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-5759/UKB-b-5759_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5759/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:34 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5759/UKB-b-5759_data.vcf.gz ...
Read summary statistics for 4055998 SNPs.
Dropped 776 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, 963069 SNPs remain.
After merging with regression SNP LD, 963069 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0007 (0.0014)
Lambda GC: 1.0459
Mean Chi^2: 1.0426
Intercept: 1.0356 (0.0091)
Ratio: 0.8361 (0.2131)
Analysis finished at Thu Oct 17 14:46:21 2019
Total time elapsed: 46.69s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8777,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -2.0055e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 33138,
    "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": 963069,
    "ldsc_nsnp_merge_regression_ld": 963069,
    "ldsc_observed_scale_h2_beta": 0.0007,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0356,
    "ldsc_intercept_se": 0.0091,
    "ldsc_lambda_gc": 1.0459,
    "ldsc_mean_chisq": 1.0426,
    "ldsc_ratio": 0.8357
}

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 1.0000000 3 58 0 4055227 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 4055998 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 8.658236e+00 5.767312e+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 7.857050e+07 5.674320e+07 828.0000000 3.163513e+07 6.891285e+07 1.146896e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.000000e-07 2.126000e-04 -0.0013787 -1.408000e-04 -3.000000e-07 1.400000e-04 1.667800e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.062000e-04 2.910000e-05 0.0001692 1.810000e-04 1.966000e-04 2.262000e-04 6.188000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.930204e-01 2.904958e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.930186e-01 2.904687e-01 0.0000000 2.398064e-01 4.901331e-01 7.445996e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.919278e-01 2.145852e-01 0.1146790 2.049670e-01 3.432130e-01 5.504000e-01 8.853210e-01 ▇▅▃▃▂
numeric AF_reference 33138 0.9918299 NA NA NA NA NA NA NA 3.811480e-01 2.181453e-01 0.0000000 2.016770e-01 3.398560e-01 5.383390e-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 -0.0004120 0.0003114 0.1900002 0.1857713 0.623752 0.782149 NA
1 54676 rs2462492 C T 0.0000709 0.0003085 0.8200001 0.8181640 0.400422 NA NA
1 91536 rs6702460 G T 0.0000352 0.0003037 0.9100000 0.9076654 0.456862 0.420727 NA
1 534192 rs6680723 C T 0.0005576 0.0003470 0.1100001 0.1080340 0.240916 NA NA
1 693731 rs12238997 A G 0.0001264 0.0002908 0.6600001 0.6638913 0.116369 0.141773 NA
1 706368 rs55727773 A G 0.0000363 0.0002154 0.8700001 0.8661700 0.515709 0.275160 NA
1 729679 rs4951859 C G -0.0000175 0.0002520 0.9400001 0.9445591 0.843121 0.639976 NA
1 731718 rs142557973 T C 0.0001896 0.0002758 0.4899999 0.4919083 0.122361 0.154353 NA
1 734349 rs141242758 T C 0.0001570 0.0002759 0.5700002 0.5693386 0.121604 0.152556 NA
1 736289 rs79010578 T A -0.0000977 0.0002719 0.7199992 0.7193882 0.132419 0.139577 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G 0.0002479 0.0002148 0.2500000 0.2484928 0.254379 0.0984425 NA
22 51208537 rs72619593 G A 0.0001853 0.0002871 0.5199996 0.5187178 0.120826 0.1142170 NA
22 51210289 rs112565862 C T 0.0002237 0.0002860 0.4299995 0.4342807 0.129938 0.1018370 NA
22 51211106 rs9628250 T C 0.0001248 0.0002130 0.5600000 0.5578702 0.271363 0.1671330 NA
22 51211392 rs3888396 T C 0.0002088 0.0002835 0.4600002 0.4612894 0.132626 0.1641370 NA
22 51212875 rs2238837 A C 0.0001094 0.0002024 0.5900000 0.5887651 0.331617 0.3724040 NA
22 51213613 rs34726907 C T -0.0000519 0.0002665 0.8499999 0.8457301 0.127894 0.1727240 NA
22 51216564 rs9616970 T C -0.0000404 0.0002654 0.8800001 0.8791017 0.128416 0.1563500 NA
22 51219006 rs28729663 G A -0.0000255 0.0002597 0.9199999 0.9216933 0.138022 0.2052720 NA
22 51237063 rs3896457 T C 0.0000502 0.0002071 0.8100000 0.8084657 0.298160 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623752 ES:SE:LP:AF:ID  -0.00041198:0.000311353:0.721246:0.623752:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400422 ES:SE:LP:AF:ID  7.09245e-05:0.000308492:0.0861861:0.400422:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456862 ES:SE:LP:AF:ID  3.52231e-05:0.00030369:0.0409586:0.456862:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240916 ES:SE:LP:AF:ID  0.000557621:0.000346975:0.958607:0.240916:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116369 ES:SE:LP:AF:ID  0.000126368:0.000290804:0.180456:0.116369:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515709 ES:SE:LP:AF:ID  3.63017e-05:0.000215408:0.0604807:0.515709:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843121 ES:SE:LP:AF:ID  -1.75245e-05:0.000252003:0.0268721:0.843121:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122361 ES:SE:LP:AF:ID  