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-11862/UKB-b-11862_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11862/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11862/UKB-b-11862_data.vcf.gz ...
Read summary statistics for 4047808 SNPs.
Dropped 773 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, 961483 SNPs remain.
After merging with regression SNP LD, 961483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0026 (0.0012)
Lambda GC: 1.0437
Mean Chi^2: 1.0443
Intercept: 1.0182 (0.0089)
Ratio: 0.4113 (0.2002)
Analysis finished at Thu Oct 17 14:42:04 2019
Total time elapsed: 54.75s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8774,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.0895e-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": 33066,
    "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": 961483,
    "ldsc_nsnp_merge_regression_ld": 961483,
    "ldsc_observed_scale_h2_beta": 0.0026,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0182,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.0437,
    "ldsc_mean_chisq": 1.0443,
    "ldsc_ratio": 0.4108
}

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 4047040 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 4047808 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 8.658247e+00 5.766848e+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 7.857025e+07 5.674406e+07 828.0000000 3.163155e+07 6.891253e+07 1.146845e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.100000e-06 2.038000e-04 -0.0013742 -1.331000e-04 7.000000e-07 1.349000e-04 1.258300e-03 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.973000e-04 2.780000e-05 0.0001620 1.732000e-04 1.881000e-04 2.163000e-04 5.924000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.927921e-01 2.905116e-01 0.0000004 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 4.927922e-01 2.904859e-01 0.0000004 2.393862e-01 4.902290e-01 7.441638e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.922677e-01 2.143295e-01 0.1151700 2.055200e-01 3.437060e-01 5.506270e-01 8.848300e-01 ▇▅▃▃▂
numeric AF_reference 33066 0.9918311 NA NA NA NA NA NA NA 3.814313e-01 2.179737e-01 0.0000000 2.020770e-01 3.402560e-01 5.385380e-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 -0.0001389 0.0002981 0.6400000 0.6413108 0.623763 0.782149 NA
1 54676 rs2462492 C T -0.0001947 0.0002953 0.5099998 0.5096124 0.400401 NA NA
1 91536 rs6702460 G T -0.0003268 0.0002908 0.2599998 0.2610735 0.456851 0.420727 NA
1 534192 rs6680723 C T 0.0004602 0.0003321 0.1700000 0.1658854 0.240960 NA NA
1 693731 rs12238997 A G 0.0001936 0.0002783 0.4899999 0.4867275 0.116325 0.141773 NA
1 706368 rs55727773 A G -0.0004081 0.0002062 0.0479999 0.0477561 0.515650 0.275160 NA
1 729679 rs4951859 C G -0.0002360 0.0002412 0.3300000 0.3279434 0.843212 0.639976 NA
1 731718 rs142557973 T C 0.0002710 0.0002640 0.2999998 0.3046862 0.122307 0.154353 NA
1 734349 rs141242758 T C 0.0002698 0.0002641 0.3100002 0.3071344 0.121549 0.152556 NA
1 736289 rs79010578 T A 0.0000834 0.0002603 0.7499995 0.7486785 0.132330 0.139577 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0000195 0.0002056 0.9199999 0.9244079 0.254557 0.0984425 NA
22 51208537 rs72619593 G A -0.0002929 0.0002748 0.2900000 0.2864714 0.120739 0.1142170 NA
22 51210289 rs112565862 C T 0.0001469 0.0002737 0.5900000 0.5913812 0.129955 0.1018370 NA
22 51211106 rs9628250 T C -0.0000284 0.0002039 0.8900000 0.8890335 0.271547 0.1671330 NA
22 51211392 rs3888396 T C 0.0001384 0.0002713 0.6100002 0.6098132 0.132635 0.1641370 NA
22 51212875 rs2238837 A C -0.0002320 0.0001937 0.2300001 0.2311333 0.331455 0.3724040 NA
22 51213613 rs34726907 C T -0.0001816 0.0002552 0.4799997 0.4767726 0.127816 0.1727240 NA
22 51216564 rs9616970 T C -0.0001795 0.0002541 0.4799997 0.4800136 0.128330 0.1563500 NA
22 51219006 rs28729663 G A -0.0000698 0.0002487 0.7800007 0.7789565 0.137953 0.2052720 NA
22 51237063 rs3896457 T C -0.0001559 0.0001983 0.4299995 0.4317591 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -0.000138867:0.000298083:0.19382:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000194737:0.000295306:0.29243:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -0.000326784:0.00029077:0.585027:0.456851:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  0.000460183:0.000332131:0.769551:0.24096:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  0.000193594:0.000278343:0.309804:0.116325:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.000408146:0.000206183:1.31876:0.51565:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  -0.000235977:0.00024122:0.481486:0.843212:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122307 ES:SE:LP:AF:ID  0.000271016:0.000264036:0.522879:0.122307:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  0.000269761:0.000264147:0.508638:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  8.34093e-05:0.000260343:0.124939:0.13233:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  -0.000174375:0.000233604:0.337242:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  -0.000177022:0.000233353:0.346787:0.83858:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  -0.000243597:0.000250397:0.481486:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129871 ES:SE:LP:AF:ID  0.000233695:0.00025091:0.455932:0.129871:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  -0.000240337:0.000249907:0.468521:0.869123:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  -0.000245692:0.000250006:0.481486:0.869221:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  -0.00024136:0.000249902:0.481486:0.869126:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  -0.000199962:0.000232705:0.408935:0.838033:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  -0.00021358:0.000233359:0.443698:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  -0.000226556:0.000236515:0.468521:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869405 ES:SE:LP:AF:ID  -0.000240345:0.000249613:0.468521:0.869405:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  -0.000221191:0.000248985:0.431798:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867905 ES:SE:LP:AF:ID  -0.00021809:0.000248507:0.420216:0.867905:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  -0.00022873:0.000249188:0.443698:0.869095:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.000229473:0.000249208:0.443698:0.869104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  -0.000230042:0.000249213:0.443698:0.869112:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869589 ES:SE:LP:AF:ID  -0.000237849:0.000249897:0.468521:0.869589:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  -0.000223063:0.000232264:0.468521:0.838313:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  -0.000221964:0.000232428:0.468521:0.838434:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862261 ES:SE:LP:AF:ID  -0.000237176:0.000248312:0.468521:0.862261:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -0.0002762:0.00024173:0.60206:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761304 ES:SE:LP:AF:ID  -0.000247898:0.000197295:0.677781:0.761304:rs2977608
1   769223  rs60320384  C   G   .   PASS    AF=0.129576 ES:SE:LP:AF:ID  0.000212927:0.00025076:0.39794:0.129576:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868911 ES:SE:LP:AF:ID  -0.000242694:0.00024942:0.481486:0.868911:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129677 ES:SE:LP:AF:ID  0.000236024:0.000250598:0.455932:0.129677:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868921 ES:SE:LP:AF:ID  -0.000245868:0.000249425:0.49485:0.868921:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  -5.52473e-05:0.000220381:0.09691:0.26539:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870044 ES:SE:LP:AF:ID  -0.000265092:0.000249934:0.537602:0.870044:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.128576 ES:SE:LP:AF:ID  0.000254596:0.000250921:0.508638:0.128576:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128873 ES:SE:LP:AF:ID  0.000244916:0.000250495:0.481486:0.128873:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868786 ES:SE:LP:AF:ID  -0.000278266:0.000249268:0.585027:0.868786:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129513 ES:SE:LP:AF:ID  0.000263894:0.000250414:0.537602:0.129513:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868539 ES:SE:LP:AF:ID  -0.000257683:0.000249209:0.522879:0.868539:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.86848  ES:SE:LP:AF:ID  -0.000259126:0.000249365:0.522879:0.86848:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.86078  ES:SE:LP:AF:ID  -0.000251901:0.000249194:0.508638:0.86078:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.128461 ES:SE:LP:AF:ID  0.000245864:0.000251764:0.481486:0.128461:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861493 ES:SE:LP:AF:ID  -0.00019002:0.000249358:0.346787:0.861493:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869229 ES:SE:LP:AF:ID  -0.000232252:0.000250276:0.455932:0.869229:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.127879 ES:SE:LP:AF:ID  0.00024301:0.000253377:0.468521:0.127879:rs111818025
1   795988  rs59380221  C   T   .   PASS    AF=0.143051 ES:SE:LP:AF:ID  -0.000105726:0.000258468:0.167491:0.143051:rs59380221