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-1852/UKB-b-1852_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1852/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-1852/UKB-b-1852_data.vcf.gz ...
Read summary statistics for 5758454 SNPs.
Dropped 2419 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, 1196508 SNPs remain.
After merging with regression SNP LD, 1196508 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0032 (0.0014)
Lambda GC: 1.0644
Mean Chi^2: 1.0749
Intercept: 1.0444 (0.0076)
Ratio: 0.5932 (0.1018)
Analysis finished at Thu Oct 17 14:41:24 2019
Total time elapsed: 1.0m:4.98s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.921,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 4.7085e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 164,
    "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": 51400,
    "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": 1196508,
    "ldsc_nsnp_merge_regression_ld": 1196508,
    "ldsc_observed_scale_h2_beta": 0.0032,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0444,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.0644,
    "ldsc_mean_chisq": 1.0749,
    "ldsc_ratio": 0.5928
}

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 5756051 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 5758454 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 8.670280e+00 5.762471e+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 7.860051e+07 5.654908e+07 828.0000000 3.199876e+07 6.903535e+07 1.145279e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 5.000000e-07 4.385000e-04 -0.0031976 -2.645000e-04 -1.000000e-07 2.657000e-04 4.071700e-03 ▁▂▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 4.045000e-04 1.239000e-04 0.0002744 3.018000e-04 3.571000e-04 4.780000e-04 1.315400e-03 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.890336e-01 2.919688e-01 0.0000000 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.890354e-01 2.919442e-01 0.0000000 2.331346e-01 4.855816e-01 7.419365e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 3.210434e-01 2.505800e-01 0.0399270 1.077212e-01 2.428920e-01 4.872928e-01 9.600720e-01 ▇▃▂▂▁
numeric AF_reference 51400 0.991074 NA NA NA NA NA NA NA 3.169137e-01 2.443295e-01 0.0000000 1.160140e-01 2.492010e-01 4.774360e-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 0.0000685 0.0005049 0.8900000 0.8920924 0.623772 0.7821490 NA
1 54676 rs2462492 C T 0.0001593 0.0005003 0.7499995 0.7502353 0.400402 NA NA
1 86028 rs114608975 T C -0.0000341 0.0007999 0.9699999 0.9659751 0.103550 0.0277556 NA
1 91536 rs6702460 G T 0.0000637 0.0004925 0.9000000 0.8970446 0.456858 0.4207270 NA
1 234313 rs8179466 C T -0.0002747 0.0009711 0.7800007 0.7772934 0.074516 NA NA
1 534192 rs6680723 C T -0.0007036 0.0005626 0.2099999 0.2111225 0.240948 NA NA
1 546697 rs12025928 A G -0.0007434 0.0007019 0.2900000 0.2895604 0.913476 NA NA
1 693731 rs12238997 A G -0.0001630 0.0004715 0.7300002 0.7295991 0.116324 0.1417730 NA
1 705882 rs72631875 G A -0.0010385 0.0006909 0.1299999 0.1327930 0.067304 0.0315495 NA
1 706368 rs55727773 A G -0.0002703 0.0003493 0.4400003 0.4390233 0.515667 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0002530 0.0005458 0.6400000 0.6429991 0.073605 0.0826677 NA
22 51219006 rs28729663 G A 0.0000631 0.0004214 0.8800001 0.8809374 0.137945 0.2052720 NA
22 51219387 rs9616832 T C -0.0001753 0.0005469 0.7499995 0.7485562 0.073730 0.0654952 NA
22 51219704 rs147475742 G A -0.0006438 0.0007328 0.3800004 0.3796116 0.041958 0.0473243 NA
22 51221190 rs369304721 G A -0.0005263 0.0007316 0.4700002 0.4718982 0.049727 NA NA
22 51221731 rs115055839 T C -0.0002447 0.0005473 0.6499995 0.6547632 0.073220 0.0625000 NA
22 51222100 rs114553188 G T 0.0005711 0.0006443 0.3800004 0.3753647 0.054465 0.0880591 NA
22 51223637 rs375798137 G A 0.0005950 0.0006474 0.3599996 0.3580554 0.054094 0.0788738 NA
22 51229805 rs9616985 T C -0.0002250 0.0005492 0.6800001 0.6819869 0.073057 0.0730831 NA
22 51237063 rs3896457 T C -0.0002533 0.0003359 0.4500005 0.4507800 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  6.8493e-05:0.000504898:0.05061:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400402 ES:SE:LP:AF:ID  0.000159268:0.000500325:0.124939:0.400402:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10355  ES:SE:LP:AF:ID  -3.41203e-05:0.00079988:0.0132283:0.10355:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456858 ES:SE:LP:AF:ID  6.37333e-05:0.000492546:0.0457575:0.456858:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074516 ES:SE:LP:AF:ID  -0.000274672:0.000971094:0.107905:0.074516:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240948 ES:SE:LP:AF:ID  -0.000703564:0.000562633:0.677781:0.240948:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -0.000743394:0.00070192:0.537602:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116324 ES:SE:LP:AF:ID  -0.000162993:0.000471543:0.136677:0.116324:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067304 ES:SE:LP:AF:ID  -0.00103854:0.000690896:0.886057:0.067304:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515667 ES:SE:LP:AF:ID  -0.000270302:0.000349298:0.356547:0.515667:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  0.000112486:0.000576276:0.0705811:0.101206:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959089 ES:SE:LP:AF:ID  0.00037477:0.000762763:0.207608:0.959089:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053267 ES:SE:LP:AF:ID  -0.000509874:0.00110134:0.19382:0.053267:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.8432   ES:SE:LP:AF:ID  0.000386411:0.00040864:0.468521:0.8432:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055916 ES:SE:LP:AF:ID  -0.000355496:0.000661647:0.229148:0.055916:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122313 ES:SE:LP:AF:ID  -0.000193112:0.000447299:0.173925:0.122313:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121556 ES:SE:LP:AF:ID  -0.000216399:0.000447487:0.200659:0.121556:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132333 ES:SE:LP:AF:ID  -0.00031461:0.000441051:0.318759:0.132333:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838942 ES:SE:LP:AF:ID  0.000232354:0.000395739:0.251812:0.838942:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838569 ES:SE:LP:AF:ID  0.000234268:0.000395312:0.259637:0.838569:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869775 ES:SE:LP:AF:ID  0.000131846:0.000424191:0.119186:0.869775:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129878 ES:SE:LP:AF:ID  -5.48758e-05:0.00042505:0.0457575:0.129878:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  0.00011244:0.000423357:0.102373:0.869115:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869213 ES:SE:LP:AF:ID  0.000132829:0.000423523:0.124939:0.869213:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  0.000113825:0.000423349:0.102373:0.869119:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838022 ES:SE:LP:AF:ID  0.000223169:0.000394215:0.244125:0.838022:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838652 ES:SE:LP:AF:ID  0.000206654:0.000395322:0.221849:0.838652:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839768 ES:SE:LP:AF:ID  0.000214556:0.000400672:0.229148:0.839768:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.8694   ES:SE:LP:AF:ID  0.000123593:0.000422863:0.113509:0.8694:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868949 ES:SE:LP:AF:ID  0.000112389:0.000421802:0.102373:0.868949:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867899 ES:SE:LP:AF:ID  5.65558e-06:0.000420989:0.00436481:0.867899:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869091 ES:SE:LP:AF:ID  0.000114338:0.000422146:0.102373:0.869091:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8691   ES:SE:LP:AF:ID  0.00011387:0.000422179:0.102373:0.8691:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869108 ES:SE:LP:AF:ID  0.000113231:0.000422188:0.102373:0.869108:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869584 ES:SE:LP:AF:ID  0.000120695:0.000423344:0.107905:0.869584:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838302 ES:SE:LP:AF:ID  0.000199712:0.000393464:0.21467:0.838302:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838423 ES:SE:LP:AF:ID  0.000194421:0.000393743:0.207608:0.838423:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862256 ES:SE:LP:AF:ID  1.8796e-05:0.000420656:0.0177288:0.862256:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706761 ES:SE:LP:AF:ID  -2.98733e-05:0.000409514:0.0268721:0.706761:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105128 ES:SE:LP:AF:ID  -0.000185737:0.000471784:0.161151:0.105128:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761332 ES:SE:LP:AF:ID  -0.00027849:0.000334252:0.39794:0.761332:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106461 ES:SE:LP:AF:ID  0.000536506:0.000460721:0.619789:0.106461:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129575 ES:SE:LP:AF:ID  -8.07706e-05:0.000424808:0.0705811:0.129575:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868911 ES:SE:LP:AF:ID  9.3216e-05:0.000422542:0.0809219:0.868911:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129676 ES:SE:LP:AF:ID  -7.34444e-05:0.000424533:0.0655015:0.129676:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868922 ES:SE:LP:AF:ID  8.8633e-05:0.000422552:0.0809219:0.868922:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265374 ES:SE:LP:AF:ID  0.000271456:0.000373332:0.327902:0.265374:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.87004  ES:SE:LP:AF:ID  3.8967e-05:0.00042341:0.0315171:0.87004:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095121 ES:SE:LP:AF:ID  0.000442224:0.000490751:0.431798:0.095121:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128577 ES:SE:LP:AF:ID  -1.96815e-05:0.000425078:0.0177288:0.128577:rs1055606