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-17469/UKB-b-17469_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17469/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17469/UKB-b-17469_data.vcf.gz ...
Read summary statistics for 9273900 SNPs.
Dropped 10113 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, 1287884 SNPs remain.
After merging with regression SNP LD, 1287884 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0013 (0.003)
Lambda GC: 1.0252
Mean Chi^2: 1.0214
Intercept: 1.0252 (0.0067)
Ratio: 1.1763 (0.311)
Analysis finished at Thu Oct 17 14:41:58 2019
Total time elapsed: 1.0m:39.56s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9486,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -4.7422e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 109339,
    "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": 1287884,
    "ldsc_nsnp_merge_regression_ld": 1287884,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0252,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0252,
    "ldsc_mean_chisq": 1.0214,
    "ldsc_ratio": 1.1776
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
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 TRUE
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 1.00000 3 58 0 9263838 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.00000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.00000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9273900 0.00000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.00000 NA NA NA NA NA NA NA 8.635987e+00 5.754464e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.00000 NA NA NA NA NA NA NA 7.880789e+07 5.631004e+07 828.0000000 3.249586e+07 6.939116e+07 1.145383e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.00000 NA NA NA NA NA NA NA -4.700000e-06 3.596000e-03 -0.0434667 -1.297000e-03 8.800000e-06 1.312600e-03 4.140550e-02 ▁▁▇▁▁
numeric SE 0 1.00000 NA NA NA NA NA NA NA 2.800300e-03 2.190600e-03 0.0009484 1.139600e-03 1.793700e-03 3.840200e-03 2.386780e-02 ▇▁▁▁▁
numeric PVAL 0 1.00000 NA NA NA NA NA NA NA 4.961516e-01 2.897203e-01 0.0000002 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.00000 NA NA NA NA NA NA NA 4.961523e-01 2.896948e-01 0.0000002 2.444467e-01 4.941800e-01 7.477112e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.00000 NA NA NA NA NA NA NA 2.144595e-01 2.578949e-01 0.0024900 1.779800e-02 9.346200e-02 3.369690e-01 9.975100e-01 ▇▂▁▁▁
numeric AF_reference 109339 0.98821 NA NA NA NA NA NA NA 2.153710e-01 2.497004e-01 0.0000000 1.517570e-02 1.118210e-01 3.366610e-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 0.0003763 0.0017483 0.8300000 0.8295678 0.623748 0.7821490 NA
1 54676 rs2462492 C T 0.0012001 0.0017366 0.4899999 0.4895407 0.399299 NA NA
1 86028 rs114608975 T C -0.0010411 0.0027680 0.7099994 0.7068348 0.103775 0.0277556 NA
1 91536 rs6702460 G T 0.0004101 0.0017112 0.8100000 0.8105742 0.456252 0.4207270 NA
1 234313 rs8179466 C T -0.0018991 0.0033782 0.5700002 0.5740025 0.074502 NA NA
1 534192 rs6680723 C T 0.0001737 0.0019554 0.9299999 0.9292173 0.241207 NA NA
1 546697 rs12025928 A G 0.0013112 0.0024256 0.5900000 0.5888149 0.913039 NA NA
1 693731 rs12238997 A G -0.0001764 0.0016300 0.9100000 0.9138073 0.116971 0.1417730 NA
1 705882 rs72631875 G A -0.0021591 0.0023839 0.3700002 0.3650862 0.067632 0.0315495 NA
1 706368 rs55727773 A G 0.0007741 0.0012071 0.5199996 0.5213555 0.514914 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0008513 0.0014619 0.5600000 0.5603678 0.137059 0.2052720 NA
22 51219387 rs9616832 T C 0.0002794 0.0019014 0.8800001 0.8831696 0.072725 0.0654952 NA
22 51219704 rs147475742 G A -0.0016886 0.0025387 0.5099998 0.5059662 0.041654 0.0473243 NA
22 51221190 rs369304721 G A 0.0000886 0.0025447 0.9699999 0.9722095 0.049100 NA NA
22 51221731 rs115055839 T C 0.0003228 0.0019028 0.8700001 0.8652988 0.072200 0.0625000 NA
22 51222100 rs114553188 G T 0.0005498 0.0022275 0.8100000 0.8050345 0.054432 0.0880591 NA
22 51223637 rs375798137 G A 0.0006628 0.0022389 0.7700005 0.7672043 0.054043 0.0788738 NA
22 51229805 rs9616985 T C 0.0001526 0.0019098 0.9400001 0.9363016 0.072056 0.0730831 NA
22 51232488 rs376461333 A G 0.0045984 0.0044714 0.2999998 0.3037679 0.020166 NA NA
22 51237063 rs3896457 T C -0.0010055 0.0011609 0.3900004 0.3864225 0.297634 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623748 ES:SE:LP:AF:ID  0.000376332:0.0017483:0.0809219:0.623748:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399299 ES:SE:LP:AF:ID  0.00120008:0.00173663:0.309804:0.399299:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103775 ES:SE:LP:AF:ID  -0.00104107:0.00276799:0.148742:0.103775:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456252 ES:SE:LP:AF:ID  0.00041014:0.00171116:0.091515:0.456252:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074502 ES:SE:LP:AF:ID  -0.0018991:0.00337818:0.244125:0.074502:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241207 ES:SE:LP:AF:ID  0.000173702:0.00195545:0.0315171:0.241207:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913039 