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-19842/UKB-b-19842_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19842/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19842/UKB-b-19842_data.vcf.gz ...
Read summary statistics for 8736325 SNPs.
Dropped 7681 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, 1286105 SNPs remain.
After merging with regression SNP LD, 1286105 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0548 (0.0049)
Lambda GC: 1.1164
Mean Chi^2: 1.1259
Intercept: 1.0024 (0.0068)
Ratio: 0.019 (0.0542)
Analysis finished at Thu Oct 17 14:43:26 2019
Total time elapsed: 1.0m:31.86s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9466,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 785,
    "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": 85366,
    "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": 1286105,
    "ldsc_nsnp_merge_regression_ld": 1286105,
    "ldsc_observed_scale_h2_beta": 0.0548,
    "ldsc_observed_scale_h2_se": 0.0049,
    "ldsc_intercept_beta": 1.0024,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.1164,
    "ldsc_mean_chisq": 1.1259,
    "ldsc_ratio": 0.0191
}

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 8728680 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 8736325 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 8.649657e+00 5.761018e+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 7.877378e+07 5.635935e+07 828.0000000 3.239802e+07 6.931323e+07 1.145626e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.140000e-05 6.254300e-03 -0.0685669 -2.643800e-03 -2.000000e-05 2.588600e-03 5.834980e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.045600e-03 3.513300e-03 0.0019508 2.308800e-03 3.441300e-03 6.856600e-03 3.393390e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.870370e-01 2.923124e-01 0.0000000 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 4.870376e-01 2.922859e-01 0.0000000 2.311100e-01 4.827117e-01 7.402179e-01 9.999993e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.264105e-01 2.592251e-01 0.0048950 2.374100e-02 1.101000e-01 3.580000e-01 9.951050e-01 ▇▂▁▁▁
numeric AF_reference 85366 0.9902286 NA NA NA NA NA NA NA 2.262578e-01 2.511943e-01 0.0000000 2.136580e-02 1.269970e-01 3.552320e-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 -0.0049878 0.0036008 0.1700000 0.1659984 0.624829 0.7821490 NA
1 54676 rs2462492 C T -0.0023152 0.0035573 0.5199996 0.5151473 0.400589 NA NA
1 86028 rs114608975 T C 0.0073926 0.0056735 0.1900002 0.1925688 0.103768 0.0277556 NA
1 91536 rs6702460 G T -0.0040569 0.0035001 0.2500000 0.2464320 0.457708 0.4207270 NA
1 234313 rs8179466 C T -0.0010018 0.0068664 0.8800001 0.8840044 0.074903 NA NA
1 534192 rs6680723 C T 0.0034131 0.0040185 0.4000000 0.3956848 0.240603 NA NA
1 546697 rs12025928 A G -0.0043111 0.0049924 0.3900004 0.3878367 0.913450 NA NA
1 693731 rs12238997 A G -0.0017898 0.0033668 0.5900000 0.5949928 0.115696 0.1417730 NA
1 705882 rs72631875 G A 0.0062237 0.0049288 0.2099999 0.2066932 0.066992 0.0315495 NA
1 706368 rs55727773 A G -0.0030977 0.0024893 0.2099999 0.2133494 0.515448 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0026936 0.0030022 0.3700002 0.3696157 0.138244 0.2052720 NA
22 51219387 rs9616832 T C -0.0010930 0.0038908 0.7800007 0.7787662 0.073823 0.0654952 NA
22 51219704 rs147475742 G A 0.0056926 0.0052176 0.2800000 0.2752559 0.041938 0.0473243 NA
22 51221190 rs369304721 G A -0.0006981 0.0052186 0.8900000 0.8935799 0.049605 NA NA
22 51221731 rs115055839 T C -0.0009052 0.0038935 0.8200001 0.8161549 0.073285 0.0625000 NA
22 51222100 rs114553188 G T -0.0053009 0.0045814 0.2500000 0.2472538 0.054537 0.0880591 NA
22 51223637 rs375798137 G A -0.0055073 0.0046037 0.2300001 0.2315880 0.054163 0.0788738 NA
22 51229805 rs9616985 T C -0.0007257 0.0039073 0.8499999 0.8526579 0.073145 0.0730831 NA
22 51232488 rs376461333 A G -0.0108050 0.0092316 0.2399999 0.2418270 0.020065 NA NA
22 51237063 rs3896457 T C -0.0001507 0.0023894 0.9500000 0.9497106 0.298924 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624829 ES:SE:LP:AF:ID  -0.0049878:0.00360084:0.769551:0.624829:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400589 ES:SE:LP:AF:ID  -0.00231524:0.00355729:0.283997:0.400589:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103768 ES:SE:LP:AF:ID  0.00739263:0.00567347:0.721246:0.103768:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457708 ES:SE:LP:AF:ID  -0.00405687:0.00350014:0.60206:0.457708:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074903 ES:SE:LP:AF:ID  -0.00100178:0.00686645:0.0555173:0.074903:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240603 ES:SE:LP:AF:ID  0.0034131:0.00401847:0.39794:0.240603:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91345  ES:SE:LP:AF:ID  -0.00431113:0.00499235:0.408935:0.91345:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115696 