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-7763/UKB-b-7763_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7763/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7763/UKB-b-7763_data.vcf.gz ...
Read summary statistics for 4494064 SNPs.
Dropped 1031 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, 1039779 SNPs remain.
After merging with regression SNP LD, 1039779 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0026 (0.0011)
Lambda GC: 1.0324
Mean Chi^2: 1.0355
Intercept: 1.0102 (0.0089)
Ratio: 0.2863 (0.252)
Analysis finished at Thu Oct 17 14:41:49 2019
Total time elapsed: 55.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8928,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 2.2543e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 465,
    "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": 37434,
    "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": 1039779,
    "ldsc_nsnp_merge_regression_ld": 1039779,
    "ldsc_observed_scale_h2_beta": 0.0026,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0102,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.0324,
    "ldsc_mean_chisq": 1.0355,
    "ldsc_ratio": 0.2873
}
 

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 4493040 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 4494064 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 8.658230e+00 5.765396e+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 7.858519e+07 5.672277e+07 828.0000000 3.172913e+07 6.893219e+07 1.147222e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.300000e-06 2.423000e-04 -0.0014727 -1.558000e-04 1.100000e-06 1.580000e-04 2.429700e-03 ▁▇▅▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.333000e-04 4.110000e-05 0.0001840 1.980000e-04 2.193000e-04 2.606000e-04 6.730000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.938873e-01 2.902861e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.938888e-01 2.902580e-01 0.0000000 2.407969e-01 4.918465e-01 7.455313e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.731806e-01 2.268461e-01 0.0897670 1.765130e-01 3.165300e-01 5.366770e-01 9.102330e-01 ▇▅▃▂▂
numeric AF_reference 37434 0.9916703 NA NA NA NA NA NA NA 3.644913e-01 2.267071e-01 0.0000000 1.773160e-01 3.158950e-01 5.251600e-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 -0.0002992 0.0003386 0.3800004 0.3768677 0.623775 0.7821490 NA
1 54676 rs2462492 C T 0.0004713 0.0003355 0.1600000 0.1600893 0.400405 NA NA
1 86028 rs114608975 T C 0.0004818 0.0005364 0.3700002 0.3690423 0.103552 0.0277556 NA
1 91536 rs6702460 G T 0.0004792 0.0003303 0.1499999 0.1467803 0.456862 0.4207270 NA
1 534192 rs6680723 C T 0.0000235 0.0003773 0.9500000 0.9503737 0.240948 NA NA
1 693731 rs12238997 A G 0.0001990 0.0003162 0.5300002 0.5291753 0.116323 0.1417730 NA
1 706368 rs55727773 A G -0.0001764 0.0002342 0.4500005 0.4512689 0.515676 0.2751600 NA
1 722670 rs116030099 T C -0.0000185 0.0003864 0.9599999 0.9617610 0.101207 0.0413339 NA
1 729679 rs4951859 C G -0.0002838 0.0002740 0.2999998 0.3003468 0.843199 0.6399760 NA
1 731718 rs142557973 T C 0.0001279 0.0003000 0.6700003 0.6697972 0.122311 0.1543530 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0003768 0.0002336 0.1100001 0.1067068 0.254582 0.0984425 NA
22 51208537 rs72619593 G A 0.0001382 0.0003122 0.6600001 0.6580964 0.120740 0.1142170 NA
22 51210289 rs112565862 C T 0.0004229 0.0003110 0.1700000 0.1739239 0.129931 0.1018370 NA
22 51211106 rs9628250 T C -0.0003597 0.0002316 0.1199999 0.1204034 0.271574 0.1671330 NA
22 51211392 rs3888396 T C 0.0004609 0.0003082 0.1299999 0.1348403 0.132613 0.1641370 NA
22 51212875 rs2238837 A C 0.0002910 0.0002200 0.1900002 0.1860037 0.331442 0.3724040 NA
22 51213613 rs34726907 C T 0.0000190 0.0002899 0.9500000 0.9477938 0.127811 0.1727240 NA
22 51216564 rs9616970 T C 0.0000053 0.0002887 0.9900000 0.9853664 0.128322 0.1563500 NA
22 51219006 rs28729663 G A -0.0000058 0.0002825 0.9800000 0.9835586 0.137946 0.2052720 NA
22 51237063 rs3896457 T C 0.0003396 0.0002253 0.1299999 0.1316871 0.297972 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623775 ES:SE:LP:AF:ID  -0.000299191:0.000338573:0.420216:0.623775:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400405 ES:SE:LP:AF:ID  0.000471305:0.000335503:0.79588:0.400405:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103552 ES:SE:LP:AF:ID  0.000481808:0.000536374:0.431798:0.103552:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456862 ES:SE:LP:AF:ID  0.000479243:0.000330285:0.823909:0.456862:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240948 ES:SE:LP:AF:ID  2.34817e-05:0.000377292:0.0222764:0.240948:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116323 ES:SE:LP:AF:ID  0.00019898:0.00031621:0.275724:0.116323:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515676 ES:SE:LP:AF:ID  -0.000176448:0.000234233:0.346787:0.515676:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101207 