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-12252/UKB-b-12252_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12252/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12252/UKB-b-12252_data.vcf.gz ...
Read summary statistics for 4448215 SNPs.
Dropped 1002 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, 1032180 SNPs remain.
After merging with regression SNP LD, 1032180 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.004 (0.0011)
Lambda GC: 1.0438
Mean Chi^2: 1.0477
Intercept: 1.0091 (0.008)
Ratio: 0.19 (0.1687)
Analysis finished at Thu Oct 17 14:42:25 2019
Total time elapsed: 52.14s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8913,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 8.7383e-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": 36935,
    "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": 1032180,
    "ldsc_nsnp_merge_regression_ld": 1032180,
    "ldsc_observed_scale_h2_beta": 0.004,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0091,
    "ldsc_intercept_se": 0.008,
    "ldsc_lambda_gc": 1.0438,
    "ldsc_mean_chisq": 1.0477,
    "ldsc_ratio": 0.1908
}

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 4447219 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 4448215 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 8.654599e+00 5.764470e+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 7.861722e+07 5.673408e+07 828.0000000 3.174699e+07 6.897962e+07 1.147458e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.000000e-07 2.390000e-04 -0.0014528 -1.549000e-04 2.000000e-07 1.561000e-04 1.438400e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.300000e-04 3.960000e-05 0.0001821 1.959000e-04 2.164000e-04 2.563000e-04 6.661000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.924318e-01 2.907031e-01 0.0000012 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 4.924323e-01 2.906774e-01 0.0000012 2.390137e-01 4.897460e-01 7.436463e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.750814e-01 2.256352e-01 0.0922270 1.793970e-01 3.191790e-01 5.381840e-01 9.077720e-01 ▇▅▃▂▂
numeric AF_reference 36935 0.9916967 NA NA NA NA NA NA NA 3.661831e-01 2.258527e-01 0.0000000 1.797120e-01 3.182910e-01 5.263580e-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 0.0000855 0.0003352 0.8000000 0.7987280 0.623772 0.7821490 NA
1 54676 rs2462492 C T -0.0007940 0.0003321 0.0170000 0.0168044 0.400415 NA NA
1 86028 rs114608975 T C 0.0007832 0.0005309 0.1400000 0.1401395 0.103540 0.0277556 NA
1 91536 rs6702460 G T -0.0001903 0.0003270 0.5600000 0.5605053 0.456897 0.4207270 NA
1 534192 rs6680723 C T -0.0005010 0.0003735 0.1800002 0.1798328 0.240946 NA NA
1 693731 rs12238997 A G -0.0000488 0.0003130 0.8800001 0.8761803 0.116282 0.1417730 NA
1 706368 rs55727773 A G 0.0002249 0.0002319 0.3300000 0.3320811 0.515651 0.2751600 NA
1 722670 rs116030099 T C -0.0005553 0.0003824 0.1499999 0.1464867 0.101233 0.0413339 NA
1 729679 rs4951859 C G -0.0002180 0.0002713 0.4199997 0.4217061 0.843240 0.6399760 NA
1 731718 rs142557973 T C -0.0000408 0.0002970 0.8900000 0.8906003 0.122265 0.1543530 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0002974 0.0002312 0.2000000 0.1983061 0.254580 0.0984425 NA
22 51208537 rs72619593 G A 0.0001330 0.0003090 0.6700003 0.6670065 0.120750 0.1142170 NA
22 51210289 rs112565862 C T 0.0000824 0.0003078 0.7899998 0.7890597 0.129924 0.1018370 NA
22 51211106 rs9628250 T C -0.0002800 0.0002293 0.2200002 0.2219674 0.271571 0.1671330 NA
22 51211392 rs3888396 T C 0.0000902 0.0003051 0.7700005 0.7673955 0.132602 0.1641370 NA
22 51212875 rs2238837 A C 0.0001251 0.0002178 0.5700002 0.5658177 0.331473 0.3724040 NA
22 51213613 rs34726907 C T 0.0002233 0.0002869 0.4400003 0.4365142 0.127814 0.1727240 NA
22 51216564 rs9616970 T C 0.0002027 0.0002857 0.4799997 0.4779754 0.128331 0.1563500 NA
22 51219006 rs28729663 G A 0.0002126 0.0002796 0.4500005 0.4472009 0.137942 0.2052720 NA
22 51237063 rs3896457 T C 0.0000704 0.0002230 0.7499995 0.7521994 0.298011 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  8.54708e-05:0.000335188:0.09691:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400415 ES:SE:LP:AF:ID  -0.000793966:0.00033207:1.76955:0.400415:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10354  ES:SE:LP:AF:ID  0.000783235:0.000530909:0.853872:0.10354:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456897 ES:SE:LP:AF:ID  -0.000190331:0.000326978:0.251812:0.456897:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240946 ES:SE:LP:AF:ID  -0.000501026:0.000373546:0.744727:0.240946:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116282 ES:SE:LP:AF:ID  -4.87767e-05:0.000313046:0.0555173:0.116282:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515651 ES:SE:LP:AF:ID  0.000224891:0.000231863:0.481486:0.515651:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101233 ES:SE:LP:AF:ID  -0.000555319:0.000382437:0.823909:0.101233:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.84324  