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-188/UKB-b-188_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-188/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-188/UKB-b-188_data.vcf.gz ...
Read summary statistics for 9329032 SNPs.
Dropped 10447 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, 1288015 SNPs remain.
After merging with regression SNP LD, 1288015 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0283 (0.0037)
Lambda GC: 1.1194
Mean Chi^2: 1.1183
Intercept: 1.034 (0.0077)
Ratio: 0.2875 (0.0647)
Analysis finished at Thu Oct 17 14:42:02 2019
Total time elapsed: 1.0m:43.09s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9488,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0001,
    "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": 113948,
    "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": 1288015,
    "ldsc_nsnp_merge_regression_ld": 1288015,
    "ldsc_observed_scale_h2_beta": 0.0283,
    "ldsc_observed_scale_h2_se": 0.0037,
    "ldsc_intercept_beta": 1.034,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.1194,
    "ldsc_mean_chisq": 1.1183,
    "ldsc_ratio": 0.2874
}

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 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 9318637 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 9329032 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 8.634409e+00 5.753904e+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 7.881295e+07 5.630860e+07 828.0000000 3.250566e+07 6.939273e+07 1.145421e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 8.000000e-05 9.067500e-03 -0.1560370 -3.265600e-03 6.040000e-05 3.402800e-03 1.118970e-01 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.948500e-03 5.518800e-03 0.0023164 2.788300e-03 4.414300e-03 9.521300e-03 8.074460e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.861472e-01 2.921671e-01 0.0000002 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.861476e-01 2.921420e-01 0.0000002 2.292695e-01 4.810863e-01 7.392678e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.133187e-01 2.577605e-01 0.0023010 1.729100e-02 9.185650e-02 3.348710e-01 9.976990e-01 ▇▂▁▁▁
numeric AF_reference 113948 0.9877857 NA NA NA NA NA NA NA 2.143968e-01 2.495412e-01 0.0000000 1.457670e-02 1.104230e-01 3.348640e-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 -0.0100053 0.0042684 0.0189998 0.0190753 0.623766 0.7821490 NA
1 54676 rs2462492 C T -0.0011533 0.0042416 0.7899998 0.7856976 0.399244 NA NA
1 86028 rs114608975 T C -0.0036507 0.0067583 0.5900000 0.5890721 0.103791 0.0277556 NA
1 91536 rs6702460 G T -0.0028878 0.0041782 0.4899999 0.4894633 0.456237 0.4207270 NA
1 234313 rs8179466 C T -0.0119111 0.0082492 0.1499999 0.1487619 0.074498 NA NA
1 534192 rs6680723 C T -0.0032896 0.0047770 0.4899999 0.4910458 0.241173 NA NA
1 546697 rs12025928 A G -0.0034783 0.0059240 0.5600000 0.5570964 0.913012 NA NA
1 693731 rs12238997 A G 0.0022526 0.0039798 0.5700002 0.5713886 0.117055 0.1417730 NA
1 705882 rs72631875 G A 0.0041004 0.0058234 0.4799997 0.4813598 0.067617 0.0315495 NA
1 706368 rs55727773 A G 0.0019081 0.0029478 0.5199996 0.5174343 0.514890 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0005976 0.0035706 0.8700001 0.8670895 0.137079 0.2052720 NA
22 51219387 rs9616832 T C -0.0019851 0.0046461 0.6700003 0.6691926 0.072660 0.0654952 NA
22 51219704 rs147475742 G A 0.0005716 0.0062023 0.9299999 0.9265712 0.041633 0.0473243 NA
22 51221190 rs369304721 G A -0.0033443 0.0062180 0.5900000 0.5906844 0.049048 NA NA
22 51221731 rs115055839 T C -0.0019150 0.0046496 0.6800001 0.6804370 0.072138 0.0625000 NA
22 51222100 rs114553188 G T 0.0046742 0.0054384 0.3900004 0.3900742 0.054499 0.0880591 NA
22 51223637 rs375798137 G A 0.0045254 0.0054664 0.4100001 0.4077511 0.054109 0.0788738 NA
22 51229805 rs9616985 T C -0.0016793 0.0046666 0.7199992 0.7189610 0.071994 0.0730831 NA
22 51232488 rs376461333 A G 0.0109820 0.0109215 0.3100002 0.3146371 0.020176 NA NA
22 51237063 rs3896457 T C 0.0021070 0.0028361 0.4600002 0.4575419 0.297611 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623766 ES:SE:LP:AF:ID  -0.0100053:0.00426837:1.72125:0.623766:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399244 ES:SE:LP:AF:ID  -0.00115329:0.00424157:0.102373:0.399244:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103791 ES:SE:LP:AF:ID  -0.00365069:0.00675827:0.229148:0.103791:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456237 ES:SE:LP:AF:ID  -0.00288783:0.00417822:0.309804:0.456237:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074498 ES:SE:LP:AF:ID  -0.0119111:0.00824915:0.823909:0.074498:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241173 ES:SE:LP:AF:ID  -0.00328965:0.00477698:0.309804:0.241173:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913012 ES:SE:LP:AF:ID  -0.00347834:0.00592401:0.251812:0.913012:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117055 