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-14679/UKB-b-14679_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14679/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:45 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14679/UKB-b-14679_data.vcf.gz ...
Read summary statistics for 4055909 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, 963066 SNPs remain.
After merging with regression SNP LD, 963066 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0005 (0.0011)
Lambda GC: 1.1968
Mean Chi^2: 1.1927
Intercept: 1.198 (0.0083)
Ratio: 1.0271 (0.0433)
Analysis finished at Thu Oct 17 14:44:36 2019
Total time elapsed: 50.79s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8777,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 1.4657e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 5,
    "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": 33137,
    "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": 963066,
    "ldsc_nsnp_merge_regression_ld": 963066,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.198,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.1968,
    "ldsc_mean_chisq": 1.1927,
    "ldsc_ratio": 1.0275
}

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 4055138 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 4055909 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 8.658337e+00 5.767253e+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 7.857038e+07 5.674286e+07 828.0000000 3.163601e+07 6.891306e+07 1.146873e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.500000e-06 2.176000e-04 -0.0012313 -1.426000e-04 -1.000000e-07 1.447000e-04 1.346200e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.971000e-04 2.780000e-05 0.0001617 1.730000e-04 1.879000e-04 2.162000e-04 5.914000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.711452e-01 2.953555e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.711449e-01 2.953303e-01 0.0000000 2.091870e-01 4.594839e-01 7.267211e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.919273e-01 2.145808e-01 0.1146790 2.049730e-01 3.432050e-01 5.504050e-01 8.853210e-01 ▇▅▃▃▂
numeric AF_reference 33137 0.9918299 NA NA NA NA NA NA NA 3.811457e-01 2.181416e-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 -0.0001675 0.0002976 0.5700002 0.5735215 0.623769 0.782149 NA
1 54676 rs2462492 C T 0.0003845 0.0002948 0.1900002 0.1920864 0.400407 NA NA
1 91536 rs6702460 G T -0.0002491 0.0002902 0.3900004 0.3907556 0.456839 0.420727 NA
1 534192 rs6680723 C T -0.0001787 0.0003315 0.5900000 0.5898048 0.240960 NA NA
1 693731 rs12238997 A G -0.0003332 0.0002778 0.2300001 0.2304842 0.116323 0.141773 NA
1 706368 rs55727773 A G 0.0002335 0.0002058 0.2599998 0.2565822 0.515616 0.275160 NA
1 729679 rs4951859 C G 0.0002745 0.0002408 0.2500000 0.2541750 0.843203 0.639976 NA
1 731718 rs142557973 T C -0.0003743 0.0002635 0.1600000 0.1554888 0.122313 0.154353 NA
1 734349 rs141242758 T C -0.0003687 0.0002637 0.1600000 0.1619861 0.121556 0.152556 NA
1 736289 rs79010578 T A -0.0002598 0.0002599 0.3200000 0.3174409 0.132337 0.139577 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0000049 0.0002054 0.9800000 0.9808412 0.254600 0.0984425 NA
22 51208537 rs72619593 G A -0.0002624 0.0002745 0.3400001 0.3390967 0.120734 0.1142170 NA
22 51210289 rs112565862 C T -0.0000509 0.0002734 0.8499999 0.8522870 0.129971 0.1018370 NA
22 51211106 rs9628250 T C -0.0000666 0.0002036 0.7400005 0.7435910 0.271575 0.1671330 NA
22 51211392 rs3888396 T C -0.0000697 0.0002709 0.8000000 0.7970822 0.132649 0.1641370 NA
22 51212875 rs2238837 A C -0.0000187 0.0001935 0.9199999 0.9229766 0.331413 0.3724040 NA
22 51213613 rs34726907 C T 0.0003027 0.0002549 0.2300001 0.2349994 0.127798 0.1727240 NA
22 51216564 rs9616970 T C 0.0002880 0.0002538 0.2599998 0.2565721 0.128313 0.1563500 NA
22 51219006 rs28729663 G A 0.0002600 0.0002484 0.2999998 0.2952498 0.137926 0.2052720 NA
22 51237063 rs3896457 T C -0.0002263 0.0001981 0.2500000 0.2532132 0.297938 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623769 ES:SE:LP:AF:ID  -0.000167489:0.000297561:0.244125:0.623769:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  0.000384493:0.000294759:0.721246:0.400407:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456839 ES:SE:LP:AF:ID  -0.000249097:0.000290239:0.408935:0.456839:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -0.000178719:0.000331502:0.229148:0.24096:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116323 ES:SE:LP:AF:ID  -0.000333153:0.000277833:0.638272:0.116323:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515616 ES:SE:LP:AF:ID  0.000233478:0.000205797:0.585027:0.515616:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843203 ES:SE:LP:AF:ID  0.000274541:0.000240769:0.60206:0.843203:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122313 ES:SE:LP:AF:ID  -0.000374343:0.000263546:0.79588:0.122313:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121556 ES:SE:LP:AF:ID  -0.000368704:0.000263657:0.79588:0.121556:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132337 ES:SE:LP:AF:ID  -0.000259787:0.000259857:0.49485:0.132337:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838942 ES:SE:LP:AF:ID  0.000328564:0.000233163:0.79588:0.838942:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838571 ES:SE:LP:AF:ID  0.000319959:0.000232912:0.769551:0.838571:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869774 ES:SE:LP:AF:ID  0.000434863:0.000249929:1.08619:0.869774:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129879 ES:SE:LP:AF:ID  -0.000431162:0.000250438:1.07058:0.129879:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  0.000433408:0.000249438:1.08619:0.869115:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869213 ES:SE:LP:AF:ID  0.000436897:0.000249538:1.09691:0.869213:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  0.000433255:0.000249434:1.08619:0.869118:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838022 ES:SE:LP:AF:ID  0.000319106:0.000232264:0.769551:0.838022:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838652 ES:SE:LP:AF:ID  0.000340569:0.000232915:0.853872:0.838652:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839764 ES:SE:LP:AF:ID  0.000316682:0.000236065:0.744727:0.839764:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869398 ES:SE:LP:AF:ID  0.000426156:0.000249146:1.06048:0.869398:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868944 ES:SE:LP:AF:ID  0.000435811:0.000248518:1.10237:0.868944:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867895 ES:SE:LP:AF:ID  0.000424835:0.00024804:1.06048:0.867895:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  0.000433098:0.000248722:1.08619:0.869087:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869096 ES:SE:LP:AF:ID  0.000432911:0.000248741:1.08619:0.869096:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  0.00043326:0.000248746:1.08619:0.869104:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869581 ES:SE:LP:AF:ID  0.000430448:0.00024943:1.07572:0.869581:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838301 ES:SE:LP:AF:ID  0.000351097:0.000231822:0.886057:0.838301:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838422 ES:SE:LP:AF:ID  0.000348515:0.000231986:0.886057:0.838422:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862248 ES:SE:LP:AF:ID  0.000426835:0.000247844:1.07058:0.862248:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706739 ES:SE:LP:AF:ID  0.000401132:0.000241285:1.01773:0.706739:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761284 ES:SE:LP:AF:ID  0.000286094:0.000196923:0.823909:0.761284:rs2977608
1   769223  rs60320384  C   G   .   PASS    AF=0.129585 ES:SE:LP:AF:ID  -0.000446745:0.000250288:1.13077:0.129585:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868904 ES:SE:LP:AF:ID  0.000446233:0.000248956:1.13668:0.868904:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129685 ES:SE:LP:AF:ID  -0.000445677:0.000250127:1.12494:0.129685:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868916 ES:SE:LP:AF:ID  0.000445783:0.000248961:1.13668:0.868916:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265359 ES:SE:LP:AF:ID  -3.73509e-05:0.00021999:0.0604807:0.265359:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870042 ES:SE:LP:AF:ID  0.000485354:0.000249471:1.284:0.870042:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.12858  ES:SE:LP:AF:ID  -0.000489742:0.000250452:1.29243:0.12858:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128876 ES:SE:LP:AF:ID  -0.000489981:0.000250029:1.30103:0.128876:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.86878  ES:SE:LP:AF:ID  0.000462842:0.000248803:1.20066:0.86878:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129518 ES:SE:LP:AF:ID  -0.000450364:0.000249947:1.14267:0.129518:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868533 ES:SE:LP:AF:ID  0.000473251:0.000248744:1.24413:0.868533:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868473 ES:SE:LP:AF:ID  0.000472283:0.000248899:1.23657:0.868473:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.860774 ES:SE:LP:AF:ID  0.000484384:0.000248727:1.29243:0.860774:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.128465 ES:SE:LP:AF:ID  -0.000496877:0.000251297:1.31876:0.128465:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861487 ES:SE:LP:AF:ID  0.000497319:0.000248889:1.33724:0.861487:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869225 ES:SE:LP:AF:ID  0.000503676:0.000249811:1.35655:0.869225:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.127883 ES:SE:LP:AF:ID  -0.00050093:0.000252907:1.31876:0.127883:rs111818025
1   795988  rs59380221  C   T   .   PASS    AF=0.143045 ES:SE:LP:AF:ID  -0.000624257:0.000257996:1.79588:0.143045:rs59380221