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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_20087_160.vcf.gz --id UKB-b:6885 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20087_160.txt.gz --cohort_cases 6693 --cohort_controls 58256 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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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-6885/UKB-b-6885_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6885/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6885/UKB-b-6885_data.vcf.gz ...
Read summary statistics for 5360673 SNPs.
Dropped 1841 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, 1158800 SNPs remain.
After merging with regression SNP LD, 1158800 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0136 (0.0068)
Lambda GC: 1.0309
Mean Chi^2: 1.0283
Intercept: 1.01 (0.0064)
Ratio: 0.3532 (0.2263)
Analysis finished at Thu Oct 17 14:41:13 2019
Total time elapsed: 56.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9141,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "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": 46615,
    "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": 1158800,
    "ldsc_nsnp_merge_regression_ld": 1158800,
    "ldsc_observed_scale_h2_beta": 0.0136,
    "ldsc_observed_scale_h2_se": 0.0068,
    "ldsc_intercept_beta": 1.01,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0309,
    "ldsc_mean_chisq": 1.0283,
    "ldsc_ratio": 0.3534
}
 

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 5358847 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 5360673 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 8.673242e+00 5.763210e+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 7.854470e+07 5.656474e+07 828.0000000 3.193614e+07 6.896555e+07 1.144947e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.210000e-05 2.378500e-03 -0.0172977 -1.504300e-03 -1.980000e-05 1.460100e-03 2.051530e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.274400e-03 5.933000e-04 0.0016287 1.776700e-03 2.055300e-03 2.640100e-03 7.788300e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.959278e-01 2.894013e-01 0.0000017 2.500000e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.959284e-01 2.893764e-01 0.0000017 2.451779e-01 4.939697e-01 7.463037e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.369050e-01 2.448424e-01 0.0522940 1.271320e-01 2.654390e-01 5.037380e-01 9.477050e-01 ▇▃▂▂▂
numeric AF_reference 46615 0.9913043 NA NA NA NA NA NA NA 3.315893e-01 2.399431e-01 0.0000000 1.337860e-01 2.695690e-01 4.934110e-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 -0.0022158 0.0030017 0.4600002 0.4604011 0.623812 0.7821490 NA
1 54676 rs2462492 C T -0.0037770 0.0029930 0.2099999 0.2069612 0.399144 NA NA
1 86028 rs114608975 T C 0.0066522 0.0047643 0.1600000 0.1626363 0.103536 0.0277556 NA
1 91536 rs6702460 G T -0.0062424 0.0029438 0.0340001 0.0339600 0.455916 0.4207270 NA
1 234313 rs8179466 C T 0.0023720 0.0058217 0.6800001 0.6836815 0.074455 NA NA
1 534192 rs6680723 C T -0.0017898 0.0033528 0.5900000 0.5934623 0.242057 NA NA
1 546697 rs12025928 A G -0.0010723 0.0041601 0.8000000 0.7965917 0.912862 NA NA
1 693731 rs12238997 A G 0.0027015 0.0027957 0.3300000 0.3338934 0.117313 0.1417730 NA
1 705882 rs72631875 G A -0.0006531 0.0040750 0.8700001 0.8726689 0.067698 0.0315495 NA
1 706368 rs55727773 A G -0.0009056 0.0020751 0.6600001 0.6625291 0.513304 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217954 rs9616974 G A 0.0050073 0.0032840 0.1299999 0.1273122 0.071487 0.0621006 NA
22 51218224 rs9616975 C A 0.0049752 0.0032855 0.1299999 0.1299531 0.071497 0.0619010 NA
22 51218377 rs2519461 G C 0.0049494 0.0032812 0.1299999 0.1314574 0.071792 0.0826677 NA
22 51219006 rs28729663 G A 0.0030710 0.0025242 0.2200002 0.2237486 0.136315 0.2052720 NA
22 51219387 rs9616832 T C 0.0047133 0.0032900 0.1499999 0.1519724 0.071797 0.0654952 NA
22 51221731 rs115055839 T C 0.0049950 0.0032907 0.1299999 0.1290399 0.071348 0.0625000 NA
22 51222100 rs114553188 G T 0.0020122 0.0038133 0.5999997 0.5977162 0.054850 0.0880591 NA
22 51223637 rs375798137 G A 0.0019814 0.0038332 0.6100002 0.6052142 0.054470 0.0788738 NA
22 51229805 rs9616985 T C 0.0050687 0.0033009 0.1199999 0.1246478 0.071253 0.0730831 NA
