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-16862/UKB-b-16862_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16862/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16862/UKB-b-16862_data.vcf.gz ...
Read summary statistics for 5557856 SNPs.
Dropped 2101 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, 1178686 SNPs remain.
After merging with regression SNP LD, 1178686 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0005 (0.0011)
Lambda GC: 1.0483
Mean Chi^2: 1.0416
Intercept: 1.0368 (0.0072)
Ratio: 0.8856 (0.1732)
Analysis finished at Thu Oct 17 14:46:25 2019
Total time elapsed: 1.0m:5.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9176,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 8.7504e-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": 48923,
    "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": 1178686,
    "ldsc_nsnp_merge_regression_ld": 1178686,
    "ldsc_observed_scale_h2_beta": 0.0005,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0368,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.0483,
    "ldsc_mean_chisq": 1.0416,
    "ldsc_ratio": 0.8846
}

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 1.0000000 3 58 0 5555771 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 5557856 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 8.672421e+00 5.763226e+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 7.859105e+07 5.656234e+07 828.0000000 3.199614e+07 6.902244e+07 1.145206e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.000000e-07 3.882000e-04 -0.0032118 -2.392000e-04 -3.000000e-07 2.398000e-04 2.972000e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.677000e-04 1.040000e-04 0.0002564 2.810000e-04 3.286000e-04 4.305000e-04 1.212900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.941715e-01 2.902577e-01 0.0000015 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 4.941720e-01 2.902307e-01 0.0000015 2.418184e-01 4.912164e-01 7.464443e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.289903e-01 2.479024e-01 0.0457940 1.171480e-01 2.541470e-01 4.957660e-01 9.542060e-01 ▇▃▂▂▂
numeric AF_reference 48923 0.9911975 NA NA NA NA NA NA NA 3.243089e-01 2.422612e-01 0.0000000 1.250000e-01 2.593850e-01 4.856230e-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 0.0012067 0.0004719 0.0109999 0.0105478 0.623782 0.7821490 NA
1 54676 rs2462492 C T -0.0004548 0.0004676 0.3300000 0.3307069 0.400407 NA NA
1 86028 rs114608975 T C -0.0015581 0.0007475 0.0369999 0.0371323 0.103551 0.0277556 NA
1 91536 rs6702460 G T 0.0006773 0.0004603 0.1400000 0.1412137 0.456865 0.4207270 NA
1 234313 rs8179466 C T 0.0013446 0.0009076 0.1400000 0.1384724 0.074513 NA NA
1 534192 rs6680723 C T 0.0005121 0.0005258 0.3300000 0.3300645 0.240943 NA NA
1 546697 rs12025928 A G 0.0004511 0.0006560 0.4899999 0.4917031 0.913476 NA NA
1 693731 rs12238997 A G 0.0002278 0.0004407 0.6100002 0.6052740 0.116318 0.1417730 NA
1 705882 rs72631875 G A -0.0002496 0.0006457 0.6999999 0.6990240 0.067304 0.0315495 NA
1 706368 rs55727773 A G -0.0000215 0.0003265 0.9500000 0.9474137 0.515675 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218224 rs9616975 C A 0.0007431 0.0005107 0.1499999 0.1456403 0.073320 0.0619010 NA
22 51218377 rs2519461 G C 0.0007111 0.0005101 0.1600000 0.1632932 0.073608 0.0826677 NA
22 51219006 rs28729663 G A 0.0002409 0.0003938 0.5400003 0.5407046 0.137945 0.2052720 NA
22 51219387 rs9616832 T C 0.0007644 0.0005111 0.1299999 0.1347379 0.073732 0.0654952 NA
22 51221190 rs369304721 G A 0.0011600 0.0006837 0.0899995 0.0897653 0.049727 NA NA
22 51221731 rs115055839 T C 0.0007215 0.0005114 0.1600000 0.1583180 0.073222 0.0625000 NA
22 51222100 rs114553188 G T -0.0007932 0.0006021 0.1900002 0.1877130 0.054462 0.0880591 NA
22 51223637 rs375798137 G A -0.0008559 0.0006050 0.1600000 0.1571626 0.054091 0.0788738 NA
22 51229805 rs9616985 T C 0.0007528 0.0005133 0.1400000 0.1424734 0.073059 0.0730831 NA
22 51237063 rs3896457 T C 0.0001296 0.0003139 0.6800001 0.6797450 0.297981 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623782 ES:SE:LP:AF:ID  0.00120674:0.000471874:1.95861:0.623782:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  -0.000454806:0.000467575:0.481486:0.400407:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103551 ES:SE:LP:AF:ID  -0.0015581:0.000747539:1.4318:0.103551:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456865 ES:SE:LP:AF:ID  0.000677264:0.000460321:0.853872:0.456865:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074513 ES:SE:LP:AF:ID  0.00134458:0.000907578:0.853872:0.074513:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240943 ES:SE:LP:AF:ID  0.00051215:0.00052583:0.481486:0.240943:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  0.000451057:0.000655985:0.309804:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116318 ES:SE:LP:AF:ID  