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/public/UKB-b-10093/UKB-b-10093_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10093/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10093/UKB-b-10093_data.vcf.gz ...
Read summary statistics for 8819038 SNPs.
Dropped 7987 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1286444 SNPs remain.
After merging with regression SNP LD, 1286444 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0547 (0.0028)
Lambda GC: 1.4055
Mean Chi^2: 1.5253
Intercept: 1.0197 (0.009)
Ratio: 0.0376 (0.0172)
Analysis finished at Thu Oct 17 14:41:54 2019
Total time elapsed: 1.0m:36.46s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9469,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 41,
    "n_p_sig": 3356,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 87403,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1286444,
    "ldsc_nsnp_merge_regression_ld": 1286444,
    "ldsc_observed_scale_h2_beta": 0.0547,
    "ldsc_observed_scale_h2_se": 0.0028,
    "ldsc_intercept_beta": 1.0197,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.4055,
    "ldsc_mean_chisq": 1.5253,
    "ldsc_ratio": 0.0375
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 8811088 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 8819038 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.648648e+00 5.760073e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.877063e+07 5.634450e+07 828.0000000 3.240567e+07 6.932413e+07 1.145476e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.040000e-05 2.658600e-03 -0.0252161 -1.148500e-03 1.190000e-05 1.179500e-03 2.900850e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.030400e-03 1.434200e-03 0.0007714 9.141000e-04 1.374000e-03 2.768500e-03 1.372040e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.573575e-01 3.005745e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.573585e-01 3.005516e-01 0.0000000 1.861279e-01 4.417406e-01 7.181815e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.244532e-01 2.590143e-01 0.0044640 2.268600e-02 1.074220e-01 3.546660e-01 9.955360e-01 ▇▂▁▁▁
numeric AF_reference 87403 0.9900893 NA NA NA NA NA NA NA 2.244252e-01 2.509611e-01 0.0000000 2.016770e-02 1.244010e-01 3.522360e-01 1.000000e+00 ▇▂▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0002414 0.0014184 0.8600001 0.8648584 0.623759 0.7821490 NA
1 54676 rs2462492 C T -0.0026633 0.0014051 0.0580003 0.0580381 0.400480 NA NA
1 86028 rs114608975 T C -0.0002652 0.0022472 0.9100000 0.9060689 0.103553 0.0277556 NA
1 91536 rs6702460 G T -0.0007491 0.0013837 0.5900000 0.5882534 0.456897 0.4207270 NA
1 234313 rs8179466 C T 0.0003449 0.0027306 0.9000000 0.8994951 0.074467 NA NA
1 534192 rs6680723 C T -0.0021138 0.0015802 0.1800002 0.1810184 0.240982 NA NA
1 546697 rs12025928 A G -0.0011376 0.0019716 0.5600000 0.5639268 0.913491 NA NA
1 693731 rs12238997 A G -0.0031820 0.0013251 0.0160000 0.0163338 0.116269 0.1417730 NA
1 705882 rs72631875 G A 0.0039836 0.0019408 0.0400000 0.0401193 0.067304 0.0315495 NA
1 706368 rs55727773 A G 0.0008207 0.0009813 0.4000000 0.4029896 0.515786 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0011497 0.0011849 0.3300000 0.3319297 0.137887 0.2052720 NA
22 51219387 rs9616832 T C 0.0004953 0.0015381 0.7499995 0.7474499 0.073718 0.0654952 NA
22 51219704 rs147475742 G A 0.0004455 0.0020620 0.8300000 0.8289659 0.041886 0.0473243 NA
22 51221190 rs369304721 G A 0.0013714 0.0020573 0.5099998 0.5050223 0.049724 NA NA
22 51221731 rs115055839 T C 0.0005426 0.0015391 0.7199992 0.7244213 0.073203 0.0625000 NA
22 51222100 rs114553188 G T -0.0026759 0.0018120 0.1400000 0.1397472 0.054449 0.0880591 NA
22 51223637 rs375798137 G A -0.0027243 0.0018207 0.1299999 0.1345710 0.054084 0.0788738 NA
22 51229805 rs9616985 T C 0.0003460 0.0015446 0.8200001 0.8227334 0.073033 0.0730831 NA
22 51232488 rs376461333 A G -0.0037347 0.0036378 0.2999998 0.3045940 0.020039 NA NA
22 51237063 rs3896457 T C -0.0000786 0.0009440 0.9299999 0.9336566 0.298203 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623759 ES:SE:LP:AF:ID  -0.000241405:0.00141842:0.0655015:0.623759:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40048  ES:SE:LP:AF:ID  -0.00266326:0.00140511:1.23657:0.40048:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103553 ES:SE:LP:AF:ID  -0.000265165:0.00224719:0.0409586:0.103553:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456897 ES:SE:LP:AF:ID  -0.000749092:0.0013837:0.229148:0.456897:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074467 ES:SE:LP:AF:ID  0.000344875:0.00273062:0.0457575:0.074467:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240982 ES:SE:LP:AF:ID  -0.00211377:0.00158024:0.744727:0.240982:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913491 ES:SE:LP:AF:ID  -0.00113765:0.0019716:0.251812:0.913491:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116269 ES:SE:LP:AF:ID  -0.00318196:0.00132506:1.79588:0.116269:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067304 ES:SE:LP:AF:ID  0.00398361:0.00194084:1.39794:0.067304:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515786 ES:SE:LP:AF:ID  0.000820687:0.000981338:0.39794:0.515786:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032989 ES:SE:LP:AF:ID  0.000760809:0.00247465:0.119186:0.032989:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036607 ES:SE:LP:AF:ID  0.00121851:0.00224781:0.229148:0.036607:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036721 ES:SE:LP:AF:ID  0.00120959:0.00223936:0.229148:0.036721:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036414 ES:SE:LP:AF:ID  0.00136099:0.00225575:0.259637:0.036414:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016378 ES:SE:LP:AF:ID  0.00178634:0.00347497:0.21467:0.016378:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036956 ES:SE:LP:AF:ID  0.00157222:0.00223061:0.318759:0.036956:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037051 ES:SE:LP:AF:ID  0.00141879:0.00222294:0.283997:0.037051:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101215 ES:SE:LP:AF:ID  -0.00193604:0.00161911:0.638272:0.101215:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959156 ES:SE:LP:AF:ID  -0.00136076:0.00214518:0.275724:0.959156:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031462 ES:SE:LP:AF:ID  0.000162105:0.00388716:0.0132283:0.031462:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053293 ES:SE:LP:AF:ID  0.000566215:0.00309257:0.0705811:0.053293:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036574 ES:SE:LP:AF:ID  0.00123115:0.00223727:0.236572:0.036574:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036887 ES:SE:LP:AF:ID  0.00142889:0.00221697:0.283997:0.036887:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843338 ES:SE:LP:AF:ID  0.002233:0.00114855:1.284:0.843338:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055884 ES:SE:LP:AF:ID  -0.00387372:0.0018593:1.4318:0.055884:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122227 ES:SE:LP:AF:ID  -0.00290766:0.00125715:1.67778:0.122227:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025714 ES:SE:LP:AF:ID  0.000913854:0.00308971:0.113509:0.025714:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121469 ES:SE:LP:AF:ID  -0.00294557:0.00125768:1.72125:0.121469:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132296 ES:SE:LP:AF:ID  -0.00289024:0.00123915:1.69897:0.132296:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011105 ES:SE:LP:AF:ID  -0.000545942:0.0045109:0.0457575:0.011105:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.00572  ES:SE:LP:AF:ID  -0.0107009:0.00580296:1.18709:0.00572:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  0.00135232:0.00219445:0.267606:0.036808:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839035 ES:SE:LP:AF:ID  0.00188316:0.00111209:1.04576:0.839035:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838671 ES:SE:LP:AF:ID  0.00197212:0.00111093:1.11919:0.838671:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869862 ES:SE:LP:AF:ID  0.0023621:0.00119216:1.31876:0.869862:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129786 ES:SE:LP:AF:ID  -0.00247617:0.00119464:1.42022:0.129786:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037314 ES:SE:LP:AF:ID  0.00147307:0.00215736:0.309804:0.037314:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037556 ES:SE:LP:AF:ID  0.00158472:0.00214378:0.337242:0.037556:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869217 ES:SE:LP:AF:ID  0.00237885:0.00118988:1.33724:0.869217:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869315 ES:SE:LP:AF:ID  0.00241982:0.00119035:1.37675:0.869315:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037516 ES:SE:LP:AF:ID  0.00174195:0.00215297:0.376751:0.037516:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869219 ES:SE:LP:AF:ID  0.00235963:0.00118986:1.3279:0.869219:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005143 ES:SE:LP:AF:ID  -0.000908191:0.00609208:0.0555173:0.005143:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00511  ES:SE:LP:AF:ID  -0.00109929:0.00610773:0.0655015:0.00511:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838125 ES:SE:LP:AF:ID  0.00186407:0.00110786:1.03621:0.838125:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037528 ES:SE:LP:AF:ID  0.00170043:0.00215603:0.366532:0.037528:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838754 ES:SE:LP:AF:ID  0.00187188:0.00111096:1.03621:0.838754:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013765 ES:SE:LP:AF:ID  -0.00021604:0.00387819:0.0177288:0.013765:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005543 ES:SE:LP:AF:ID  0.00032161:0.00598254:0.0177288:0.005543:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839852 ES:SE:LP:AF:ID  0.00200812:0.00112595:1.12494:0.839852:rs3131965