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-8893/UKB-b-8893_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8893/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8893/UKB-b-8893_data.vcf.gz ...
Read summary statistics for 5323244 SNPs.
Dropped 1794 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, 1154918 SNPs remain.
After merging with regression SNP LD, 1154918 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0274 (0.0144)
Lambda GC: 1.0108
Mean Chi^2: 1.0183
Intercept: 1.0004 (0.0075)
Ratio: 0.0233 (0.4078)
Analysis finished at Thu Oct 17 14:43:05 2019
Total time elapsed: 58.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9137,
    "inflation_factor": 1,
    "mean_EFFECT": 3.7657e-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": 46189,
    "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": 1154918,
    "ldsc_nsnp_merge_regression_ld": 1154918,
    "ldsc_observed_scale_h2_beta": 0.0274,
    "ldsc_observed_scale_h2_se": 0.0144,
    "ldsc_intercept_beta": 1.0004,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.0108,
    "ldsc_mean_chisq": 1.0183,
    "ldsc_ratio": 0.0219
}

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 5321463 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 5323244 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 8.673116e+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 7.853510e+07 5.657503e+07 828.0000000 3.190936e+07 6.894415e+07 1.145035e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.800000e-06 4.538700e-03 -0.0343961 -2.829400e-03 -5.500000e-06 2.830800e-03 3.905530e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.351900e-03 1.116800e-03 0.0031178 3.414000e-03 3.941200e-03 5.042500e-03 1.494820e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.965040e-01 2.893218e-01 0.0000002 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.965032e-01 2.892955e-01 0.0000002 2.454727e-01 4.956509e-01 7.464957e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.384445e-01 2.441529e-01 0.0536570 1.290420e-01 2.675380e-01 5.052690e-01 9.463430e-01 ▇▃▂▂▂
numeric AF_reference 46189 0.9913231 NA NA NA NA NA NA NA 3.330363e-01 2.394398e-01 0.0000000 1.357830e-01 2.713660e-01 4.950080e-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 0.0004359 0.0057531 0.9400001 0.9396017 0.623710 0.7821490 NA
1 54676 rs2462492 C T -0.0035799 0.0057255 0.5300002 0.5318066 0.399162 NA NA
1 86028 rs114608975 T C -0.0012529 0.0090599 0.8900000 0.8900102 0.103756 0.0277556 NA
1 91536 rs6702460 G T -0.0022860 0.0056297 0.6800001 0.6847022 0.455304 0.4207270 NA
1 234313 rs8179466 C T 0.0005903 0.0111911 0.9599999 0.9579328 0.073691 NA NA
1 534192 rs6680723 C T -0.0074596 0.0064558 0.2500000 0.2478947 0.240720 NA NA
1 546697 rs12025928 A G -0.0175568 0.0079814 0.0280001 0.0278270 0.912539 NA NA
1 693731 rs12238997 A G 0.0002076 0.0053633 0.9699999 0.9691168 0.118189 0.1417730 NA
1 705882 rs72631875 G A 0.0141761 0.0078368 0.0700003 0.0704650 0.068040 0.0315495 NA
1 706368 rs55727773 A G -0.0029944 0.0039829 0.4500005 0.4521720 0.513640 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217954 rs9616974 G A 0.0165962 0.0062508 0.0079001 0.0079292 0.072868 0.0621006 NA
22 51218224 rs9616975 C A 0.0166342 0.0062535 0.0077999 0.0078143 0.072874 0.0619010 NA
22 51218377 rs2519461 G C 0.0170031 0.0062390 0.0064000 0.0064246 0.073259 0.0826677 NA
22 51219006 rs28729663 G A 0.0092912 0.0048104 0.0530005 0.0534250 0.138957 0.2052720 NA
22 51219387 rs9616832 T C 0.0159195 0.0062566 0.0109999 0.0109457 0.073345 0.0654952 NA
22 51221731 rs115055839 T C 0.0170178 0.0062626 0.0065999 0.0065802 0.072770 0.0625000 NA
22 51222100 rs114553188 G T -0.0028088 0.0073077 0.6999999 0.7007091 0.055203 0.0880591 NA
22 51223637 rs375798137 G A -0.0030983 0.0073435 0.6700003 0.6730897 0.054822 0.0788738 NA
22 51229805 rs9616985 T C 0.0173958 0.0062884 0.0056999 0.0056692 0.072555 0.0730831 NA
22 51237063 rs3896457 T C -0.0052551 0.0038586 0.1700000 0.1732282 0.295451 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62371  ES:SE:LP:AF:ID  0.000435912:0.00575306:0.0268721:0.62371:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399162 ES:SE:LP:AF:ID  -0.00357986:0.00572548:0.275724:0.399162:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103756 ES:SE:LP:AF:ID  -0.0012529:0.00905986:0.05061:0.103756:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455304 ES:SE:LP:AF:ID  -0.00228596:0.00562968:0.167491:0.455304:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.073691 ES:SE:LP:AF:ID  0.000590306:0.0111911:0.0177288:0.073691:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24072  ES:SE:LP:AF:ID  -0.00745957:0.00645583:0.60206:0.24072:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912539 ES:SE:LP:AF:ID  -0.0175568:0.00798139:1.55284:0.912539:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.118189 ES:SE:LP:AF:ID  