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-8146/UKB-b-8146_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8146/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8146/UKB-b-8146_data.vcf.gz ...
Read summary statistics for 5778175 SNPs.
Dropped 2444 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, 1198110 SNPs remain.
After merging with regression SNP LD, 1198110 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0058 (0.0011)
Lambda GC: 1.0845
Mean Chi^2: 1.0819
Intercept: 1.0279 (0.0073)
Ratio: 0.3406 (0.0894)
Analysis finished at Thu Oct 17 14:42:29 2019
Total time elapsed: 1.0m:6.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9213,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 5.3834e-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": 51627,
    "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": 1198110,
    "ldsc_nsnp_merge_regression_ld": 1198110,
    "ldsc_observed_scale_h2_beta": 0.0058,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0279,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0845,
    "ldsc_mean_chisq": 1.0819,
    "ldsc_ratio": 0.3407
}

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 5775747 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 5778175 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 8.670462e+00 5.762462e+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 7.859652e+07 5.654651e+07 828.0000000 3.199373e+07 6.903390e+07 1.145206e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.000000e-07 4.459000e-04 -0.0032890 -2.724000e-04 -5.000000e-07 2.708000e-04 3.593900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.115000e-04 1.270000e-04 0.0002784 3.063000e-04 3.629000e-04 4.868000e-04 1.333900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.868631e-01 2.923751e-01 0.0000002 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 4.868619e-01 2.923496e-01 0.0000002 2.306455e-01 4.817191e-01 7.405562e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.202768e-01 2.508292e-01 0.0393930 1.068280e-01 2.418350e-01 4.865140e-01 9.606070e-01 ▇▃▂▂▁
numeric AF_reference 51627 0.9910652 NA NA NA NA NA NA NA 3.162049e-01 2.445255e-01 0.0000000 1.150160e-01 2.482030e-01 4.764380e-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 -0.0009763 0.0005124 0.0569994 0.0567065 0.623783 0.7821490 NA
1 54676 rs2462492 C T 0.0004823 0.0005076 0.3400001 0.3420105 0.400457 NA NA
1 86028 rs114608975 T C -0.0000968 0.0008116 0.9100000 0.9050414 0.103543 0.0277556 NA
1 91536 rs6702460 G T -0.0004409 0.0004997 0.3800004 0.3776715 0.456874 0.4207270 NA
1 234313 rs8179466 C T 0.0012143 0.0009852 0.2200002 0.2177659 0.074519 NA NA
1 534192 rs6680723 C T -0.0006673 0.0005708 0.2399999 0.2424018 0.240975 NA NA
1 546697 rs12025928 A G -0.0003962 0.0007120 0.5800000 0.5779311 0.913488 NA NA
1 693731 rs12238997 A G -0.0000672 0.0004782 0.8900000 0.8881734 0.116354 0.1417730 NA
1 705882 rs72631875 G A -0.0000858 0.0007008 0.9000000 0.9026073 0.067296 0.0315495 NA
1 706368 rs55727773 A G 0.0002353 0.0003544 0.5099998 0.5067222 0.515658 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0003603 0.0005538 0.5199996 0.5153649 0.073602 0.0826677 NA
22 51219006 rs28729663 G A 0.0007616 0.0004275 0.0749998 0.0748454 0.137921 0.2052720 NA
22 51219387 rs9616832 T C 0.0003652 0.0005550 0.5099998 0.5104880 0.073721 0.0654952 NA
22 51219704 rs147475742 G A 0.0006452 0.0007436 0.3900004 0.3855870 0.041945 0.0473243 NA
22 51221190 rs369304721 G A 0.0003085 0.0007423 0.6800001 0.6777340 0.049724 NA NA
22 51221731 rs115055839 T C 0.0003808 0.0005553 0.4899999 0.4928081 0.073211 0.0625000 NA
22 51222100 rs114553188 G T 0.0008877 0.0006537 0.1700000 0.1744975 0.054450 0.0880591 NA
22 51223637 rs375798137 G A 0.0008913 0.0006569 0.1700000 0.1748352 0.054078 0.0788738 NA
22 51229805 rs9616985 T C 0.0003556 0.0005573 0.5199996 0.5234129 0.073046 0.0730831 NA
22 51237063 rs3896457 T C 0.0004168 0.0003408 0.2200002 0.2212797 0.297942 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623783 ES:SE:LP:AF:ID  -0.000976338:0.000512361:1.24413:0.623783:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400457 ES:SE:LP:AF:ID  0.000482276:0.000507552:0.468521:0.400457:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103543 ES:SE:LP:AF:ID  -9.68176e-05:0.000811579:0.0409586:0.103543:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456874 ES:SE:LP:AF:ID  -0.000440868:0.00049974:0.420216:0.456874:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  0.00121431:0.000985249:0.657577:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240975 ES:SE:LP:AF:ID  -0.000667262:0.000570795:0.619789:0.240975:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913488 ES:SE:LP:AF:ID  -0.000396184:0.000712037:0.236572:0.913488:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116354 ES:SE:LP:AF:ID  -6.72445e-05:0.000478214:0.05061:0.116354:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067296 