0.000227768:0.000440701:0.21467:0.116318:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067304 ES:SE:LP:AF:ID  -0.000249645:0.000645681:0.154902:0.067304:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515675 ES:SE:LP:AF:ID  -2.15312e-05:0.000326453:0.0222764:0.515675:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101209 ES:SE:LP:AF:ID  -0.000969434:0.000538565:1.14267:0.101209:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.05327  ES:SE:LP:AF:ID  -0.000130403:0.00102918:0.0457575:0.05327:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843205 ES:SE:LP:AF:ID  -3.41138e-05:0.000381907:0.0315171:0.843205:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055909 ES:SE:LP:AF:ID  0.000189331:0.000618391:0.119186:0.055909:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122308 ES:SE:LP:AF:ID  0.000293291:0.000418039:0.318759:0.122308:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12155  ES:SE:LP:AF:ID  0.000265371:0.000418214:0.275724:0.12155:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132328 ES:SE:LP:AF:ID  -9.58744e-05:0.000412199:0.0861861:0.132328:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838944 ES:SE:LP:AF:ID  -4.76971e-05:0.000369849:0.0457575:0.838944:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838571 ES:SE:LP:AF:ID  -7.27304e-05:0.000369449:0.0757207:0.838571:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869778 ES:SE:LP:AF:ID  -0.000260063:0.00039644:0.29243:0.869778:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  0.000314183:0.000397243:0.366532:0.129876:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  -0.000271587:0.00039566:0.309804:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  -0.000265688:0.000395816:0.30103:0.869216:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  -0.000272649:0.000395653:0.309804:0.869122:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838024 ES:SE:LP:AF:ID  -5.47154e-05:0.000368424:0.0555173:0.838024:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838654 ES:SE:LP:AF:ID  -5.40401e-05:0.000369458:0.0555173:0.838654:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83977  ES:SE:LP:AF:ID  -6.75937e-05:0.000374458:0.0655015:0.83977:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869403 ES:SE:LP:AF:ID  -0.000280716:0.000395199:0.318759:0.869403:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  -0.000325959:0.000394207:0.387216:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867902 ES:SE:LP:AF:ID  -0.000404907:0.000393447:0.522879:0.867902:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  -0.00030427:0.000394529:0.356547:0.869095:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  -0.00030363:0.000394559:0.356547:0.869103:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869111 ES:SE:LP:AF:ID  -0.00030161:0.000394568:0.356547:0.869111:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869587 ES:SE:LP:AF:ID  -0.000269695:0.000395648:0.30103:0.869587:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838304 ES:SE:LP:AF:ID  -3.07901e-05:0.000367722:0.0315171:0.838304:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838425 ES:SE:LP:AF:ID  -3.5549e-05:0.000367982:0.0362122:0.838425:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862258 ES:SE:LP:AF:ID  -0.000301426:0.000393136:0.356547:0.862258:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706761 ES:SE:LP:AF:ID  -0.000145784:0.000382722:0.154902:0.706761:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105125 ES:SE:LP:AF:ID  9.38035e-05:0.00044092:0.0809219:0.105125:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761343 ES:SE:LP:AF:ID  -0.000636165:0.000312389:1.37675:0.761343:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106452 ES:SE:LP:AF:ID  0.000769777:0.000430585:1.13077:0.106452:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129572 ES:SE:LP:AF:ID  0.000282783:0.000397017:0.318759:0.129572:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868913 ES:SE:LP:AF:ID  -0.000329782:0.000394898:0.39794:0.868913:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129673 ES:SE:LP:AF:ID  0.000331907:0.00039676:0.39794:0.129673:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868924 ES:SE:LP:AF:ID  -0.000332528:0.000394907:0.39794:0.868924:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265365 ES:SE:LP:AF:ID  -2.68306e-05:0.000348908:0.0268721:0.265365:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870042 ES:SE:LP:AF:ID  -0.000310806:0.000395709:0.366532:0.870042:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095112 ES:SE:LP:AF:ID  0.000855665:0.000458656:1.20761:0.095112:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128574 ES:SE:LP:AF:ID  0.000334986:0.000397269:0.39794:0.128574:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128872 ES:SE:LP:AF:ID  0.00033206:0.000396593:0.39794:0.128872:rs4040617