ES:SE:LP:AF:ID  -0.00178983:0.00336678:0.229148:0.115696:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066992 ES:SE:LP:AF:ID  0.00622366:0.00492881:0.677781:0.066992:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515448 ES:SE:LP:AF:ID  -0.00309768:0.00248928:0.677781:0.515448:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032967 ES:SE:LP:AF:ID  -0.0035251:0.00626903:0.244125:0.032967:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036588 ES:SE:LP:AF:ID  -0.00372313:0.00569548:0.29243:0.036588:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  -0.0032193:0.00567153:0.244125:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036397 ES:SE:LP:AF:ID  -0.00331253:0.00571439:0.251812:0.036397:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016486 ES:SE:LP:AF:ID  -0.00876405:0.00873663:0.49485:0.016486:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036953 ES:SE:LP:AF:ID  -0.00302311:0.00564884:0.229148:0.036953:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  -0.00345912:0.00563006:0.267606:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101315 ES:SE:LP:AF:ID  -0.00104602:0.00409774:0.09691:0.101315:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959059 ES:SE:LP:AF:ID  0.0024698:0.00543007:0.187087:0.959059:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031554 ES:SE:LP:AF:ID  -0.00257571:0.00979517:0.102373:0.031554:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053159 ES:SE:LP:AF:ID  0.00367837:0.00786517:0.19382:0.053159:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036579 ES:SE:LP:AF:ID  -0.00294013:0.00566673:0.221849:0.036579:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036824 ES:SE:LP:AF:ID  -0.00394475:0.00562086:0.318759:0.036824:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843656 ES:SE:LP:AF:ID  0.00173862:0.00291135:0.259637:0.843656:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055239 ES:SE:LP:AF:ID  -0.000675443:0.00474437:0.05061:0.055239:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121958 ES:SE:LP:AF:ID  -0.00072673:0.00318602:0.0861861:0.121958:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025761 ES:SE:LP:AF:ID  -0.0152234:0.00782642:1.284:0.025761:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121209 ES:SE:LP:AF:ID  -0.000723056:0.00318713:0.0861861:0.121209:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13188  ES:SE:LP:AF:ID  -0.00126484:0.00314706:0.161151:0.13188:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.010989 ES:SE:LP:AF:ID  0.0103969:0.0115039:0.431798:0.010989:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005888 ES:SE:LP:AF:ID  0.0301984:0.014536:1.42022:0.005888:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036812 ES:SE:LP:AF:ID  -0.00379987:0.00555725:0.309804:0.036812:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839396 ES:SE:LP:AF:ID  0.00170277:0.00282164:0.259637:0.839396:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.839044 ES:SE:LP:AF:ID  0.00169829:0.00281861:0.259637:0.839044:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.870033 ES:SE:LP:AF:ID  0.000163301:0.00302186:0.0177288:0.870033:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12962  ES:SE:LP:AF:ID  7.32529e-05:0.00302781:0.00877392:0.12962:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037285 ES:SE:LP:AF:ID  -0.0039161:0.00546588:0.327902:0.037285:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037543 ES:SE:LP:AF:ID  -0.00385544:0.00542957:0.318759:0.037543:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869363 ES:SE:LP:AF:ID  8.15202e-06:0.00301579:-0:0.869363:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869463 ES:SE:LP:AF:ID  -0.000121728:0.00301674:0.0132283:0.869463:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037495 ES:SE:LP:AF:ID  -0.00416282:0.00545408:0.346787:0.037495:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869372 ES:SE:LP:AF:ID  -6.66609e-05:0.00301592:0.00877392:0.869372:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005028 ES:SE:LP:AF:ID  0.02817:0.0156166:1.14874:0.005028:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.004997 ES:SE:LP:AF:ID  0.0281964:0.0156485:1.14267:0.004997:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838477 ES:SE:LP:AF:ID  0.00148138:0.00281081:0.221849:0.838477:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037506 ES:SE:LP:AF:ID  -0.00452765:0.00546238:0.387216:0.037506:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839081 ES:SE:LP:AF:ID  0.00140204:0.0028185:0.207608:0.839081:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013877 ES:SE:LP:AF:ID  0.00757083:0.00977221:0.356547:0.013877:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005516 ES:SE:LP:AF:ID  -0.0108991:0.0152062:0.327902:0.005516:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.840151 ES:SE:LP:AF:ID  0.00131532:0.00285595:0.187087:0.840151:rs3131965