ES:SE:LP:AF:ID  -1.85273e-05:0.000386438:0.0177288:0.101207:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843199 ES:SE:LP:AF:ID  -0.000283806:0.000274026:0.522879:0.843199:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:ID  0.000127907:0.000299951:0.173925:0.122311:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121554 ES:SE:LP:AF:ID  0.000115971:0.000300077:0.154902:0.121554:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132333 ES:SE:LP:AF:ID  0.00034899:0.00029576:0.619789:0.132333:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838942 ES:SE:LP:AF:ID  -0.000241549:0.000265375:0.443698:0.838942:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838569 ES:SE:LP:AF:ID  -0.00022259:0.000265089:0.39794:0.838569:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869777 ES:SE:LP:AF:ID  -0.000179773:0.000284455:0.275724:0.869777:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  0.000157809:0.000285032:0.236572:0.129876:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.000170117:0.000283896:0.259637:0.869117:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  -0.000158317:0.000284008:0.236572:0.869215:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  -0.000171007:0.000283891:0.259637:0.869121:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838022 ES:SE:LP:AF:ID  -0.000229851:0.000264353:0.420216:0.838022:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838652 ES:SE:LP:AF:ID  -0.000241909:0.000265095:0.443698:0.838652:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839768 ES:SE:LP:AF:ID  -0.000227917:0.000268683:0.39794:0.839768:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869402 ES:SE:LP:AF:ID  -0.000160873:0.000283565:0.244125:0.869402:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  -0.000147299:0.000282854:0.221849:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867901 ES:SE:LP:AF:ID  -0.000175001:0.000282308:0.267606:0.867901:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869094 ES:SE:LP:AF:ID  -0.000151493:0.000283084:0.229148:0.869094:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869102 ES:SE:LP:AF:ID  -0.000151765:0.000283106:0.229148:0.869102:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  -0.000151427:0.000283113:0.229148:0.86911:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869586 ES:SE:LP:AF:ID  -0.000166898:0.000283888:0.251812:0.869586:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838302 ES:SE:LP:AF:ID  -0.000243908:0.000263849:0.443698:0.838302:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838423 ES:SE:LP:AF:ID  -0.000244177:0.000264036:0.443698:0.838423:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862257 ES:SE:LP:AF:ID  -0.000204676:0.000282085:0.327902:0.862257:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706761 ES:SE:LP:AF:ID  -0.000178284:0.000274614:0.283997:0.706761:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105127 ES:SE:LP:AF:ID  0.000269991:0.00031637:0.408935:0.105127:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.76134  ES:SE:LP:AF:ID  -0.000283181:0.000224148:0.677781:0.76134:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106455 ES:SE:LP:AF:ID  0.000202195:0.000308957:0.29243:0.106455:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129573 ES:SE:LP:AF:ID  0.000174135:0.00028487:0.267606:0.129573:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868913 ES:SE:LP:AF:ID  -0.000202453:0.00028335:0.327902:0.868913:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129674 ES:SE:LP:AF:ID  0.00017762:0.000284685:0.275724:0.129674:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868924 ES:SE:LP:AF:ID  -0.000204461:0.000283356:0.327902:0.868924:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265371 ES:SE:LP:AF:ID  0.000208166:0.000250354:0.387216:0.265371:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870042 ES:SE:LP:AF:ID  -0.000203853:0.000283932:0.327902:0.870042:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095116 ES:SE:LP:AF:ID  0.000156194:0.000329095:0.19382:0.095116:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128575 ES:SE:LP:AF:ID  0.000183412:0.00028505:0.283997:0.128575:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128873 ES:SE:LP:AF:ID  0.000189801:0.000284566:0.30103:0.128873:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868783 ES:SE:LP:AF:ID  -0.000234021:0.000283173:0.387216:0.868783:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.10186  ES:SE:LP:AF:ID  0.000278601:0.000320883:0.408935:0.10186:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.129515 ES:SE:LP:AF:ID  0.00018875:0.000284473:0.29243:0.129515:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868537 ES:SE:LP:AF:ID  -0.000239576:0.000283111:0.39794:0.868537:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868478 ES:SE:LP:AF:ID  -0.000245958:0.000283287:0.408935:0.868478:rs2980300