ES:SE:LP:AF:ID  0.00225258:0.00397977:0.244125:0.117055:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067617 ES:SE:LP:AF:ID  0.00410037:0.00582342:0.318759:0.067617:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51489  ES:SE:LP:AF:ID  0.00190814:0.00294782:0.283997:0.51489:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033537 ES:SE:LP:AF:ID  -0.00456143:0.00737077:0.267606:0.033537:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037242 ES:SE:LP:AF:ID  -0.0046507:0.00669281:0.309804:0.037242:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037372 ES:SE:LP:AF:ID  -0.00443187:0.00666647:0.29243:0.037372:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037024 ES:SE:LP:AF:ID  -0.00483051:0.00671753:0.327902:0.037024:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016409 ES:SE:LP:AF:ID  -0.00325069:0.0104651:0.119186:0.016409:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037614 ES:SE:LP:AF:ID  -0.00485157:0.00663955:0.337242:0.037614:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037708 ES:SE:LP:AF:ID  -0.00491045:0.00661831:0.337242:0.037708:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101511 ES:SE:LP:AF:ID  -0.00240444:0.00485692:0.207608:0.101511:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958335 ES:SE:LP:AF:ID  0.00283573:0.00638559:0.180456:0.958335:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031687 ES:SE:LP:AF:ID  0.0121963:0.0116712:0.522879:0.031687:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052576 ES:SE:LP:AF:ID  0.0026074:0.00943177:0.107905:0.052576:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03718  ES:SE:LP:AF:ID  -0.00477628:0.00666427:0.327902:0.03718:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037518 ES:SE:LP:AF:ID  -0.00499321:0.0066042:0.346787:0.037518:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841878 ES:SE:LP:AF:ID  -0.000324609:0.00344581:0.0362122:0.841878:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056117 ES:SE:LP:AF:ID  0.00341886:0.00559744:0.267606:0.056117:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122961 ES:SE:LP:AF:ID  0.000355255:0.00377785:0.0315171:0.122961:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025743 ES:SE:LP:AF:ID  0.00462583:0.00929296:0.207608:0.025743:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122183 ES:SE:LP:AF:ID  0.000634321:0.00377968:0.0604807:0.122183:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133396 ES:SE:LP:AF:ID  -0.000570868:0.00371966:0.0555173:0.133396:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01122  ES:SE:LP:AF:ID  -0.0114902:0.0135:0.408935:0.01122:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005854 ES:SE:LP:AF:ID  -0.0117533:0.0172184:0.309804:0.005854:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037456 ES:SE:LP:AF:ID  -0.00407881:0.0065369:0.275724:0.037456:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837594 ES:SE:LP:AF:ID  -0.00132386:0.00333643:0.161151:0.837594:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83721  ES:SE:LP:AF:ID  -0.00166451:0.00333278:0.207608:0.83721:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868893 ES:SE:LP:AF:ID  -0.00244989:0.00357696:0.309804:0.868893:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130797 ES:SE:LP:AF:ID  0.00253307:0.00358423:0.318759:0.130797:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037946 ES:SE:LP:AF:ID  -0.00391986:0.00642991:0.267606:0.037946:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.0382   ES:SE:LP:AF:ID  -0.00359471:0.00638886:0.244125:0.0382:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868216 ES:SE:LP:AF:ID  -0.00275263:0.00356986:0.356547:0.868216:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868324 ES:SE:LP:AF:ID  -0.00287001:0.00357146:0.376751:0.868324:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038129 ES:SE:LP:AF:ID  -0.00347:0.00641693:0.229148:0.038129:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868212 ES:SE:LP:AF:ID  -0.00278755:0.00356963:0.366532:0.868212:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005136 ES:SE:LP:AF:ID  0.0406451:0.0183829:1.56864:0.005136:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005106 ES:SE:LP:AF:ID  0.0408833:0.0184236:1.58503:0.005106:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.836692 ES:SE:LP:AF:ID  -0.00129778:0.00332411:0.154902:0.836692:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038139 ES:SE:LP:AF:ID  -0.0040841:0.00642585:0.275724:0.038139:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837324 ES:SE:LP:AF:ID  -0.0013064:0.00333334:0.154902:0.837324:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013268 ES:SE:LP:AF:ID  0.0131811:0.011922:0.568636:0.013268:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005465 ES:SE:LP:AF:ID  0.0156446:0.0181033:0.408935:0.005465:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838552 ES:SE:LP:AF:ID  -0.00171501:0.0033789:0.21467:0.838552:rs3131965