0.000189564:0.000275819:0.309804:0.122361:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121604 ES:SE:LP:AF:ID  0.000157013:0.000275933:0.244125:0.121604:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132419 ES:SE:LP:AF:ID  -9.76995e-05:0.000271934:0.142668:0.132419:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838812 ES:SE:LP:AF:ID  -1.67382e-05:0.000243988:0.0222764:0.838812:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838432 ES:SE:LP:AF:ID  -3.54951e-05:0.000243715:0.0555173:0.838432:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869687 ES:SE:LP:AF:ID  -0.000147161:0.000261526:0.244125:0.869687:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129978 ES:SE:LP:AF:ID  0.000141095:0.000262045:0.229148:0.129978:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869026 ES:SE:LP:AF:ID  -0.000162543:0.000261006:0.275724:0.869026:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869127 ES:SE:LP:AF:ID  -0.000168256:0.000261112:0.283997:0.869127:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86903  ES:SE:LP:AF:ID  -0.000172615:0.000261001:0.29243:0.86903:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837883 ES:SE:LP:AF:ID  -2.17524e-05:0.000243038:0.0315171:0.837883:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838514 ES:SE:LP:AF:ID  -1.7694e-05:0.000243721:0.0268721:0.838514:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839634 ES:SE:LP:AF:ID  -2.80476e-05:0.000247031:0.0409586:0.839634:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869317 ES:SE:LP:AF:ID  -0.000143444:0.000260715:0.236572:0.869317:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86887  ES:SE:LP:AF:ID  -0.000144441:0.000260071:0.236572:0.86887:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867812 ES:SE:LP:AF:ID  -0.000153776:0.000259556:0.259637:0.867812:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869008 ES:SE:LP:AF:ID  -0.000154251:0.000260279:0.259637:0.869008:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869017 ES:SE:LP:AF:ID  -0.000153567:0.000260299:0.251812:0.869017:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869024 ES:SE:LP:AF:ID  -0.000154601:0.000260305:0.259637:0.869024:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:ID  -0.00015202:0.00026101:0.251812:0.8695:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.83817  ES:SE:LP:AF:ID  -5.08627e-06:0.000242589:0.00877392:0.83817:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838289 ES:SE:LP:AF:ID  -8.09512e-06:0.00024276:0.0132283:0.838289:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862169 ES:SE:LP:AF:ID  -0.000136588:0.000259373:0.221849:0.862169:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706642 ES:SE:LP:AF:ID  -0.000183429:0.00025251:0.327902:0.706642:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761325 ES:SE:LP:AF:ID  7.33141e-05:0.000206198:0.142668:0.761325:rs2977608
1   769223  rs60320384  C   G   .   PASS    AF=0.129665 ES:SE:LP:AF:ID  0.000154376:0.000261922:0.251812:0.129665:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868831 ES:SE:LP:AF:ID  -0.000154407:0.000260526:0.259637:0.868831:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129765 ES:SE:LP:AF:ID  0.000143218:0.000261752:0.236572:0.129765:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868841 ES:SE:LP:AF:ID  -0.000146487:0.000260531:0.244125:0.868841:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265278 ES:SE:LP:AF:ID  -0.000259609:0.00023028:0.585027:0.265278:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869987 ES:SE:LP:AF:ID  -0.000181248:0.00026108:0.309804:0.869987:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.128634 ES:SE:LP:AF:ID  0.000164067:0.00026211:0.275724:0.128634:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128929 ES:SE:LP:AF:ID  0.000152336:0.00026167:0.251812:0.128929:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868726 ES:SE:LP:AF:ID  -0.000157746:0.000260385:0.267606:0.868726:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129578 ES:SE:LP:AF:ID  0.000153938:0.000261583:0.251812:0.129578:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868481 ES:SE:LP:AF:ID  -0.000165032:0.000260325:0.275724:0.868481:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868423 ES:SE:LP:AF:ID  -0.000160708:0.000260488:0.267606:0.868423:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.860712 ES:SE:LP:AF:ID  -0.000195845:0.000260292:0.346787:0.860712:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.128525 ES:SE:LP:AF:ID  0.000153977:0.000262996:0.251812:0.128525:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861442 ES:SE:LP:AF:ID  -0.000162762:0.000260482:0.275724:0.861442:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869173 ES:SE:LP:AF:ID  -0.000183749:0.000261441:0.318759:0.869173:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.12794  ES:SE:LP:AF:ID  0.000153492:0.000264688:0.251812:0.12794:rs111818025
1   795988  rs59380221  C   T   .   PASS    AF=0.143074 ES:SE:LP:AF:ID  0.000354109:0.00027002:0.721246:0.143074:rs59380221