479:1.28246:0.115836:360913:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973058    ES:SE:LP:AF:SS:ID   0.002096:0.00138819:0.882483:0.0973058:360913:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015688 ES:SE:LP:AF:SS:ID   0.00441846:0.00331263:0.739302:0.015688:360913:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173341   ES:SE:LP:AF:SS:ID   0.000776263:0.00977422:0.0283999:0.00173341:360913:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564617    ES:SE:LP:AF:SS:ID   0.00179299:0.00172025:0.526831:0.0564617:360913:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121742 ES:SE:LP:AF:SS:ID   0.00164522:0.00117108:0.795717:0.121742:360913:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121175 ES:SE:LP:AF:SS:ID   0.00222919:0.0012492:1.12875:0.121175:360913:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12097  ES:SE:LP:AF:SS:ID   0.00172727:0.00117171:0.8525:0.12097:360913:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578659   ES:SE:LP:AF:SS:ID   0.00139075:0.00536013:0.0994805:0.00578659:360913:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187801   ES:SE:LP:AF:SS:ID   0.00830332:0.0101222:0.385062:0.00187801:360913:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869737 ES:SE:LP:AF:SS:ID   -0.0021532:0.00115514:1.20536:0.869737:360913:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152869   ES:SE:LP:AF:SS:ID   -0.00549086:0.0104641:0.222017:0.00152869:360913:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122926 ES:SE:LP:AF:SS:ID   0.00233097:0.00114399:1.38097:0.122926:360913:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142717 ES:SE:LP:AF:SS:ID   0.0019074:0.00113077:1.03792:0.142717:360913:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123041 ES:SE:LP:AF:SS:ID   0.00229477:0.0011424:1.35098:0.123041:360913:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870884 ES:SE:LP:AF:SS:ID   -0.00221989:0.00111325:1.33586:0.870884:360913:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875465 ES:SE:LP:AF:SS:ID   -0.00247969:0.0011317:1.54601:0.875465:360913:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128639 ES:SE:LP:AF:SS:ID   0.00209524:0.00111603:1.21851:0.128639:360913:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363592    ES:SE:LP:AF:SS:ID   -0.00177025:0.00202482:0.417972:0.0363592:360913:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870477 ES:SE:LP:AF:SS:ID   -0.00221282:0.00111209:1.33147:0.870477:360913:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870583 ES:SE:LP:AF:SS:ID   -0.00229276:0.0011126:1.40527:0.870583:360913:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870474 ES:SE:LP:AF:SS:ID   -0.00223039:0.00111205:1.34781:0.870474:360913:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504747   ES:SE:LP:AF:SS:ID   0.00792805:0.00570689:0.783119:0.00504747:360913:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501442   ES:SE:LP:AF:SS:ID   0.00779312:0.00572216:0.761392:0.00501442:360913:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558593   ES:SE:LP:AF:SS:ID   0.00197679:0.00552976:0.142226:0.00558593:360913:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870557 ES:SE:LP:AF:SS:ID   -0.00216801:0.0011101:1.29395:0.870557:360913:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125994 ES:SE:LP:AF:SS:ID   0.00231159:0.00113269:1.38436:0.125994:360913:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87012  ES:SE:LP:AF:SS:ID   -0.00217461:0.00110742:1.30479:0.87012:360913:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869407 ES:SE:LP:AF:SS:ID   -0.00219196:0.00110641:1.32261:0.869407:360913:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870274 ES:SE:LP:AF:SS:ID   -0.0021644:0.00110838:1.29372:0.870274:360913:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87028  ES:SE:LP:AF:SS:ID   -0.00216463:0.00110846:1.2938:0.87028:360913:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870289 ES:SE:LP:AF:SS:ID   -0.00216282:0.00110849:1.29208:0.870289:360913:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870732 ES:SE:LP:AF:SS:ID   -0.00219462:0.00111131:1.31613:0.870732:360913:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988499    ES:SE:LP:AF:SS:ID   0.00158032:0.0012914:0.655498:0.0988499:360913:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647466   ES:SE:LP:AF:SS:ID   -0.000169097:0.00499577:0.0118881:0.00647466:360913:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874629 ES:SE:LP:AF:SS:ID   -0.00241782:0.00112788:1.49405:0.874629:360913:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86402  ES:SE:LP:AF:SS:ID   -0.00208431:0.00110605:1.22547:0.86402:360913:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86942  ES:SE:LP:AF:SS:ID   -0.00216001:0.00111679:1.27492:0.86942:360913:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866364 ES:SE:LP:AF:SS:ID   -0.00240733:0.00111701:1.50653:0.866364:360913:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987833    ES:SE:LP:AF:SS:ID   0.00301144:0.00133732:1.61381:0.0987833:360913:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87155  ES:SE:LP:AF:SS:ID   -0.002335:0.00112974:1.41173:0.87155:360913:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87155  ES:SE:LP:AF:SS:ID   -0.00233496:0.00112974:1.41169:0.87155:360913:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871549 ES:SE:LP:AF:SS:ID   -0.00233239:0.00112976:1.40925:0.871549:360913:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871923 ES:SE:LP:AF:SS:ID   -0.00235076:0.00113041:1.42521:0.871923:360913:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12557  ES:SE:LP:AF:SS:ID   0.00227509:0.00113128:1.35341:0.12557:360913:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105432 ES:SE:LP:AF:SS:ID   0.00167654:0.00123159:0.760886:0.105432:360913:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855372 ES:SE:LP:AF:SS:ID   -0.0018548:0.00110563:1.02952:0.855372:360913:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165425   ES:SE:LP:AF:SS:ID   0.000625886:0.00979523:0.02271:0.00165425:360913:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838371 ES:SE:LP:AF:SS:ID   1.60861e-05:0.00108929:0.00514724:0.838371:360913:rs376645387