22 51237063 rs3896457 T C -0.0028934 0.0019928 0.1499999 0.1465089 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.0022158:0.00300168:0.337242:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  -0.003777:0.00299295:0.677781:0.399144:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  0.0066522:0.0047643:0.79588:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  -0.0062424:0.00294377:1.46852:0.455916:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074455 ES:SE:LP:AF:ID  0.00237202:0.0058217:0.167491:0.074455:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  -0.00178981:0.0033528:0.229148:0.242057:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912862 ES:SE:LP:AF:ID  -0.00107231:0.0041601:0.09691:0.912862:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117313 ES:SE:LP:AF:ID  0.00270146:0.00279567:0.481486:0.117313:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067698 ES:SE:LP:AF:ID  -0.000653096:0.00407499:0.0604807:0.067698:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  -0.000905641:0.00207514:0.180456:0.513304:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.102736 ES:SE:LP:AF:ID  -0.00309598:0.00338637:0.443698:0.102736:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.052723 ES:SE:LP:AF:ID  0.00317339:0.00660412:0.200659:0.052723:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  -0.0032379:0.00241774:0.744727:0.841441:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056334 ES:SE:LP:AF:ID  0.00253585:0.00392748:0.283997:0.056334:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  0.00360917:0.00265556:0.769551:0.123078:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  0.00353646:0.00265642:0.744727:0.12233:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  0.00277138:0.00260771:0.537602:0.134139:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  -0.00281238:0.00233887:0.638272:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  -0.00267335:0.00233715:0.60206:0.836733:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  -0.00263588:0.00251139:0.537602:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131004 ES:SE:LP:AF:ID  0.00245662:0.00251784:0.481486:0.131004:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.867976 ES:SE:LP:AF:ID  -0.00254103:0.00250735:0.508638:0.867976:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86805  ES:SE:LP:AF:ID  -0.00254055:0.00250838:0.508638:0.86805:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867987 ES:SE:LP:AF:ID  -0.00248682:0.00250729:0.49485:0.867987:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  -0.00265961:0.00233031:0.60206:0.836159:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  -0.00272708:0.0023367:0.619789:0.836793:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  -0.00284371:0.00236959:0.638272:0.838109:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  -0.00242963:0.00250406:0.481486:0.868228:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867742 ES:SE:LP:AF:ID  -0.00254795:0.00249743:0.508638:0.867742:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866644 ES:SE:LP:AF:ID  -0.00259812:0.00249285:0.522879:0.866644:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867911 ES:SE:LP:AF:ID  -0.002415:0.00249996:0.481486:0.867911:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867923 ES:SE:LP:AF:ID  -0.00241575:0.00250013:0.481486:0.867923:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867932 ES:SE:LP:AF:ID  -0.00242257:0.00250022:0.481486:0.867932:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868398 ES:SE:LP:AF:ID  -0.00246259:0.0025068:0.481486:0.868398:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.836369 ES:SE:LP:AF:ID  -0.00275284:0.0023245:0.619789:0.836369:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.836495 ES:SE:LP:AF:ID  -0.00272876:0.00232609:0.619789:0.836495:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860851 ES:SE:LP:AF:ID  -0.00264912:0.00249136:0.537602:0.860851:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705804 ES:SE:LP:AF:ID  -0.00145072:0.00243113:0.259637:0.705804:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106094 ES:SE:LP:AF:ID  0.00300035:0.00279748:0.552842:0.106094:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.758252 ES:SE:LP:AF:ID  -0.000435046:0.00197045:0.0809219:0.758252:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108262 ES:SE:LP:AF:ID  -0.00219507:0.00271206:0.376751:0.108262:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.13066  ES:SE:LP:AF:ID  0.00204267:0.00251688:0.376751:0.13066:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.867852 ES:SE:LP:AF:ID  -0.00204303:0.00250313:0.387216:0.867852:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.130756 ES:SE:LP:AF:ID  0.00197993:0.00251519:0.366532:0.130756:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.867878 ES:SE:LP:AF:ID  -0.00192175:0.00250328:0.356547:0.867878:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.263729 ES:SE:LP:AF:ID  0.00275224:0.00222653:0.657577:0.263729:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  -0.00212793:0.00250987:0.39794:0.869067:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.096639 ES:SE:LP:AF:ID  -0.00117905:0.00289098:0.167491:0.096639:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.129594 ES:SE:LP:AF:ID  0.00185208:0.00251944:0.337242:0.129594:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.129863 ES:SE:LP:AF:ID  0.00174145:0.00251515:0.309804:0.129863:rs4040617