ES:SE:LP:AF:ID  0.00131119:0.00242564:0.229148:0.913039:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116971 ES:SE:LP:AF:ID  -0.000176425:0.00162998:0.0409586:0.116971:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067632 ES:SE:LP:AF:ID  -0.0021591:0.00238386:0.431798:0.067632:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514914 ES:SE:LP:AF:ID  0.000774081:0.00120713:0.283997:0.514914:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033497 ES:SE:LP:AF:ID  0.00252383:0.00301949:0.39794:0.033497:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037198 ES:SE:LP:AF:ID  0.00214727:0.0027418:0.366532:0.037198:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037328 ES:SE:LP:AF:ID  0.00219202:0.00273099:0.376751:0.037328:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036984 ES:SE:LP:AF:ID  0.00216765:0.00275174:0.366532:0.036984:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016386 ES:SE:LP:AF:ID  -0.00465913:0.00428875:0.552842:0.016386:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037567 ES:SE:LP:AF:ID  0.00237882:0.00272012:0.420216:0.037567:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037663 ES:SE:LP:AF:ID  0.00220561:0.00271134:0.376751:0.037663:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101506 ES:SE:LP:AF:ID  -0.000630326:0.00198823:0.124939:0.101506:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958382 ES:SE:LP:AF:ID  -0.00214116:0.00261587:0.387216:0.958382:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031679 ES:SE:LP:AF:ID  -0.00504874:0.00478079:0.537602:0.031679:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052643 ES:SE:LP:AF:ID  -0.000733573:0.00385714:0.0705811:0.052643:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03714  ES:SE:LP:AF:ID  0.00242909:0.00273001:0.431798:0.03714:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037471 ES:SE:LP:AF:ID  0.00265429:0.00270557:0.481486:0.037471:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841976 ES:SE:LP:AF:ID  -0.000422372:0.00141088:0.119186:0.841976:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056088 ES:SE:LP:AF:ID  0.000340186:0.00229222:0.0555173:0.056088:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122901 ES:SE:LP:AF:ID  -0.000496395:0.001547:0.124939:0.122901:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025749 ES:SE:LP:AF:ID  0.00329377:0.00380512:0.408935:0.025749:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122123 ES:SE:LP:AF:ID  -0.000589211:0.00154775:0.154902:0.122123:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13332  ES:SE:LP:AF:ID  0.00069336:0.00152299:0.187087:0.13332:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011223 ES:SE:LP:AF:ID  0.00296051:0.00552702:0.229148:0.011223:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005839 ES:SE:LP:AF:ID  -0.00525218:0.00705924:0.337242:0.005839:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037417 ES:SE:LP:AF:ID  0.00313461:0.00267772:0.619789:0.037417:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837725 ES:SE:LP:AF:ID  -0.00112751:0.00136619:0.387216:0.837725:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837337 ES:SE:LP:AF:ID  -0.00114145:0.00136466:0.39794:0.837337:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868987 ES:SE:LP:AF:ID  -0.000199918:0.00146479:0.05061:0.868987:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130713 ES:SE:LP:AF:ID  1.03066e-05:0.00146769:0.00436481:0.130713:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037908 ES:SE:LP:AF:ID  0.0028074:0.00263388:0.537602:0.037908:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038159 ES:SE:LP:AF:ID  0.00278668:0.00261721:0.537602:0.038159:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868307 ES:SE:LP:AF:ID  -0.00011549:0.00146184:0.0268721:0.868307:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868414 ES:SE:LP:AF:ID  -6.64597e-05:0.0014625:0.0177288:0.868414:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038094 ES:SE:LP:AF:ID  0.00254797:0.00262848:0.481486:0.038094:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868303 ES:SE:LP:AF:ID  -5.83304e-05:0.00146175:0.0132283:0.868303:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00513  ES:SE:LP:AF:ID  0.00626977:0.00752994:0.387216:0.00513:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0051   ES:SE:LP:AF:ID  0.00642527:0.00754641:0.408935:0.0051:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.836819 ES:SE:LP:AF:ID  -0.000958795:0.00136111:0.318759:0.836819:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038101 ES:SE:LP:AF:ID  0.00252191:0.00263222:0.468521:0.038101:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837451 ES:SE:LP:AF:ID  -0.000949212:0.00136489:0.309804:0.837451:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013287 ES:SE:LP:AF:ID  -0.00404181:0.00487796:0.387216:0.013287:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005451 ES:SE:LP:AF:ID  0.00087305:0.00742375:0.0409586:0.005451:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.83868  ES:SE:LP:AF:ID  -0.000875949:0.00138356:0.275724:0.83868:rs3131965