ES:SE:LP:AF:ID  -0.000217972:0.00027129:0.376751:0.84324:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122265 ES:SE:LP:AF:ID  -4.0845e-05:0.000296958:0.05061:0.122265:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121506 ES:SE:LP:AF:ID  -6.90478e-05:0.000297087:0.0861861:0.121506:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132323 ES:SE:LP:AF:ID  0.000172452:0.000292754:0.251812:0.132323:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.83896  ES:SE:LP:AF:ID  -0.000256738:0.000262716:0.481486:0.83896:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83859  ES:SE:LP:AF:ID  -0.000275461:0.000262435:0.537602:0.83859:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869809 ES:SE:LP:AF:ID  -9.058e-05:0.000281616:0.124939:0.869809:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129838 ES:SE:LP:AF:ID  9.22391e-05:0.000282193:0.130768:0.129838:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869151 ES:SE:LP:AF:ID  -0.000105272:0.000281064:0.148742:0.869151:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869248 ES:SE:LP:AF:ID  -0.000113141:0.000281175:0.161151:0.869248:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  -0.000106147:0.000281058:0.148742:0.869154:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838041 ES:SE:LP:AF:ID  -0.000265316:0.000261704:0.508638:0.838041:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838673 ES:SE:LP:AF:ID  -0.000245145:0.00026244:0.455932:0.838673:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83978  ES:SE:LP:AF:ID  -0.000221408:0.000265984:0.387216:0.83978:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869433 ES:SE:LP:AF:ID  -7.95081e-05:0.000280732:0.107905:0.869433:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868979 ES:SE:LP:AF:ID  -9.56364e-05:0.000280026:0.136677:0.868979:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867935 ES:SE:LP:AF:ID  -0.000107243:0.00027949:0.154902:0.867935:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869124 ES:SE:LP:AF:ID  -8.10018e-05:0.000280258:0.113509:0.869124:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869132 ES:SE:LP:AF:ID  -8.14188e-05:0.000280279:0.113509:0.869132:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86914  ES:SE:LP:AF:ID  -8.13583e-05:0.000280286:0.113509:0.86914:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869616 ES:SE:LP:AF:ID  -8.48685e-05:0.000281051:0.119186:0.869616:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.83832  ES:SE:LP:AF:ID  -0.000221136:0.000261203:0.39794:0.83832:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.83844  ES:SE:LP:AF:ID  -0.000221039:0.000261387:0.39794:0.83844:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862291 ES:SE:LP:AF:ID  -0.000146958:0.000279277:0.221849:0.862291:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706756 ES:SE:LP:AF:ID  -0.000264569:0.000271867:0.481486:0.706756:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105117 ES:SE:LP:AF:ID  -3.75678e-05:0.00031316:0.0457575:0.105117:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761378 ES:SE:LP:AF:ID  -6.41571e-05:0.000221888:0.113509:0.761378:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106451 ES:SE:LP:AF:ID  -2.56321e-05:0.00030583:0.0315171:0.106451:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129542 ES:SE:LP:AF:ID  5.03129e-05:0.000282028:0.0655015:0.129542:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868945 ES:SE:LP:AF:ID  -8.86293e-05:0.000280524:0.124939:0.868945:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129641 ES:SE:LP:AF:ID  5.67292e-05:0.000281849:0.0757207:0.129641:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868955 ES:SE:LP:AF:ID  -8.03566e-05:0.000280529:0.113509:0.868955:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26542  ES:SE:LP:AF:ID  8.42402e-05:0.000247806:0.136677:0.26542:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870078 ES:SE:LP:AF:ID  -4.65131e-05:0.000281104:0.0604807:0.870078:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095103 ES:SE:LP:AF:ID  -6.72258e-05:0.000325774:0.0757207:0.095103:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.12854  ES:SE:LP:AF:ID  1.58305e-05:0.000282215:0.0177288:0.12854:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128836 ES:SE:LP:AF:ID  2.67088e-05:0.000281738:0.0362122:0.128836:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868822 ES:SE:LP:AF:ID  -9.46815e-05:0.000280356:0.130768:0.868822:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101847 ES:SE:LP:AF:ID  -5.65941e-05:0.000317629:0.0655015:0.101847:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.129474 ES:SE:LP:AF:ID  8.04357e-05:0.000281648:0.107905:0.129474:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868577 ES:SE:LP:AF:ID  -0.000115616:0.000280289:0.167491:0.868577:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868518 ES:SE:LP:AF:ID  -0.000123681:0.000280463:0.180456:0.868518:rs2980300