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-7418/UKB-b-7418_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7418/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7418/UKB-b-7418_data.vcf.gz ...
Read summary statistics for 5433263 SNPs.
Dropped 1936 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, 1166446 SNPs remain.
After merging with regression SNP LD, 1166446 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0006 (0.001)
Lambda GC: 1.0198
Mean Chi^2: 1.0197
Intercept: 1.0144 (0.0072)
Ratio: 0.7317 (0.3673)
Analysis finished at Thu Oct 17 14:41:48 2019
Total time elapsed: 1.0m:30.24s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9154,
    "inflation_factor": 1,
    "mean_EFFECT": 8.5023e-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": 47443,
    "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": 1166446,
    "ldsc_nsnp_merge_regression_ld": 1166446,
    "ldsc_observed_scale_h2_beta": 0.0006,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0144,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.0198,
    "ldsc_mean_chisq": 1.0197,
    "ldsc_ratio": 0.731
}

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 5431343 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 5433263 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 8.672876e+00 5.763444e+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 7.855499e+07 5.656641e+07 828.0000000 3.194710e+07 6.897284e+07 1.145027e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 9.000000e-07 3.608000e-04 -0.0032167 -2.234000e-04 1.000000e-07 2.240000e-04 3.524800e-03 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 3.454000e-04 9.290000e-05 0.0002449 2.677000e-04 3.109000e-04 4.022000e-04 1.158000e-03 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.969907e-01 2.892586e-01 0.0000004 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.969906e-01 2.892313e-01 0.0000004 2.454005e-01 4.954682e-01 7.471674e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 3.340536e-01 2.460805e-01 0.0498370 1.234510e-01 2.613590e-01 5.009030e-01 9.501630e-01 ▇▃▂▂▂
numeric AF_reference 47443 0.991268 NA NA NA NA NA NA NA 3.289673e-01 2.408637e-01 0.0000000 1.305910e-01 2.657750e-01 4.906150e-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 -0.0010781 0.0004507 0.0170000 0.0167502 0.623765 0.7821490 NA
1 54676 rs2462492 C T -0.0000714 0.0004465 0.8700001 0.8730148 0.400401 NA NA
1 86028 rs114608975 T C 0.0009708 0.0007138 0.1700000 0.1738221 0.103556 0.0277556 NA
1 91536 rs6702460 G T -0.0006652 0.0004396 0.1299999 0.1302129 0.456846 0.4207270 NA
1 234313 rs8179466 C T -0.0003498 0.0008668 0.6899999 0.6865545 0.074506 NA NA
1 534192 rs6680723 C T -0.0005882 0.0005022 0.2399999 0.2414511 0.240959 NA NA
1 546697 rs12025928 A G 0.0004966 0.0006265 0.4299995 0.4279320 0.913475 NA NA
1 693731 rs12238997 A G -0.0000739 0.0004208 0.8600001 0.8605796 0.116329 0.1417730 NA
1 705882 rs72631875 G A -0.0002682 0.0006167 0.6600001 0.6636581 0.067288 0.0315495 NA
1 706368 rs55727773 A G 0.0004767 0.0003117 0.1299999 0.1262144 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217954 rs9616974 G A 0.0003745 0.0004875 0.4400003 0.4423306 0.073312 0.0621006 NA
22 51218224 rs9616975 C A 0.0003781 0.0004877 0.4400003 0.4381547 0.073333 0.0619010 NA
22 51218377 rs2519461 G C 0.0003748 0.0004871 0.4400003 0.4415917 0.073622 0.0826677 NA
22 51219006 rs28729663 G A -0.0000713 0.0003760 0.8499999 0.8497110 0.137950 0.2052720 NA
22 51219387 rs9616832 T C 0.0003932 0.0004881 0.4199997 0.4204868 0.073744 0.0654952 NA
22 51221731 rs115055839 T C 0.0003781 0.0004884 0.4400003 0.4387994 0.073235 0.0625000 NA
22 51222100 rs114553188 G T -0.0007681 0.0005750 0.1800002 0.1816422 0.054460 0.0880591 NA
22 51223637 rs375798137 G A -0.0007753 0.0005778 0.1800002 0.1796517 0.054089 0.0788738 NA
22 51229805 rs9616985 T C 0.0003227 0.0004902 0.5099998 0.5102844 0.073071 0.0730831 NA
22 51237063 rs3896457 T C 0.0001179 0.0002998 0.6899999 0.6940864 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  -0.00107808:0.000450675:1.76955:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -7.1361e-05:0.00044648:0.0604807:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  0.000970825:0.000713829:0.769551:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.00066525:0.000439613:0.886057:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074506 ES:SE:LP:AF:ID  -0.00034979:0.000866814:0.161151:0.074506:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  -0.000588208:0.000502155:0.619789:0.240959:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  0.000496621:0.000626465:0.366532:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116329 ES:SE:LP:AF:ID  -7.39115e-05:0.000420821:0.0655015:0.116329:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  -0.000268168:0.000616665:0.180456:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  0.000476695:0.000311728:0.886057:0.515645:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.1012   ES:SE:LP:AF:ID  -0.000370399:0.000514332:0.327902:0.1012:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  0.000333671:0.000983196:0.136677:0.053255:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  -3.60209e-05:0.000364696:0.0362122:0.843204:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055912 ES:SE:LP:AF:ID  -0.000495324:0.000590502:0.39794:0.055912:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122312 ES:SE:LP:AF:ID  -0.000292581:0.000399191:0.337242:0.122312:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121554 ES:SE:LP:AF:ID  -0.000292204:0.000399359:0.337242:0.121554:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132335 ES:SE:LP:AF:ID  0.000102676:0.000393608:0.102373:0.132335:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  1.36231e-05:0.000353183:0.0132283:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838573 ES:SE:LP:AF:ID  9.19345e-06:0.000352804:0.00877392:0.838573:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  0.000361595:0.000378571:0.468521:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  -0.000368352:0.000379345:0.481486:0.129876:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  0.000362053:0.000377829:0.468521:0.869117:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  0.000357173:0.000377979:0.468521:0.869215:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  0.000365691:0.000377822:0.481486:0.869121:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838026 ES:SE:LP:AF:ID  5.06033e-05:0.000351824:0.05061:0.838026:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838657 ES:SE:LP:AF:ID  3.06372e-05:0.000352813:0.0315171:0.838657:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83977  ES:SE:LP:AF:ID  2.54891e-05:0.000357585:0.0268721:0.83977:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.8694   ES:SE:LP:AF:ID  0.000328734:0.000377385:0.420216:0.8694:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868947 ES:SE:LP:AF:ID  0.000352555:0.000376435:0.455932:0.868947:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867898 ES:SE:LP:AF:ID  0.000315591:0.000375713:0.39794:0.867898:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86909  ES:SE:LP:AF:ID  0.00034016:0.000376743:0.431798:0.86909:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869098 ES:SE:LP:AF:ID  0.000340104:0.000376772:0.431798:0.869098:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  0.000340013:0.000376781:0.431798:0.869106:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869584 ES:SE:LP:AF:ID  0.000331114:0.000377815:0.420216:0.869584:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838306 ES:SE:LP:AF:ID  5.09105e-05:0.000351157:0.0555173:0.838306:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838427 ES:SE:LP:AF:ID  5.85793e-05:0.000351405:0.0604807:0.838427:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862254 ES:SE:LP:AF:ID  0.000312602:0.000375418:0.387216:0.862254:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  0.000327821:0.000365471:0.431798:0.706753:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105145 ES:SE:LP:AF:ID  -0.000442497:0.000421016:0.537602:0.105145:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761297 ES:SE:LP:AF:ID  0.000199299:0.000298288:0.30103:0.761297:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.10649  ES:SE:LP:AF:ID  -4.57985e-05:0.000411134:0.0409586:0.10649:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129581 ES:SE:LP:AF:ID  -0.000334034:0.000379119:0.420216:0.129581:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868906 ES:SE:LP:AF:ID  0.000326318:0.000377094:0.408935:0.868906:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129682 ES:SE:LP:AF:ID  -0.000310872:0.000378874:0.387216:0.129682:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868916 ES:SE:LP:AF:ID  0.000333823:0.000377101:0.420216:0.868916:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265385 ES:SE:LP:AF:ID  -0.00031049:0.000333199:0.455932:0.265385:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870039 ES:SE:LP:AF:ID  0.000378255:0.00037787:0.49485:0.870039:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095141 ES:SE:LP:AF:ID  -0.000266654:0.000437945:0.267606:0.095141:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.12858  ES:SE:LP:AF:ID  -0.000356458:0.000379362:0.455932:0.12858:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128877 ES:SE:LP:AF:ID  -0.000358847:0.000378719:0.468521:0.128877:rs4040617