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_41214_1.vcf.gz --id UKB-b:67 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41214_1.txt.gz --cohort_cases 8862 --cohort_controls 16329 --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-67/UKB-b-67_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-67/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-67/UKB-b-67_data.vcf.gz ...
Read summary statistics for 5774876 SNPs.
Dropped 2425 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, 1197818 SNPs remain.
After merging with regression SNP LD, 1197818 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0217 (0.0207)
Lambda GC: 1.0989
Mean Chi^2: 1.0944
Intercept: 1.0835 (0.0073)
Ratio: 0.884 (0.0768)
Analysis finished at Thu Oct 17 14:41:23 2019
Total time elapsed: 1.0m:4.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9211,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 3.1494e-06,
    "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": 51561,
    "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": 1197818,
    "ldsc_nsnp_merge_regression_ld": 1197818,
    "ldsc_observed_scale_h2_beta": 0.0217,
    "ldsc_observed_scale_h2_se": 0.0207,
    "ldsc_intercept_beta": 1.0835,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0989,
    "ldsc_mean_chisq": 1.0944,
    "ldsc_ratio": 0.8845
}

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 1.0000000 3 58 0 5772467 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 5774876 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 8.670010e+00 5.762109e+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 7.860485e+07 5.654602e+07 828.0000000 3.200417e+07 6.904692e+07 1.145219e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.100000e-06 6.489000e-03 -0.0559911 -3.942000e-03 -1.450000e-05 3.949900e-03 6.231230e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.929800e-03 1.827200e-03 0.0040101 4.416700e-03 5.231600e-03 7.015100e-03 1.947580e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.838368e-01 2.920045e-01 0.0000004 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 4.838393e-01 2.919801e-01 0.0000004 2.265528e-01 4.776580e-01 7.368935e-01 9.999995e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.204347e-01 2.508087e-01 0.0394950 1.070050e-01 2.419685e-01 4.866900e-01 9.605050e-01 ▇▃▂▂▁
numeric AF_reference 51561 0.9910715 NA NA NA NA NA NA NA 3.163379e-01 2.445091e-01 0.0000000 1.152160e-01 2.484030e-01 4.766370e-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 0.0096383 0.0073336 0.1900002 0.1887567 0.623606 0.7821490 NA
1 54676 rs2462492 C T 0.0008574 0.0072756 0.9100000 0.9061913 0.399205 NA NA
1 86028 rs114608975 T C -0.0109852 0.0116831 0.3500000 0.3470821 0.102984 0.0277556 NA
1 91536 rs6702460 G T -0.0095700 0.0071952 0.1800002 0.1834993 0.454182 0.4207270 NA
1 234313 rs8179466 C T 0.0262114 0.0138838 0.0589997 0.0590377 0.075832 NA NA
1 534192 rs6680723 C T 0.0048446 0.0082676 0.5600000 0.5578929 0.236154 NA NA
1 546697 rs12025928 A G -0.0051325 0.0101222 0.6100002 0.6121191 0.912469 NA NA
1 693731 rs12238997 A G 0.0068919 0.0068304 0.3100002 0.3129685 0.117156 0.1417730 NA
1 705882 rs72631875 G A 0.0031765 0.0099851 0.7499995 0.7503899 0.068339 0.0315495 NA
1 706368 rs55727773 A G -0.0029314 0.0050729 0.5600000 0.5633577 0.518965 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0062305 0.0080872 0.4400003 0.4410558 0.072297 0.0826677 NA
22 51219006 rs28729663 G A -0.0006699 0.0062116 0.9100000 0.9141130 0.135974 0.2052720 NA
22 51219387 rs9616832 T C 0.0067812 0.0080933 0.4000000 0.4021009 0.072554 0.0654952 NA
22 51219704 rs147475742 G A 0.0022878 0.0106388 0.8300000 0.8297308 0.042561 0.0473243 NA
22 51221190 rs369304721 G A 0.0051048 0.0108073 0.6400000 0.6366808 0.048773 NA NA
22 51221731 rs115055839 T C 0.0067202 0.0081041 0.4100001 0.4069683 0.072006 0.0625000 NA
22 51222100 rs114553188 G T -0.0047438 0.0094614 0.6200004 0.6161020 0.053823 0.0880591 NA
22 51223637 rs375798137 G A -0.0039221 0.0095016 0.6800001 0.6797687 0.053487 0.0788738 NA
22 51229805 rs9616985 T C 0.0050185 0.0081246 0.5400003 0.5367770 0.071894 0.0730831 NA
