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-3273/UKB-b-3273_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3273/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3273/UKB-b-3273_data.vcf.gz ...
Read summary statistics for 4559600 SNPs.
Dropped 1066 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, 1050257 SNPs remain.
After merging with regression SNP LD, 1050257 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0046 (0.0013)
Lambda GC: 1.0724
Mean Chi^2: 1.0712
Intercept: 1.0278 (0.0081)
Ratio: 0.39 (0.1138)
Analysis finished at Thu Oct 17 14:44:18 2019
Total time elapsed: 54.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8948,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 3.1541e-07,
    "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": 38054,
    "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": 1050257,
    "ldsc_nsnp_merge_regression_ld": 1050257,
    "ldsc_observed_scale_h2_beta": 0.0046,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0278,
    "ldsc_intercept_se": 0.0081,
    "ldsc_lambda_gc": 1.0724,
    "ldsc_mean_chisq": 1.0712,
    "ldsc_ratio": 0.3904
}

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 4558543 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 4559600 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 8.658605e+00 5.765006e+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 7.858719e+07 5.671996e+07 828.0000000 3.175550e+07 6.892204e+07 1.147052e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.000000e-07 2.599000e-04 -0.0017842 -1.689000e-04 -1.100000e-06 1.690000e-04 1.689800e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.481000e-04 4.510000e-05 0.0001943 2.094000e-04 2.326000e-04 2.779000e-04 7.108000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.897043e-01 2.919728e-01 0.0000020 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.897044e-01 2.919479e-01 0.0000020 2.340337e-01 4.857653e-01 7.431493e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.704493e-01 2.285314e-01 0.0864200 1.724860e-01 3.125460e-01 5.344780e-01 9.135800e-01 ▇▅▃▂▂
numeric AF_reference 38054 0.9916541 NA NA NA NA NA NA NA 3.620376e-01 2.279299e-01 0.0000000 1.739220e-01 3.125000e-01 5.229630e-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 -0.0002206 0.0003576 0.5400003 0.5373813 0.623744 0.7821490 NA
1 54676 rs2462492 C T -0.0000938 0.0003543 0.7899998 0.7911054 0.400437 NA NA
1 86028 rs114608975 T C -0.0003195 0.0005665 0.5700002 0.5727626 0.103526 0.0277556 NA
1 91536 rs6702460 G T 0.0000652 0.0003488 0.8499999 0.8516167 0.456863 0.4207270 NA
1 534192 rs6680723 C T -0.0002177 0.0003985 0.5800000 0.5848223 0.240911 NA NA
1 546697 rs12025928 A G 0.0000003 0.0004971 1.0000000 0.9995003 0.913479 NA NA
1 693731 rs12238997 A G 0.0001545 0.0003340 0.6400000 0.6437601 0.116353 0.1417730 NA
1 706368 rs55727773 A G -0.0002559 0.0002474 0.2999998 0.3009396 0.515724 0.2751600 NA
1 722670 rs116030099 T C -0.0000037 0.0004082 0.9900000 0.9927095 0.101237 0.0413339 NA
1 729679 rs4951859 C G 0.0000398 0.0002894 0.8900000 0.8906862 0.843134 0.6399760 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0004018 0.0002467 0.1000000 0.1034392 0.254350 0.0984425 NA
22 51208537 rs72619593 G A 0.0001882 0.0003297 0.5700002 0.5681586 0.120844 0.1142170 NA
22 51210289 rs112565862 C T 0.0001310 0.0003285 0.6899999 0.6901137 0.129948 0.1018370 NA
22 51211106 rs9628250 T C -0.0002715 0.0002446 0.2700001 0.2670305 0.271348 0.1671330 NA
22 51211392 rs3888396 T C 0.0001197 0.0003256 0.7099994 0.7132128 0.132635 0.1641370 NA
22 51212875 rs2238837 A C 0.0002812 0.0002324 0.2300001 0.2262092 0.331649 0.3724040 NA
22 51213613 rs34726907 C T 0.0001701 0.0003061 0.5800000 0.5784095 0.127899 0.1727240 NA
22 51216564 rs9616970 T C 0.0001877 0.0003048 0.5400003 0.5379114 0.128420 0.1563500 NA
22 51219006 rs28729663 G A 0.0002361 0.0002983 0.4299995 0.4287446 0.138026 0.2052720 NA
22 51237063 rs3896457 T C 0.0002008 0.0002379 0.4000000 0.3985524 0.298186 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623744 ES:SE:LP:AF:ID  -0.000220569:0.000357615:0.267606:0.623744:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400437 ES:SE:LP:AF:ID  -9.38496e-05:0.000354316:0.102373:0.400437:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103526 ES:SE:LP:AF:ID  -0.000319486:0.000566477:0.244125:0.103526:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  6.52457e-05:0.000348803:0.0705811:0.456863:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240911 ES:SE:LP:AF:ID  -0.000217737:0.000398527:0.236572:0.240911:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913479 ES:SE:LP:AF:ID  3.11341e-07:0.000497144:-0:0.913479:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116353 ES:SE:LP:AF:ID  0.000154459:0.000334003:0.19382:0.116353:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515724 ES:SE:LP:AF:ID  -0.000255927:0.000247411:0.522879:0.515724:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101237 