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-15784/UKB-b-15784_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15784/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15784/UKB-b-15784_data.vcf.gz ...
Read summary statistics for 8849604 SNPs.
Dropped 8092 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, 1286574 SNPs remain.
After merging with regression SNP LD, 1286574 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.023 (0.0017)
Lambda GC: 1.2746
Mean Chi^2: 1.2997
Intercept: 1.0929 (0.0084)
Ratio: 0.3098 (0.0281)
Analysis finished at Thu Oct 17 14:45:57 2019
Total time elapsed: 1.0m:31.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9471,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 58,
    "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": 88234,
    "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": 1286574,
    "ldsc_nsnp_merge_regression_ld": 1286574,
    "ldsc_observed_scale_h2_beta": 0.023,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.0929,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.2746,
    "ldsc_mean_chisq": 1.2997,
    "ldsc_ratio": 0.31
}

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 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 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 8841550 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 8849604 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 8.647867e+00 5.760025e+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 7.877786e+07 5.634471e+07 828.0000000 3.241074e+07 6.933296e+07 1.145558e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.040000e-05 2.644200e-03 -0.0335987 -1.101200e-03 2.600000e-06 1.114200e-03 2.577460e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.018400e-03 1.433700e-03 0.0007615 9.033000e-04 1.361700e-03 2.755100e-03 1.766280e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.667602e-01 2.971905e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.667610e-01 2.971658e-01 0.0000000 2.004821e-01 4.549960e-01 7.236734e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.237397e-01 2.589270e-01 0.0043140 2.231900e-02 1.064530e-01 3.534450e-01 9.956860e-01 ▇▂▁▁▁
numeric AF_reference 88234 0.9900296 NA NA NA NA NA NA NA 2.237629e-01 2.508692e-01 0.0000000 1.976840e-02 1.236020e-01 3.512380e-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 -0.0007427 0.0014007 0.5999997 0.5959565 0.623763 0.7821490 NA
1 54676 rs2462492 C T 0.0019730 0.0013879 0.1600000 0.1551353 0.400408 NA NA
1 86028 rs114608975 T C 0.0005921 0.0022189 0.7899998 0.7895988 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0011976 0.0013664 0.3800004 0.3807745 0.456871 0.4207270 NA
1 234313 rs8179466 C T 0.0000783 0.0026940 0.9800000 0.9768061 0.074514 NA NA
1 534192 rs6680723 C T 0.0034203 0.0015608 0.0280001 0.0284241 0.240951 NA NA
1 546697 rs12025928 A G 0.0033057 0.0019473 0.0899995 0.0895816 0.913476 NA NA
1 693731 rs12238997 A G 0.0008092 0.0013081 0.5400003 0.5361492 0.116326 0.1417730 NA
1 705882 rs72631875 G A -0.0047308 0.0019168 0.0140001 0.0135826 0.067296 0.0315495 NA
1 706368 rs55727773 A G 0.0003472 0.0009690 0.7199992 0.7201209 0.515683 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0006219 0.0011694 0.5900000 0.5948475 0.137967 0.2052720 NA
22 51219387 rs9616832 T C 0.0001557 0.0015180 0.9199999 0.9183054 0.073738 0.0654952 NA
22 51219704 rs147475742 G A -0.0013920 0.0020341 0.4899999 0.4937748 0.041954 0.0473243 NA
22 51221190 rs369304721 G A 0.0003391 0.0020308 0.8700001 0.8673784 0.049729 NA NA
22 51221731 rs115055839 T C 0.0002297 0.0015189 0.8800001 0.8797781 0.073228 0.0625000 NA
22 51222100 rs114553188 G T -0.0019289 0.0017880 0.2800000 0.2806730 0.054478 0.0880591 NA
22 51223637 rs375798137 G A -0.0020251 0.0017967 0.2599998 0.2596897 0.054107 0.0788738 NA
22 51229805 rs9616985 T C 0.0002576 0.0015244 0.8700001 0.8658216 0.073065 0.0730831 NA
22 51232488 rs376461333 A G -0.0054780 0.0035910 0.1299999 0.1271358 0.020049 NA NA
22 51237063 rs3896457 T C 0.0022202 0.0009324 0.0170000 0.0172614 0.297986 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -0.000742685:0.0014007:0.221849:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400408 ES:SE:LP:AF:ID  0.00197303:0.00138787:0.79588:0.400408:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  0.000592062:0.00221886:0.102373:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456871 ES:SE:LP:AF:ID  0.0011976:0.00136639:0.420216:0.456871:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074514 ES:SE:LP:AF:ID  7.83229e-05:0.00269398:0.00877392:0.074514:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240951 ES:SE:LP:AF:ID  0.00342031:0.0015608:1.55284:0.240951:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  0.00330572:0.00194728:1.04576:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116326 