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-6614/UKB-b-6614_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6614/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-6614/UKB-b-6614_data.vcf.gz ...
Read summary statistics for 5339540 SNPs.
Dropped 1816 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, 1156417 SNPs remain.
After merging with regression SNP LD, 1156417 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0031 (0.0013)
Lambda GC: 1.05
Mean Chi^2: 1.0525
Intercept: 1.0237 (0.008)
Ratio: 0.451 (0.1515)
Analysis finished at Thu Oct 17 14:41:22 2019
Total time elapsed: 1.0m:2.77s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9136,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -1.0944e-06,
    "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": 46380,
    "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": 1156417,
    "ldsc_nsnp_merge_regression_ld": 1156417,
    "ldsc_observed_scale_h2_beta": 0.0031,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0237,
    "ldsc_intercept_se": 0.008,
    "ldsc_lambda_gc": 1.05,
    "ldsc_mean_chisq": 1.0525,
    "ldsc_ratio": 0.4514
}

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 5337738 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 5339540 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 8.673127e+00 5.762893e+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 7.853187e+07 5.656447e+07 828.0000000 3.191960e+07 6.895150e+07 1.144739e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.100000e-06 3.646000e-04 -0.0026771 -2.295000e-04 -1.600000e-06 2.267000e-04 2.776700e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.450000e-04 8.920000e-05 0.0002475 2.701000e-04 3.121000e-04 4.000000e-04 1.170700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.915004e-01 2.907030e-01 0.0000001 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 4.915028e-01 2.906766e-01 0.0000001 2.379572e-01 4.881777e-01 7.432582e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.377596e-01 2.445157e-01 0.0530230 1.281710e-01 2.665830e-01 5.045330e-01 9.469770e-01 ▇▃▂▂▂
numeric AF_reference 46380 0.9913139 NA NA NA NA NA NA NA 3.323633e-01 2.396905e-01 0.0000000 1.347840e-01 2.705670e-01 4.942090e-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 0.0006987 0.0004554 0.1199999 0.1249406 0.623776 0.7821490 NA
1 54676 rs2462492 C T 0.0001535 0.0004512 0.7300002 0.7337607 0.400414 NA NA
1 86028 rs114608975 T C -0.0018058 0.0007214 0.0120000 0.0123035 0.103532 0.0277556 NA
1 91536 rs6702460 G T 0.0011915 0.0004441 0.0073000 0.0073028 0.456872 0.4207270 NA
1 234313 rs8179466 C T 0.0012694 0.0008765 0.1499999 0.1475304 0.074441 NA NA
1 534192 rs6680723 C T 0.0001909 0.0005074 0.7099994 0.7067829 0.240926 NA NA
1 546697 rs12025928 A G 0.0000694 0.0006331 0.9100000 0.9126759 0.913495 NA NA
1 693731 rs12238997 A G -0.0002053 0.0004254 0.6300007 0.6293151 0.116352 0.1417730 NA
1 705882 rs72631875 G A -0.0003333 0.0006232 0.5900000 0.5928176 0.067325 0.0315495 NA
1 706368 rs55727773 A G -0.0000399 0.0003151 0.9000000 0.8993075 0.515702 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217954 rs9616974 G A 0.0003547 0.0004924 0.4700002 0.4713328 0.073364 0.0621006 NA
22 51218224 rs9616975 C A 0.0003525 0.0004926 0.4700002 0.4742946 0.073386 0.0619010 NA
22 51218377 rs2519461 G C 0.0002988 0.0004920 0.5400003 0.5436838 0.073667 0.0826677 NA
22 51219006 rs28729663 G A -0.0000272 0.0003799 0.9400001 0.9428294 0.138022 0.2052720 NA
22 51219387 rs9616832 T C 0.0003622 0.0004930 0.4600002 0.4625109 0.073796 0.0654952 NA
22 51221731 rs115055839 T C 0.0003268 0.0004933 0.5099998 0.5076507 0.073290 0.0625000 NA
22 51222100 rs114553188 G T -0.0009055 0.0005810 0.1199999 0.1191118 0.054500 0.0880591 NA
22 51223637 rs375798137 G A -0.0009318 0.0005838 0.1100001 0.1104577 0.054128 0.0788738 NA
22 51229805 rs9616985 T C 0.0003599 0.0004951 0.4700002 0.4672174 0.073128 0.0730831 NA
22 51237063 rs3896457 T C 0.0002935 0.0003029 0.3300000 0.3326018 0.298180 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623776 ES:SE:LP:AF:ID  0.00069873:0.000455388:0.920819:0.623776:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400414 ES:SE:LP:AF:ID  0.000153461:0.000451187:0.136677:0.400414:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103532 ES:SE:LP:AF:ID  -0.00180577:0.000721351:1.92082:0.103532:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456872 ES:SE:LP:AF:ID  0.00119148:0.000444133:2.13668:0.456872:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074441 ES:SE:LP:AF:ID  0.00126939:0.000876463:0.823909:0.074441:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240926 ES:SE:LP:AF:ID  0.000190872:0.000507395:0.148742:0.240926:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913495 ES:SE:LP:AF:ID  6.94331e-05:0.000633144:0.0409586:0.913495:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116352 ES:SE:LP:AF:ID  -0.000205316:0.000425357:0.200659:0.116352:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067325 ES:SE:LP:AF:ID  -0.000333271:0.000623219:0.229148:0.067325:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515702 ES:SE:LP:AF:ID  -3.98655e-05:0.000315052:0.0457575:0.515702:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101252 ES:SE:LP:AF:ID  -0.00019496:0.00051974:0.148742:0.101252:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053317 ES:SE:LP:AF:ID  0.00103892:0.000992197:0.522879:0.053317:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843145 ES:SE:LP:AF:ID  0.00044772:0.000368603:0.657577:0.843145:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055899 ES:SE:LP:AF:ID  -0.000569631:0.000596912:0.468521:0.055899:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12234  ES:SE:LP:AF:ID  -0.000175753:0.000403442:0.180456:0.12234:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121582 ES:SE:LP:AF:ID  -0.000205153:0.000403609:0.21467:0.121582:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132402 ES:SE:LP:AF:ID  -0.000536856:0.000397748:0.744727:0.132402:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838835 ES:SE:LP:AF:ID  0.000391814:0.000356874:0.568636:0.838835:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838456 ES:SE:LP:AF:ID  0.000364421:0.000356476:0.508638:0.838456:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869707 ES:SE:LP:AF:ID  0.000194084:0.000382528:0.21467:0.869707:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129959 ES:SE:LP:AF:ID  -0.000161821:0.000383287:0.173925:0.129959:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869046 ES:SE:LP:AF:ID  0.000186356:0.000381767:0.200659:0.869046:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869146 ES:SE:LP:AF:ID  0.000193408:0.000381922:0.21467:0.869146:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869049 ES:SE:LP:AF:ID  0.000185089:0.00038176:0.200659:0.869049:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837905 ES:SE:LP:AF:ID  0.000369115:0.000355483:0.522879:0.837905:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838536 ES:SE:LP:AF:ID  0.000384806:0.000356482:0.552842:0.838536:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839657 ES:SE:LP:AF:ID  0.000399586:0.00036132:0.568636:0.839657:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869336 ES:SE:LP:AF:ID  0.000161117:0.00038134:0.173925:0.869336:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868888 ES:SE:LP:AF:ID  0.000116593:0.000380398:0.119186:0.868888:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867831 ES:SE:LP:AF:ID  4.70318e-05:0.000379645:0.0457575:0.867831:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869027 ES:SE:LP:AF:ID  0.000140154:0.000380702:0.148742:0.869027:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869036 ES:SE:LP:AF:ID  0.000141727:0.000380731:0.148742:0.869036:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869044 ES:SE:LP:AF:ID  0.000143092:0.00038074:0.148742:0.869044:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869519 ES:SE:LP:AF:ID  0.000178752:0.000381772:0.19382:0.869519:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838191 ES:SE:LP:AF:ID  0.000400845:0.000354824:0.585027:0.838191:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.83831  ES:SE:LP:AF:ID  0.000395058:0.000355075:0.568636:0.83831:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862188 ES:SE:LP:AF:ID  0.00015058:0.000379378:0.161151:0.862188:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706672 ES:SE:LP:AF:ID  0.000282101:0.000369338:0.356547:0.706672:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105166 ES:SE:LP:AF:ID  -0.000307174:0.000425497:0.327902:0.105166:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761329 ES:SE:LP:AF:ID  -0.000274883:0.000301578:0.443698:0.761329:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106407 ES:SE:LP:AF:ID  0.000640122:0.000415728:0.920819:0.106407:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129645 ES:SE:LP:AF:ID  -0.000154529:0.000383106:0.161151:0.129645:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.86885  ES:SE:LP:AF:ID  0.00013613:0.000381063:0.142668:0.86885:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129745 ES:SE:LP:AF:ID  -0.000124303:0.000382857:0.124939:0.129745:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.86886  ES:SE:LP:AF:ID  0.000134855:0.000381071:0.142668:0.86886:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265285 ES:SE:LP:AF:ID  0.000323305:0.0003368:0.468521:0.265285:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870008 ES:SE:LP:AF:ID  0.0001665:0.000381876:0.180456:0.870008:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095093 ES:SE:LP:AF:ID  0.000822938:0.000442745:1.20066:0.095093:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128612 ES:SE:LP:AF:ID  -0.000150353:0.000383383:0.161151:0.128612:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128907 ES:SE:LP:AF:ID  -0.000160679:0.000382739:0.173925:0.128907:rs4040617