ES:SE:LP:AF:ID  -8.5761e-05:0.000700843:0.0457575:0.067296:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515658 ES:SE:LP:AF:ID  0.000235284:0.00035437:0.29243:0.515658:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101246 ES:SE:LP:AF:ID  -0.000787991:0.000584476:0.744727:0.101246:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959089 ES:SE:LP:AF:ID  -0.000450239:0.000773832:0.251812:0.959089:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053273 ES:SE:LP:AF:ID  0.0017075:0.00111706:0.886057:0.053273:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843184 ES:SE:LP:AF:ID  -0.000168258:0.00041449:0.167491:0.843184:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055947 ES:SE:LP:AF:ID  0.00013651:0.00067095:0.0757207:0.055947:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122327 ES:SE:LP:AF:ID  -3.66367e-06:0.000453657:0.00436481:0.122327:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121571 ES:SE:LP:AF:ID  -7.34485e-05:0.000453846:0.0604807:0.121571:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132347 ES:SE:LP:AF:ID  0.000105428:0.000447356:0.091515:0.132347:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838927 ES:SE:LP:AF:ID  -9.31951e-05:0.000401417:0.0861861:0.838927:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838554 ES:SE:LP:AF:ID  -8.15644e-05:0.000400983:0.0757207:0.838554:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869761 ES:SE:LP:AF:ID  2.85474e-05:0.000430262:0.0222764:0.869761:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129894 ES:SE:LP:AF:ID  -0.000109634:0.000431126:0.09691:0.129894:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  4.01549e-05:0.000429418:0.0315171:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869199 ES:SE:LP:AF:ID  4.27906e-05:0.000429589:0.0362122:0.869199:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  4.0562e-05:0.00042941:0.0362122:0.869104:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838003 ES:SE:LP:AF:ID  -5.37179e-05:0.000399865:0.05061:0.838003:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838632 ES:SE:LP:AF:ID  -3.89015e-05:0.000400989:0.0362122:0.838632:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839742 ES:SE:LP:AF:ID  -9.91663e-05:0.000406415:0.091515:0.839742:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869381 ES:SE:LP:AF:ID  6.74434e-05:0.000428907:0.0555173:0.869381:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868926 ES:SE:LP:AF:ID  5.98739e-05:0.000427825:0.05061:0.868926:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867879 ES:SE:LP:AF:ID  5.94186e-05:0.000427007:0.05061:0.867879:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869071 ES:SE:LP:AF:ID  5.72382e-05:0.000428178:0.05061:0.869071:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86908  ES:SE:LP:AF:ID  5.73232e-05:0.00042821:0.05061:0.86908:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  6.66881e-05:0.00042822:0.0555173:0.869087:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869564 ES:SE:LP:AF:ID  6.32191e-05:0.000429395:0.0555173:0.869564:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838282 ES:SE:LP:AF:ID  -5.85623e-05:0.000399105:0.0555173:0.838282:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838401 ES:SE:LP:AF:ID  -5.82698e-05:0.000399381:0.0555173:0.838401:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862235 ES:SE:LP:AF:ID  6.37788e-05:0.000426671:0.0555173:0.862235:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706707 ES:SE:LP:AF:ID  0.000428127:0.000415377:0.522879:0.706707:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105164 ES:SE:LP:AF:ID  -2.26027e-05:0.000478467:0.0177288:0.105164:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761359 ES:SE:LP:AF:ID  0.000134775:0.000339088:0.161151:0.761359:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106411 ES:SE:LP:AF:ID  -0.000118078:0.000467504:0.09691:0.106411:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129601 ES:SE:LP:AF:ID  -0.000130171:0.000430857:0.119186:0.129601:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868887 ES:SE:LP:AF:ID  5.70496e-05:0.000428567:0.05061:0.868887:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129704 ES:SE:LP:AF:ID  -0.000159494:0.000430575:0.148742:0.129704:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868898 ES:SE:LP:AF:ID  7.32433e-05:0.000428577:0.0655015:0.868898:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265396 ES:SE:LP:AF:ID  -7.13295e-05:0.000378738:0.0705811:0.265396:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870029 ES:SE:LP:AF:ID  3.39832e-05:0.000429463:0.0268721:0.870029:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095091 ES:SE:LP:AF:ID  -0.000277717:0.000497896:0.236572:0.095091:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128594 ES:SE:LP:AF:ID  -0.000144905:0.000431142:0.130768:0.128594:rs1055606