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-11262/UKB-b-11262_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11262/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11262/UKB-b-11262_data.vcf.gz ...
Read summary statistics for 5237224 SNPs.
Dropped 1670 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, 1144841 SNPs remain.
After merging with regression SNP LD, 1144841 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0005 (0.001)
Lambda GC: 1.0306
Mean Chi^2: 1.0275
Intercept: 1.0323 (0.0071)
Ratio: 1.1749 (0.2596)
Analysis finished at Thu Oct 17 14:41:21 2019
Total time elapsed: 1.0m:2.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9115,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -3.8496e-08,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 45234,
    "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": 1144841,
    "ldsc_nsnp_merge_regression_ld": 1144841,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0323,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.0306,
    "ldsc_mean_chisq": 1.0275,
    "ldsc_ratio": 1.1745
}

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 1.000000 3 58 0 5235566 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 5237224 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.673172e+00 5.763983e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.852600e+07 5.659370e+07 828.0000000 3.189976e+07 6.890485e+07 1.144835e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 0.000000e+00 3.295000e-04 -0.0021579 -2.081000e-04 -1.100000e-06 2.069000e-04 3.016900e-03 ▁▅▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 3.166000e-04 7.840000e-05 0.0002301 2.506000e-04 2.880000e-04 3.655000e-04 1.057200e-03 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.963688e-01 2.897302e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.963692e-01 2.897037e-01 0.0000000 2.443154e-01 4.948567e-01 7.474420e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 3.418340e-01 2.427068e-01 0.0566710 1.332870e-01 2.723470e-01 5.086030e-01 9.433290e-01 ▇▃▂▂▂
numeric AF_reference 45234 0.991363 NA NA NA NA NA NA NA 3.360646e-01 2.383399e-01 0.0000000 1.395770e-01 2.759580e-01 4.982030e-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 -0.0002005 0.0004234 0.6400000 0.6359234 0.623767 0.7821490 NA
1 54676 rs2462492 C T 0.0003176 0.0004195 0.4500005 0.4490491 0.400401 NA NA
1 86028 rs114608975 T C -0.0008417 0.0006707 0.2099999 0.2094938 0.103555 0.0277556 NA
1 91536 rs6702460 G T 0.0004993 0.0004130 0.2300001 0.2267308 0.456847 0.4207270 NA
1 234313 rs8179466 C T -0.0001697 0.0008144 0.8300000 0.8349805 0.074507 NA NA
1 534192 rs6680723 C T 0.0002895 0.0004718 0.5400003 0.5395055 0.240957 NA NA
1 546697 rs12025928 A G -0.0004098 0.0005886 0.4899999 0.4862618 0.913476 NA NA
1 693731 rs12238997 A G 0.0002874 0.0003954 0.4700002 0.4672740 0.116328 0.1417730 NA
1 705882 rs72631875 G A 0.0000520 0.0005794 0.9299999 0.9284218 0.067288 0.0315495 NA
1 706368 rs55727773 A G 0.0002065 0.0002929 0.4799997 0.4807604 0.515644 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T -0.0007125 0.0003625 0.0490004 0.0493651 0.127815 0.1727240 NA
22 51216564 rs9616970 T C -0.0007082 0.0003610 0.0500000 0.0497709 0.128330 0.1563500 NA
22 51217954 rs9616974 G A -0.0005123 0.0004580 0.2599998 0.2633424 0.073313 0.0621006 NA
22 51218224 rs9616975 C A -0.0005190 0.0004582 0.2599998 0.2574210 0.073335 0.0619010 NA
22 51218377 rs2519461 G C -0.0005600 0.0004577 0.2200002 0.2211607 0.073624 0.0826677 NA
22 51219006 rs28729663 G A -0.0005905 0.0003533 0.0949992 0.0946306 0.137952 0.2052720 NA
22 51219387 rs9616832 T C -0.0005480 0.0004586 0.2300001 0.2321383 0.073746 0.0654952 NA
22 51221731 rs115055839 T C -0.0005153 0.0004589 0.2599998 0.2614755 0.073237 0.0625000 NA
22 51229805 rs9616985 T C -0.0004612 0.0004606 0.3200000 0.3166532 0.073072 0.0730831 NA
22 51237063 rs3896457 T C 0.0001516 0.0002817 0.5900000 0.5904030 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623767 ES:SE:LP:AF:ID  -0.000200461:0.000423444:0.19382:0.623767:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000317562:0.0004195:0.346787:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103555 ES:SE:LP:AF:ID  -0.000841692:0.000670693:0.677781:0.103555:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456847 ES:SE:LP:AF:ID  0.000499302:0.000413048:0.638272:0.456847:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074507 ES:SE:LP:AF:ID  -0.00016966:0.000814427:0.0809219:0.074507:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240957 ES:SE:LP:AF:ID  0.000289486:0.000471813:0.267606:0.240957:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -0.000409831:0.000588612:0.309804:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116328 ES:SE:LP:AF:ID  