ES:SE:LP:AF:ID  -3.72981e-06:0.000408193:0.00436481:0.101237:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843134 ES:SE:LP:AF:ID  3.97792e-05:0.000289438:0.05061:0.843134:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122339 ES:SE:LP:AF:ID  9.98368e-05:0.000316802:0.124939:0.122339:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121582 ES:SE:LP:AF:ID  0.000100941:0.000316933:0.124939:0.121582:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132407 ES:SE:LP:AF:ID  -7.07034e-05:0.000312339:0.0861861:0.132407:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838833 ES:SE:LP:AF:ID  -2.04273e-05:0.000280239:0.0268721:0.838833:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838453 ES:SE:LP:AF:ID  -2.37088e-05:0.000279926:0.0315171:0.838453:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869719 ES:SE:LP:AF:ID  -6.84252e-05:0.000300391:0.0861861:0.869719:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129948 ES:SE:LP:AF:ID  7.79016e-05:0.000300986:0.09691:0.129948:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869057 ES:SE:LP:AF:ID  -6.79191e-05:0.000299793:0.0861861:0.869057:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869157 ES:SE:LP:AF:ID  -7.19653e-05:0.000299915:0.091515:0.869157:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86906  ES:SE:LP:AF:ID  -6.93491e-05:0.000299788:0.0861861:0.86906:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837904 ES:SE:LP:AF:ID  -7.30049e-06:0.000279149:0.00877392:0.837904:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838536 ES:SE:LP:AF:ID  1.42832e-05:0.000279933:0.0177288:0.838536:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839657 ES:SE:LP:AF:ID  1.13817e-05:0.000283736:0.0132283:0.839657:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869347 ES:SE:LP:AF:ID  -8.06326e-05:0.000299458:0.102373:0.869347:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868897 ES:SE:LP:AF:ID  -0.000119038:0.000298716:0.161151:0.868897:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86784  ES:SE:LP:AF:ID  -0.00013905:0.000298125:0.19382:0.86784:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869037 ES:SE:LP:AF:ID  -0.000107407:0.000298956:0.142668:0.869037:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869046 ES:SE:LP:AF:ID  -0.000107665:0.000298979:0.142668:0.869046:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869054 ES:SE:LP:AF:ID  -0.000107137:0.000298986:0.142668:0.869054:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86953  ES:SE:LP:AF:ID  -8.77567e-05:0.000299798:0.113509:0.86953:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838193 ES:SE:LP:AF:ID  1.84974e-05:0.000278634:0.0222764:0.838193:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  2.03345e-05:0.000278832:0.0268721:0.838313:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862194 ES:SE:LP:AF:ID  -0.000134013:0.000297914:0.187087:0.862194:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.70668  ES:SE:LP:AF:ID  -3.14189e-05:0.000290033:0.0409586:0.70668:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.10516  ES:SE:LP:AF:ID  0.000291649:0.000334139:0.420216:0.10516:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761333 ES:SE:LP:AF:ID  -0.000347183:0.000236829:0.853872:0.761333:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106414 ES:SE:LP:AF:ID  0.000489196:0.000326465:0.886057:0.106414:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129635 ES:SE:LP:AF:ID  0.000158966:0.000300842:0.221849:0.129635:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868861 ES:SE:LP:AF:ID  -0.000124514:0.000299239:0.167491:0.868861:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129735 ES:SE:LP:AF:ID  0.000154494:0.000300647:0.21467:0.129735:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868871 ES:SE:LP:AF:ID  -0.000125469:0.000299245:0.167491:0.868871:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265297 ES:SE:LP:AF:ID  0.000116532:0.000264486:0.180456:0.265297:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870017 ES:SE:LP:AF:ID  -4.88026e-05:0.000299876:0.0604807:0.870017:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095092 ES:SE:LP:AF:ID  0.000310513:0.000347692:0.431798:0.095092:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128604 ES:SE:LP:AF:ID  7.90289e-05:0.000301059:0.102373:0.128604:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128899 ES:SE:LP:AF:ID  6.67124e-05:0.000300554:0.0861861:0.128899:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868755 ES:SE:LP:AF:ID  -5.27942e-05:0.000299077:0.0655015:0.868755:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101861 ES:SE:LP:AF:ID  0.000157551:0.000338942:0.19382:0.101861:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.12955  ES:SE:LP:AF:ID  8.1748e-05:0.000300452:0.102373:0.12955:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.86851  ES:SE:LP:AF:ID  -5.92253e-05:0.000299009:0.0757207:0.86851:rs2905062