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-20437/UKB-b-20437_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20437/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20437/UKB-b-20437_data.vcf.gz ...
Read summary statistics for 4430078 SNPs.
Dropped 988 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, 1029199 SNPs remain.
After merging with regression SNP LD, 1029199 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0041 (0.0013)
Lambda GC: 1.0578
Mean Chi^2: 1.0621
Intercept: 1.021 (0.0091)
Ratio: 0.3385 (0.1458)
Analysis finished at Thu Oct 17 14:43:01 2019
Total time elapsed: 54.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8908,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -7.7662e-08,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 7,
    "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": 36748,
    "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": 1029199,
    "ldsc_nsnp_merge_regression_ld": 1029199,
    "ldsc_observed_scale_h2_beta": 0.0041,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.021,
    "ldsc_intercept_se": 0.0091,
    "ldsc_lambda_gc": 1.0578,
    "ldsc_mean_chisq": 1.0621,
    "ldsc_ratio": 0.3382
}

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 4429096 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 4430078 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 8.655611e+00 5.764867e+00 1.000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.861008e+07 5.672505e+07 8.280e+02 3.175198e+07 6.897720e+07 1.147297e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.000000e-07 2.373000e-04 -1.425e-03 -1.550000e-04 -9.000000e-07 1.535000e-04 1.582400e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.274000e-04 3.880000e-05 1.804e-04 1.940000e-04 2.142000e-04 2.533000e-04 6.599000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.911347e-01 2.912874e-01 0.000e+00 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 4.911338e-01 2.912636e-01 0.000e+00 2.371848e-01 4.885410e-01 7.430518e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.758371e-01 2.251511e-01 9.321e-02 1.804732e-01 3.203580e-01 5.387880e-01 9.067900e-01 ▇▅▃▂▂
numeric AF_reference 36748 0.9917049 NA NA NA NA NA NA NA 3.668723e-01 2.255070e-01 0.000e+00 1.807110e-01 3.192890e-01 5.269570e-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 -0.0006093 0.0003321 0.0669993 0.0665135 0.623778 0.7821490 NA
1 54676 rs2462492 C T -0.0001727 0.0003289 0.5999997 0.5994927 0.400378 NA NA
1 86028 rs114608975 T C 0.0010292 0.0005259 0.0500000 0.0503346 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0004076 0.0003239 0.2099999 0.2081916 0.456860 0.4207270 NA
1 534192 rs6680723 C T 0.0002751 0.0003700 0.4600002 0.4570809 0.240951 NA NA
1 693731 rs12238997 A G 0.0001833 0.0003100 0.5500004 0.5543792 0.116347 0.1417730 NA
1 706368 rs55727773 A G 0.0000190 0.0002297 0.9299999 0.9341219 0.515631 0.2751600 NA
1 722670 rs116030099 T C 0.0000073 0.0003789 0.9800000 0.9845494 0.101197 0.0413339 NA
1 729679 rs4951859 C G -0.0001383 0.0002687 0.6100002 0.6068101 0.843206 0.6399760 NA
1 731718 rs142557973 T C 0.0001558 0.0002941 0.5999997 0.5962037 0.122330 0.1543530 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0000949 0.0002290 0.6800001 0.6785687 0.254601 0.0984425 NA
22 51208537 rs72619593 G A -0.0001083 0.0003062 0.7199992 0.7236250 0.120703 0.1142170 NA
22 51210289 rs112565862 C T 0.0001699 0.0003049 0.5800000 0.5774313 0.129972 0.1018370 NA
22 51211106 rs9628250 T C -0.0001734 0.0002271 0.4500005 0.4450830 0.271580 0.1671330 NA
22 51211392 rs3888396 T C 0.0001972 0.0003022 0.5099998 0.5140734 0.132647 0.1641370 NA
22 51212875 rs2238837 A C 0.0001656 0.0002158 0.4400003 0.4427892 0.331418 0.3724040 NA
22 51213613 rs34726907 C T -0.0000319 0.0002843 0.9100000 0.9105175 0.127808 0.1727240 NA
22 51216564 rs9616970 T C -0.0000801 0.0002831 0.7800007 0.7772020 0.128324 0.1563500 NA
22 51219006 rs28729663 G A -0.0001386 0.0002771 0.6200004 0.6170090 0.137948 0.2052720 NA
22 51237063 rs3896457 T C 0.0001561 0.0002209 0.4799997 0.4798546 0.297948 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623778 ES:SE:LP:AF:ID  -0.000609296:0.000332051:1.17393:0.623778:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400378 ES:SE:LP:AF:ID  -0.000172719:0.000328907:0.221849:0.400378:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  0.00102924:0.000525898:1.30103:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45686  ES:SE:LP:AF:ID  0.000407648:0.000323902:0.677781:0.45686:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240951 ES:SE:LP:AF:ID  0.000275123:0.000369957:0.337242:0.240951:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116347 ES:SE:LP:AF:ID  0.000183286:0.000310018:0.259637:0.116347:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515631 ES:SE:LP:AF:ID  1.89842e-05:0.000229666:0.0315171:0.515631:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101197 