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-17107/UKB-b-17107_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17107/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17107/UKB-b-17107_data.vcf.gz ...
Read summary statistics for 5730096 SNPs.
Dropped 2369 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, 1194108 SNPs remain.
After merging with regression SNP LD, 1194108 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0062 (0.0012)
Lambda GC: 1.0749
Mean Chi^2: 1.0733
Intercept: 1.0134 (0.0071)
Ratio: 0.1827 (0.0974)
Analysis finished at Thu Oct 17 14:46:29 2019
Total time elapsed: 55.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9205,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -4.4424e-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": 51056,
    "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": 1194108,
    "ldsc_nsnp_merge_regression_ld": 1194108,
    "ldsc_observed_scale_h2_beta": 0.0062,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0134,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.0749,
    "ldsc_mean_chisq": 1.0733,
    "ldsc_ratio": 0.1828
}

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 5727743 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 5730096 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 8.669628e+00 5.762112e+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 7.860432e+07 5.655348e+07 828.0000000 3.199556e+07 6.904414e+07 1.145460e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.000000e-07 4.297000e-04 -0.0037852 -2.631000e-04 -5.000000e-07 2.612000e-04 4.698800e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.981000e-04 1.206000e-04 0.0002711 2.981000e-04 3.521000e-04 4.699000e-04 1.293800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.881590e-01 2.917697e-01 0.0000001 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.881595e-01 2.917430e-01 0.0000001 2.331818e-01 4.832169e-01 7.410825e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.221800e-01 2.502413e-01 0.0407220 1.090480e-01 2.444150e-01 4.885432e-01 9.592780e-01 ▇▃▂▂▁
numeric AF_reference 51056 0.9910899 NA NA NA NA NA NA NA 3.179737e-01 2.440722e-01 0.0000000 1.172120e-01 2.507990e-01 4.786340e-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 0.0005303 0.0004990 0.2900000 0.2878695 0.623794 0.7821490 NA
1 54676 rs2462492 C T -0.0004944 0.0004943 0.3200000 0.3172420 0.400412 NA NA
1 86028 rs114608975 T C -0.0005546 0.0007904 0.4799997 0.4828886 0.103543 0.0277556 NA
1 91536 rs6702460 G T 0.0002671 0.0004868 0.5800000 0.5831697 0.456865 0.4207270 NA
1 234313 rs8179466 C T 0.0003186 0.0009596 0.7400005 0.7399203 0.074516 NA NA
1 534192 rs6680723 C T -0.0013772 0.0005560 0.0129999 0.0132521 0.240948 NA NA
1 546697 rs12025928 A G -0.0002161 0.0006935 0.7600007 0.7553026 0.913458 NA NA
1 693731 rs12238997 A G -0.0003316 0.0004659 0.4799997 0.4766539 0.116328 0.1417730 NA
1 705882 rs72631875 G A 0.0021089 0.0006828 0.0020000 0.0020106 0.067284 0.0315495 NA
1 706368 rs55727773 A G 0.0000704 0.0003452 0.8400000 0.8384536 0.515613 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0004700 0.0005394 0.3800004 0.3835416 0.073617 0.0826677 NA
22 51219006 rs28729663 G A 0.0003917 0.0004164 0.3500000 0.3468683 0.137952 0.2052720 NA
22 51219387 rs9616832 T C 0.0004208 0.0005404 0.4400003 0.4361836 0.073740 0.0654952 NA
22 51219704 rs147475742 G A 0.0008718 0.0007242 0.2300001 0.2286281 0.041958 0.0473243 NA
22 51221190 rs369304721 G A 0.0007249 0.0007230 0.3200000 0.3160745 0.049729 NA NA
22 51221731 rs115055839 T C 0.0003580 0.0005408 0.5099998 0.5079428 0.073230 0.0625000 NA
22 51222100 rs114553188 G T -0.0000799 0.0006366 0.9000000 0.9001596 0.054472 0.0880591 NA
22 51223637 rs375798137 G A -0.0000971 0.0006397 0.8800001 0.8793270 0.054101 0.0788738 NA
22 51229805 rs9616985 T C 0.0004391 0.0005427 0.4199997 0.4185377 0.073065 0.0730831 NA
22 51237063 rs3896457 T C -0.0002566 0.0003320 0.4400003 0.4395799 0.297957 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623794 ES:SE:LP:AF:ID  0.000530347:0.000499006:0.537602:0.623794:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400412 ES:SE:LP:AF:ID  -0.000494393:0.000494323:0.49485:0.400412:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103543 ES:SE:LP:AF:ID  -0.000554601:0.000790408:0.318759:0.103543:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456865 ES:SE:LP:AF:ID  0.000267112:0.000486755:0.236572:0.456865:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074516 ES:SE:LP:AF:ID  0.000318558:0.000959631:0.130768:0.074516:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240948 ES:SE:LP:AF:ID  -0.00137722:0.000556021:1.88606:0.240948:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913458 ES:SE:LP:AF:ID  -0.000216136:0.00069351:0.119186:0.913458:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116328 ES:SE:LP:AF:ID  -0.000331612:0.000465947:0.318759:0.116328:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067284 ES:SE:LP:AF:ID  0.00210886:0.000682773:2.69897:0.067284:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515613 ES:SE:LP:AF:ID  7.03678e-05:0.000345157:0.0757207:0.515613:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101218 ES:SE:LP:AF:ID  -0.000270491:0.000569423:0.200659:0.101218:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.9591   ES:SE:LP:AF:ID  0.000348769:0.00075386:0.19382:0.9591:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.05326  ES:SE:LP:AF:ID  -0.000541582:0.00108848:0.207608:0.05326:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843217 ES:SE:LP:AF:ID  0.00044754:0.000403811:0.568636:0.843217:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055923 ES:SE:LP:AF:ID  -0.000887158:0.000653754:0.769551:0.055923:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:ID  -0.000438181:0.000441993:0.49485:0.122311:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121553 ES:SE:LP:AF:ID  -0.000422823:0.000442184:0.468521:0.121553:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132335 ES:SE:LP:AF:ID  -0.000563004:0.000435808:0.69897:0.132335:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  0.000281459:0.000391056:0.327902:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838581 ES:SE:LP:AF:ID  0.000248691:0.000390639:0.283997:0.838581:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869775 ES:SE:LP:AF:ID  0.000224787:0.000419174:0.229148:0.869775:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129877 ES:SE:LP:AF:ID  -0.000131143:0.000420023:0.124939:0.129877:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  0.000185574:0.000418353:0.180456:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  0.000191888:0.00041852:0.187087:0.869216:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  0.000185978:0.000418345:0.180456:0.869121:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838034 ES:SE:LP:AF:ID  0.000238022:0.000389551:0.267606:0.838034:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838665 ES:SE:LP:AF:ID  0.00025994:0.000390647:0.29243:0.838665:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839775 ES:SE:LP:AF:ID  0.000278516:0.000395926:0.318759:0.839775:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869399 ES:SE:LP:AF:ID  0.000188174:0.000417862:0.187087:0.869399:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868946 ES:SE:LP:AF:ID  0.000197953:0.00041681:0.200659:0.868946:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867901 ES:SE:LP:AF:ID  0.000172327:0.000416012:0.167491:0.867901:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869088 ES:SE:LP:AF:ID  0.000200628:0.000417148:0.200659:0.869088:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869097 ES:SE:LP:AF:ID  0.000200256:0.00041718:0.200659:0.869097:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869105 ES:SE:LP:AF:ID  0.000199879:0.000417189:0.200659:0.869105:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869581 ES:SE:LP:AF:ID  0.000210629:0.000418333:0.21467:0.869581:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838312 ES:SE:LP:AF:ID  0.000245369:0.000388807:0.275724:0.838312:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838433 ES:SE:LP:AF:ID  0.000249766:0.000389081:0.283997:0.838433:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862261 ES:SE:LP:AF:ID  0.000195261:0.000415689:0.19382:0.862261:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706751 ES:SE:LP:AF:ID  5.61793e-05:0.000404669:0.05061:0.706751:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105147 ES:SE:LP:AF:ID  -0.000520166:0.000466171:0.585027:0.105147:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761319 ES:SE:LP:AF:ID  0.000223892:0.000330291:0.30103:0.761319:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106468 ES:SE:LP:AF:ID  -0.000110403:0.000455256:0.091515:0.106468:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129583 ES:SE:LP:AF:ID  -0.000193134:0.000419771:0.187087:0.129583:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868906 ES:SE:LP:AF:ID  0.000203734:0.000417537:0.200659:0.868906:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129684 ES:SE:LP:AF:ID  -0.000207356:0.000419499:0.207608:0.129684:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868916 ES:SE:LP:AF:ID  0.000191462:0.000417545:0.187087:0.868916:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265389 ES:SE:LP:AF:ID  4.21557e-05:0.000368925:0.0409586:0.265389:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870039 ES:SE:LP:AF:ID  0.000240996:0.000418396:0.251812:0.870039:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.09513  ES:SE:LP:AF:ID  -0.000276237:0.000484927:0.244125:0.09513:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128583 ES:SE:LP:AF:ID  -0.00022636:0.000420039:0.229148:0.128583:rs1055606