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-17814/UKB-b-17814_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17814/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:28 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17814/UKB-b-17814_data.vcf.gz ...
Read summary statistics for 5795029 SNPs.
Dropped 2470 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, 1199459 SNPs remain.
After merging with regression SNP LD, 1199459 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0018 (0.0012)
Lambda GC: 1.0241
Mean Chi^2: 1.0299
Intercept: 1.0142 (0.0074)
Ratio: 0.4742 (0.2469)
Analysis finished at Thu Oct 17 14:41:40 2019
Total time elapsed: 1.0m:11.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9215,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 3.1584e-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": 51815,
    "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": 1199459,
    "ldsc_nsnp_merge_regression_ld": 1199459,
    "ldsc_observed_scale_h2_beta": 0.0018,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0142,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.0241,
    "ldsc_mean_chisq": 1.0299,
    "ldsc_ratio": 0.4749
}

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 5792575 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 5795029 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 8.670182e+00 5.762424e+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 7.859614e+07 5.654172e+07 828.0000000 3.199496e+07 6.904133e+07 1.145151e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.200000e-06 4.759000e-04 -0.0039061 -2.868000e-04 -9.000000e-07 2.882000e-04 3.933000e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.465000e-04 1.387000e-04 0.0003013 3.317000e-04 3.934000e-04 5.287000e-04 1.443500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.946054e-01 2.902102e-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 4.946058e-01 2.901834e-01 0.0000015 2.415375e-01 4.936000e-01 7.459466e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.195983e-01 2.510193e-01 0.0389280 1.060820e-01 2.408890e-01 4.857680e-01 9.610720e-01 ▇▃▂▂▁
numeric AF_reference 51815 0.9910587 NA NA NA NA NA NA NA 3.155782e-01 2.446699e-01 0.0000000 1.144170e-01 2.474040e-01 4.758390e-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 0.0009568 0.0005547 0.0850002 0.0845836 0.623787 0.7821490 NA
1 54676 rs2462492 C T -0.0009490 0.0005497 0.0840001 0.0842586 0.400358 NA NA
1 86028 rs114608975 T C -0.0005082 0.0008783 0.5600000 0.5628000 0.103536 0.0277556 NA
1 91536 rs6702460 G T -0.0004430 0.0005411 0.4100001 0.4130019 0.456805 0.4207270 NA
1 234313 rs8179466 C T -0.0002255 0.0010676 0.8300000 0.8327281 0.074505 NA NA
1 534192 rs6680723 C T -0.0000291 0.0006178 0.9599999 0.9624846 0.241007 NA NA
1 546697 rs12025928 A G -0.0013048 0.0007712 0.0909997 0.0906585 0.913444 NA NA
1 693731 rs12238997 A G -0.0003144 0.0005179 0.5400003 0.5437266 0.116352 0.1417730 NA
1 705882 rs72631875 G A 0.0004635 0.0007588 0.5400003 0.5412917 0.067304 0.0315495 NA
1 706368 rs55727773 A G 0.0003917 0.0003836 0.3100002 0.3071702 0.515345 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0010503 0.0005994 0.0800000 0.0797364 0.073626 0.0826677 NA
22 51219006 rs28729663 G A 0.0005232 0.0004629 0.2599998 0.2584231 0.137898 0.2052720 NA
22 51219387 rs9616832 T C 0.0010582 0.0006006 0.0779992 0.0781023 0.073752 0.0654952 NA
22 51219704 rs147475742 G A 0.0006312 0.0008055 0.4299995 0.4332563 0.041907 0.0473243 NA
22 51221190 rs369304721 G A 0.0017731 0.0008037 0.0269998 0.0273806 0.049707 NA NA
22 51221731 rs115055839 T C 0.0010496 0.0006011 0.0810009 0.0807753 0.073232 0.0625000 NA
22 51222100 rs114553188 G T -0.0005836 0.0007078 0.4100001 0.4096647 0.054446 0.0880591 NA
22 51223637 rs375798137 G A -0.0005696 0.0007113 0.4199997 0.4232645 0.054076 0.0788738 NA
22 51229805 rs9616985 T C 0.0010291 0.0006033 0.0879995 0.0880267 0.073063 0.0730831 NA
22 51237063 rs3896457 T C -0.0003236 0.0003691 0.3800004 0.3806403 0.297825 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623787 ES:SE:LP:AF:ID  0.000956764:0.000554746:1.07058:0.623787:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400358 ES:SE:LP:AF:ID  -0.000949014:0.000549677:1.07572:0.400358:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  -0.000508233:0.000878251:0.251812:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456805 ES:SE:LP:AF:ID  -0.000442995:0.000541147:0.387216:0.456805:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074505 ES:SE:LP:AF:ID  -0.000225492:0.00106765:0.0809219:0.074505:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241007 ES:SE:LP:AF:ID  -2.90569e-05:0.000617759:0.0177288:0.241007:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913444 ES:SE:LP:AF:ID  -0.00130484:0.000771212:1.04096:0.913444:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116352 ES:SE:LP:AF:ID  -0.000314435:0.000517855:0.267606:0.116352:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067304 