0.000287419:0.000395392:0.327902:0.116328:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  5.20477e-05:0.000579398:0.0315171:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515644 ES:SE:LP:AF:ID  0.000206513:0.000292893:0.318759:0.515644:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101201 ES:SE:LP:AF:ID  0.000163283:0.000483249:0.130768:0.101201:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  -0.000386721:0.000342658:0.585027:0.843204:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:ID  0.00016912:0.000375068:0.187087:0.122311:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121553 ES:SE:LP:AF:ID  0.000162833:0.000375226:0.180456:0.121553:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132334 ES:SE:LP:AF:ID  0.000780366:0.000369823:1.45593:0.132334:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  -0.000335929:0.000331841:0.508638:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838574 ES:SE:LP:AF:ID  -0.000374951:0.000331484:0.585027:0.838574:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  -0.000146779:0.000355694:0.167491:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129875 ES:SE:LP:AF:ID  0.000194077:0.000356422:0.229148:0.129875:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  -0.000183441:0.000354997:0.21467:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  -0.00016639:0.000355137:0.19382:0.869216:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  -0.00017481:0.00035499:0.207608:0.869121:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838027 ES:SE:LP:AF:ID  -0.000349413:0.000330564:0.537602:0.838027:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838658 ES:SE:LP:AF:ID  -0.000351534:0.000331493:0.537602:0.838658:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839771 ES:SE:LP:AF:ID  -0.000312718:0.000335976:0.455932:0.839771:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.8694   ES:SE:LP:AF:ID  -0.000133914:0.000354579:0.148742:0.8694:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868947 ES:SE:LP:AF:ID  -0.000135482:0.000353687:0.154902:0.868947:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867899 ES:SE:LP:AF:ID  -0.000135481:0.000353009:0.154902:0.867899:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86909  ES:SE:LP:AF:ID  -0.000135636:0.000353977:0.154902:0.86909:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869099 ES:SE:LP:AF:ID  -0.000135986:0.000354004:0.154902:0.869099:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869107 ES:SE:LP:AF:ID  -0.000136956:0.000354012:0.154902:0.869107:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869584 ES:SE:LP:AF:ID  -0.000126163:0.000354984:0.142668:0.869584:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838307 ES:SE:LP:AF:ID  -0.000328474:0.000329937:0.49485:0.838307:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838428 ES:SE:LP:AF:ID  -0.000325367:0.00033017:0.49485:0.838428:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862255 ES:SE:LP:AF:ID  -0.000254727:0.000352731:0.327902:0.862255:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706755 ES:SE:LP:AF:ID  -0.00020191:0.000343387:0.251812:0.706755:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105144 ES:SE:LP:AF:ID  0.000470575:0.000395575:0.638272:0.105144:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761297 ES:SE:LP:AF:ID  0.000301068:0.000280262:0.552842:0.761297:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.10649  ES:SE:LP:AF:ID  -0.00072443:0.000386289:1.21467:0.10649:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.12958  ES:SE:LP:AF:ID  0.000122635:0.000356209:0.136677:0.12958:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868906 ES:SE:LP:AF:ID  -0.000148179:0.000354306:0.167491:0.868906:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129681 ES:SE:LP:AF:ID  0.000149415:0.000355979:0.173925:0.129681:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868916 ES:SE:LP:AF:ID  -0.000140828:0.000354313:0.161151:0.868916:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265384 ES:SE:LP:AF:ID  -9.34253e-05:0.000313063:0.113509:0.265384:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.87004  ES:SE:LP:AF:ID  -0.000161774:0.000355036:0.187087:0.87004:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095141 ES:SE:LP:AF:ID  -0.000830716:0.00041148:1.35655:0.095141:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.12858  ES:SE:LP:AF:ID  0.000149802:0.000356438:0.173925:0.12858:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128877 ES:SE:LP:AF:ID  0.000154709:0.000355833:0.180456:0.128877:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.86878  ES:SE:LP:AF:ID  -0.00018424:0.000354088:0.221849:0.86878:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101872 ES:SE:LP:AF:ID  0.000581539:0.000401218:0.823909:0.101872:rs61768199