ES:SE:LP:AF:ID  0.000809233:0.00130807:0.267606:0.116326:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067296 ES:SE:LP:AF:ID  -0.00473081:0.00191677:1.85387:0.067296:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515683 ES:SE:LP:AF:ID  0.000347185:0.000968986:0.142668:0.515683:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033013 ES:SE:LP:AF:ID  0.00087359:0.00244238:0.142668:0.033013:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036627 ES:SE:LP:AF:ID  0.000700041:0.00221863:0.124939:0.036627:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036744 ES:SE:LP:AF:ID  0.000618771:0.00221022:0.107905:0.036744:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036442 ES:SE:LP:AF:ID  0.000874156:0.00222622:0.161151:0.036442:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016415 ES:SE:LP:AF:ID  -0.000965432:0.00342704:0.107905:0.016415:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036981 ES:SE:LP:AF:ID  0.000642754:0.00220153:0.113509:0.036981:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037078 ES:SE:LP:AF:ID  0.000763081:0.00219396:0.136677:0.037078:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101198 ES:SE:LP:AF:ID  0.00140418:0.00159875:0.420216:0.101198:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959087 ES:SE:LP:AF:ID  0.000164605:0.00211596:0.0268721:0.959087:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031439 ES:SE:LP:AF:ID  0.00186126:0.00384328:0.200659:0.031439:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053262 ES:SE:LP:AF:ID  -0.00366744:0.00305558:0.638272:0.053262:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036596 ES:SE:LP:AF:ID  0.000927375:0.00220819:0.173925:0.036596:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036912 ES:SE:LP:AF:ID  0.000820659:0.0021881:0.148742:0.036912:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843195 ES:SE:LP:AF:ID  -0.000262404:0.00113358:0.0861861:0.843195:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055908 ES:SE:LP:AF:ID  0.00102889:0.00183554:0.236572:0.055908:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122313 ES:SE:LP:AF:ID  0.000631339:0.00124084:0.21467:0.122313:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025712 ES:SE:LP:AF:ID  0.0049353:0.00305233:0.958607:0.025712:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121555 ES:SE:LP:AF:ID  0.000725606:0.00124136:0.251812:0.121555:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  0.00109668:0.00122348:0.431798:0.132336:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011129 ES:SE:LP:AF:ID  -0.00421268:0.00444928:0.468521:0.011129:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005698 ES:SE:LP:AF:ID  -0.00364765:0.00574295:0.275724:0.005698:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036827 ES:SE:LP:AF:ID  0.000623449:0.00216595:0.113509:0.036827:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838934 ES:SE:LP:AF:ID  -0.00050659:0.0010978:0.19382:0.838934:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838562 ES:SE:LP:AF:ID  -0.000531665:0.00109662:0.200659:0.838562:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869772 ES:SE:LP:AF:ID  -0.000568151:0.00117674:0.200659:0.869772:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129879 ES:SE:LP:AF:ID  0.000534554:0.00117914:0.187087:0.129879:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03734  ES:SE:LP:AF:ID  0.00070612:0.00212918:0.130768:0.03734:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037583 ES:SE:LP:AF:ID  0.000778034:0.00211574:0.148742:0.037583:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  -0.000585622:0.00117443:0.207608:0.869114:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869212 ES:SE:LP:AF:ID  -0.000580039:0.00117489:0.207608:0.869212:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037542 ES:SE:LP:AF:ID  0.00074947:0.00212486:0.142668:0.037542:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.000634895:0.00117441:0.229148:0.869117:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  0.00148829:0.00603102:0.091515:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  0.00150861:0.0060468:0.09691:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838014 ES:SE:LP:AF:ID  -0.000561794:0.00109356:0.21467:0.838014:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037554 ES:SE:LP:AF:ID  0.000717574:0.00212787:0.130768:0.037554:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838645 ES:SE:LP:AF:ID  -0.000578571:0.00109664:0.221849:0.838645:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013774 ES:SE:LP:AF:ID  -0.000583:0.00382789:0.0555173:0.013774:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005544 ES:SE:LP:AF:ID  -0.00148212:0.00590787:0.09691:0.005544:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839758 ES:SE:LP:AF:ID  -0.000580475:0.00111147:0.221849:0.839758:rs3131965