ES:SE:LP:AF:ID  0.000463506:0.000758775:0.267606:0.067304:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515345 ES:SE:LP:AF:ID  0.000391686:0.000383563:0.508638:0.515345:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101297 ES:SE:LP:AF:ID  0.000107166:0.000632396:0.0604807:0.101297:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958938 ES:SE:LP:AF:ID  -0.00105628:0.000836428:0.677781:0.958938:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053199 ES:SE:LP:AF:ID  -0.00214556:0.00121066:1.11919:0.053199:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.842982 ES:SE:LP:AF:ID  1.63706e-05:0.000448564:0.0132283:0.842982:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055967 ES:SE:LP:AF:ID  -0.00133708:0.000726533:1.18046:0.055967:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122374 ES:SE:LP:AF:ID  -0.000476881:0.000491119:0.481486:0.122374:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121616 ES:SE:LP:AF:ID  -0.000455361:0.000491325:0.455932:0.121616:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132519 ES:SE:LP:AF:ID  0.000132964:0.000484062:0.107905:0.132519:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838683 ES:SE:LP:AF:ID  -0.000105426:0.000434321:0.091515:0.838683:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838322 ES:SE:LP:AF:ID  -8.76092e-05:0.00043386:0.0757207:0.838322:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869666 ES:SE:LP:AF:ID  0.000380705:0.000465705:0.387216:0.869666:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129949 ES:SE:LP:AF:ID  -0.000404952:0.000466688:0.408935:0.129949:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869023 ES:SE:LP:AF:ID  0.000418251:0.000464815:0.431798:0.869023:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869125 ES:SE:LP:AF:ID  0.000430812:0.000464999:0.455932:0.869125:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869026 ES:SE:LP:AF:ID  0.000417343:0.000464801:0.431798:0.869026:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837777 ES:SE:LP:AF:ID  -6.21169e-05:0.000432657:0.05061:0.837777:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838408 ES:SE:LP:AF:ID  -2.05759e-05:0.000433872:0.0177288:0.838408:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839539 ES:SE:LP:AF:ID  0.000120454:0.00043978:0.107905:0.839539:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869292 ES:SE:LP:AF:ID  0.000370182:0.000464247:0.366532:0.869292:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868839 ES:SE:LP:AF:ID  0.000384108:0.000463072:0.387216:0.868839:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867806 ES:SE:LP:AF:ID  0.000377793:0.000462202:0.387216:0.867806:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868982 ES:SE:LP:AF:ID  0.00036796:0.000463456:0.366532:0.868982:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86899  ES:SE:LP:AF:ID  0.00036897:0.000463492:0.366532:0.86899:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868999 ES:SE:LP:AF:ID  0.000368754:0.000463503:0.366532:0.868999:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869475 ES:SE:LP:AF:ID  0.000367467:0.000464776:0.366532:0.869475:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838035 ES:SE:LP:AF:ID  -5.58114e-05:0.000431822:0.0457575:0.838035:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838156 ES:SE:LP:AF:ID  -5.44133e-05:0.000432126:0.0457575:0.838156:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862125 ES:SE:LP:AF:ID  0.000263517:0.000461839:0.244125:0.862125:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706748 ES:SE:LP:AF:ID  0.000321644:0.000449655:0.327902:0.706748:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.10518  ES:SE:LP:AF:ID  -0.000529311:0.000518004:0.508638:0.10518:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.7611   ES:SE:LP:AF:ID  0.000312791:0.00036695:0.408935:0.7611:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106574 ES:SE:LP:AF:ID  -0.000101015:0.000505834:0.0757207:0.106574:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129671 ES:SE:LP:AF:ID  -0.000383449:0.000466385:0.387216:0.129671:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868791 ES:SE:LP:AF:ID  0.000383622:0.000463897:0.387216:0.868791:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129778 ES:SE:LP:AF:ID  -0.000385612:0.000466089:0.387216:0.129778:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868802 ES:SE:LP:AF:ID  0.000380672:0.000463908:0.387216:0.868802:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265205 ES:SE:LP:AF:ID  0.000336597:0.000410027:0.387216:0.265205:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869923 ES:SE:LP:AF:ID  0.000359084:0.000464856:0.356547:0.869923:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095222 ES:SE:LP:AF:ID  -7.02463e-05:0.000538772:0.0457575:0.095222:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.12868  ES:SE:LP:AF:ID  -0.000361932:0.000466673:0.356547:0.12868:rs1055606