0.000207645:0.00536328:0.0132283:0.118189:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06804  ES:SE:LP:AF:ID  0.0141761:0.00783682:1.1549:0.06804:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51364  ES:SE:LP:AF:ID  -0.00299437:0.00398294:0.346787:0.51364:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.100278 ES:SE:LP:AF:ID  0.00922835:0.00659734:0.79588:0.100278:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.840353 ES:SE:LP:AF:ID  0.00359167:0.00463578:0.356547:0.840353:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056243 ES:SE:LP:AF:ID  -0.00804287:0.00756277:0.537602:0.056243:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124107 ES:SE:LP:AF:ID  -0.00172869:0.00509681:0.136677:0.124107:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.123373 ES:SE:LP:AF:ID  -0.00212083:0.00509892:0.167491:0.123373:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134053 ES:SE:LP:AF:ID  -0.00357036:0.00502901:0.318759:0.134053:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.835828 ES:SE:LP:AF:ID  0.00266163:0.00450126:0.259637:0.835828:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.835345 ES:SE:LP:AF:ID  0.00205518:0.00449324:0.187087:0.835345:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.866915 ES:SE:LP:AF:ID  0.00123188:0.00481636:0.09691:0.866915:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.132666 ES:SE:LP:AF:ID  -0.000920562:0.00482866:0.0705811:0.132666:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.866153 ES:SE:LP:AF:ID  0.000687601:0.00480402:0.05061:0.866153:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.866318 ES:SE:LP:AF:ID  0.000685481:0.00480664:0.05061:0.866318:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86615  ES:SE:LP:AF:ID  0.000581679:0.00480358:0.0457575:0.86615:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.834923 ES:SE:LP:AF:ID  0.00246022:0.00448599:0.236572:0.834923:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.835586 ES:SE:LP:AF:ID  0.00250303:0.00449956:0.236572:0.835586:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.836772 ES:SE:LP:AF:ID  0.00258622:0.00455798:0.244125:0.836772:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.866643 ES:SE:LP:AF:ID  0.00119738:0.00480196:0.09691:0.866643:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.866271 ES:SE:LP:AF:ID  0.00142692:0.00479035:0.113509:0.866271:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.864793 ES:SE:LP:AF:ID  0.000884249:0.00477431:0.0705811:0.864793:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866378 ES:SE:LP:AF:ID  0.0013557:0.00479464:0.107905:0.866378:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866402 ES:SE:LP:AF:ID  0.00133649:0.00479495:0.107905:0.866402:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866407 ES:SE:LP:AF:ID  0.00133309:0.00479506:0.107905:0.866407:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86679  ES:SE:LP:AF:ID  0.00131254:0.00480752:0.107905:0.86679:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.835422 ES:SE:LP:AF:ID  0.00324943:0.00447991:0.327902:0.835422:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.835566 ES:SE:LP:AF:ID  0.00316731:0.00448319:0.318759:0.835566:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.859182 ES:SE:LP:AF:ID  0.000991672:0.00477303:0.0757207:0.859182:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705081 ES:SE:LP:AF:ID  0.00260179:0.00465499:0.236572:0.705081:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106752 ES:SE:LP:AF:ID  -0.0016446:0.00537698:0.119186:0.106752:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.756826 ES:SE:LP:AF:ID  0.00140464:0.00379116:0.148742:0.756826:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108264 ES:SE:LP:AF:ID  -0.000513779:0.00519423:0.0362122:0.108264:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.131879 ES:SE:LP:AF:ID  -0.00123282:0.00483534:0.09691:0.131879:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.866392 ES:SE:LP:AF:ID  0.00159849:0.00480135:0.130768:0.866392:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.131995 ES:SE:LP:AF:ID  -0.00174368:0.00483083:0.142668:0.131995:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.866394 ES:SE:LP:AF:ID  0.0016095:0.0048012:0.130768:0.866394:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.264497 ES:SE:LP:AF:ID  -0.00526853:0.00428284:0.657577:0.264497:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.868007 ES:SE:LP:AF:ID  0.00283978:0.00481768:0.251812:0.868007:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.096795 ES:SE:LP:AF:ID  0.00145344:0.00554445:0.102373:0.096795:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.130462 ES:SE:LP:AF:ID  -0.0031882:0.00484179:0.29243:0.130462:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.130808 ES:SE:LP:AF:ID  -0.00325394:0.00483233:0.30103:0.130808:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.866654 ES:SE:LP:AF:ID  0.00205012:0.00480075:0.173925:0.866654:rs2977612