ES:SE:LP:AF:ID  7.33811e-06:0.000378924:0.00877392:0.101197:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843206 ES:SE:LP:AF:ID  -0.000138276:0.000268689:0.21467:0.843206:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  0.000155824:0.000294081:0.221849:0.12233:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121571 ES:SE:LP:AF:ID  0.00014843:0.00029421:0.21467:0.121571:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  -3.50055e-06:0.000289986:0.00436481:0.132336:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838943 ES:SE:LP:AF:ID  -0.000250252:0.000260204:0.468521:0.838943:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838571 ES:SE:LP:AF:ID  -0.000307263:0.000259924:0.619789:0.838571:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86976  ES:SE:LP:AF:ID  -0.000422736:0.000278906:0.886057:0.86976:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  0.00041944:0.00027947:0.886057:0.129892:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869102 ES:SE:LP:AF:ID  -0.000477595:0.000278359:1.0655:0.869102:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869201 ES:SE:LP:AF:ID  -0.000482859:0.00027847:1.08092:0.869201:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869105 ES:SE:LP:AF:ID  -0.000479623:0.000278353:1.07058:0.869105:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838023 ES:SE:LP:AF:ID  -0.000297052:0.000259201:0.60206:0.838023:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838653 ES:SE:LP:AF:ID  -0.000306567:0.000259929:0.619789:0.838653:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839766 ES:SE:LP:AF:ID  -0.000286993:0.000263443:0.552842:0.839766:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869384 ES:SE:LP:AF:ID  -0.000412879:0.000278032:0.853872:0.869384:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868929 ES:SE:LP:AF:ID  -0.000420787:0.000277331:0.886057:0.868929:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867885 ES:SE:LP:AF:ID  -0.000481919:0.000276801:1.08619:0.867885:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869073 ES:SE:LP:AF:ID  -0.000417419:0.000277558:0.886057:0.869073:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869082 ES:SE:LP:AF:ID  -0.000417567:0.00027758:0.886057:0.869082:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  -0.000408103:0.000277586:0.853872:0.869089:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869568 ES:SE:LP:AF:ID  -0.000412356:0.000278349:0.853872:0.869568:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838305 ES:SE:LP:AF:ID  -0.000260625:0.00025871:0.508638:0.838305:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838424 ES:SE:LP:AF:ID  -0.000267178:0.00025889:0.522879:0.838424:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862245 ES:SE:LP:AF:ID  -0.00050008:0.000276589:1.14874:0.862245:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706739 ES:SE:LP:AF:ID  -0.000483195:0.000269258:1.13668:0.706739:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105159 ES:SE:LP:AF:ID  0.000245583:0.000310168:0.366532:0.105159:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761308 ES:SE:LP:AF:ID  -0.000298746:0.000219766:0.769551:0.761308:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106471 ES:SE:LP:AF:ID  1.77198e-05:0.000302953:0.0222764:0.106471:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129596 ES:SE:LP:AF:ID  0.000315392:0.000279305:0.585027:0.129596:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868893 ES:SE:LP:AF:ID  -0.000401833:0.000277819:0.823909:0.868893:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129697 ES:SE:LP:AF:ID  0.000318167:0.000279124:0.60206:0.129697:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868903 ES:SE:LP:AF:ID  -0.000401761:0.000277824:0.823909:0.868903:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265404 ES:SE:LP:AF:ID  0.000155402:0.000245483:0.275724:0.265404:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870025 ES:SE:LP:AF:ID  -0.000389691:0.00027839:0.79588:0.870025:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095138 ES:SE:LP:AF:ID  2.68342e-05:0.000322676:0.0315171:0.095138:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128597 ES:SE:LP:AF:ID  0.000322254:0.000279484:0.60206:0.128597:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128893 ES:SE:LP:AF:ID  0.000325754:0.00027901:0.619789:0.128893:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868769 ES:SE:LP:AF:ID  -0.000450624:0.000277652:1:0.868769:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101887 ES:SE:LP:AF:ID  0.000174268:0.000314592:0.236572:0.101887:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.129532 ES:SE:LP:AF:ID  0.000370101:0.000278925:0.744727:0.129532:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868525 ES:SE:LP:AF:ID  -0.000477681:0.000277589:1.07058:0.868525:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868466 ES:SE:LP:AF:ID  -0.000470997:0.000277762:1.04576:0.868466:rs2980300