22 51237063 rs3896457 T C 0.0001988 0.0049264 0.9699999 0.9678178 0.298341 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623606 ES:SE:LP:AF:ID  0.00963834:0.00733363:0.721246:0.623606:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399205 ES:SE:LP:AF:ID  0.00085739:0.00727564:0.0409586:0.399205:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.102984 ES:SE:LP:AF:ID  -0.0109852:0.0116831:0.455932:0.102984:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.454182 ES:SE:LP:AF:ID  -0.00957003:0.0071952:0.744727:0.454182:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.075832 ES:SE:LP:AF:ID  0.0262114:0.0138838:1.22915:0.075832:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.236154 ES:SE:LP:AF:ID  0.00484457:0.00826755:0.251812:0.236154:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912469 ES:SE:LP:AF:ID  -0.00513247:0.0101222:0.21467:0.912469:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117156 ES:SE:LP:AF:ID  0.00689192:0.00683036:0.508638:0.117156:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.068339 ES:SE:LP:AF:ID  0.0031765:0.00998506:0.124939:0.068339:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.518965 ES:SE:LP:AF:ID  -0.00293141:0.00507286:0.251812:0.518965:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101348 ES:SE:LP:AF:ID  -0.000609687:0.00840394:0.0268721:0.101348:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.957991 ES:SE:LP:AF:ID  0.00935217:0.0110227:0.39794:0.957991:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.051583 ES:SE:LP:AF:ID  -0.021494:0.0165139:0.721246:0.051583:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.841775 ES:SE:LP:AF:ID  -0.00149034:0.00591604:0.09691:0.841775:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05495  ES:SE:LP:AF:ID  -0.0148748:0.00969636:0.886057:0.05495:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122715 ES:SE:LP:AF:ID  0.00344738:0.00649244:0.221849:0.122715:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.122012 ES:SE:LP:AF:ID  0.00358987:0.00649193:0.236572:0.122012:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133013 ES:SE:LP:AF:ID  -0.000249805:0.0063936:0.0132283:0.133013:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837957 ES:SE:LP:AF:ID  -3.73286e-05:0.00573228:0.00436481:0.837957:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837674 ES:SE:LP:AF:ID  0.000193467:0.00572977:0.0132283:0.837674:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869374 ES:SE:LP:AF:ID  -0.00271894:0.00615817:0.180456:0.869374:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129813 ES:SE:LP:AF:ID  0.00235015:0.0061791:0.154902:0.129813:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.868662 ES:SE:LP:AF:ID  -0.00248895:0.006147:0.161151:0.868662:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868754 ES:SE:LP:AF:ID  -0.00252819:0.0061483:0.167491:0.868754:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868694 ES:SE:LP:AF:ID  -0.00241463:0.00614712:0.161151:0.868694:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837068 ES:SE:LP:AF:ID  0.000749607:0.00571042:0.0457575:0.837068:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.837739 ES:SE:LP:AF:ID  0.000680198:0.00572744:0.0409586:0.837739:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838972 ES:SE:LP:AF:ID  0.000127422:0.00580881:0.00877392:0.838972:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869049 ES:SE:LP:AF:ID  -0.00242054:0.00614055:0.161151:0.869049:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868618 ES:SE:LP:AF:ID  -0.00250568:0.00612564:0.167491:0.868618:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867635 ES:SE:LP:AF:ID  -0.00238539:0.00611811:0.154902:0.867635:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868781 ES:SE:LP:AF:ID  -0.00240149:0.00613152:0.154902:0.868781:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868788 ES:SE:LP:AF:ID  -0.00239909:0.00613196:0.154902:0.868788:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868795 ES:SE:LP:AF:ID  -0.0023808:0.00613216:0.154902:0.868795:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869208 ES:SE:LP:AF:ID  -0.00244859:0.0061465:0.161151:0.869208:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.83752  ES:SE:LP:AF:ID  8.58276e-05:0.00569896:0.00436481:0.83752:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.837649 ES:SE:LP:AF:ID  0.000240429:0.00570292:0.0132283:0.837649:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.861964 ES:SE:LP:AF:ID  -0.00275184:0.00610919:0.187087:0.861964:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.70665  ES:SE:LP:AF:ID  -0.00186036:0.00595063:0.124939:0.70665:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.104927 ES:SE:LP:AF:ID  0.00149317:0.00686862:0.0809219:0.104927:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.766177 ES:SE:LP:AF:ID  -0.00767887:0.00489632:0.920819:0.766177:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.10127  ES:SE:LP:AF:ID  0.0109074:0.00685114:0.958607:0.10127:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129477 ES:SE:LP:AF:ID  0.00277249:0.00617351:0.187087:0.129477:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.86855  ES:SE:LP:AF:ID  -0.00309419:0.00613516:0.21467:0.86855:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129595 ES:SE:LP:AF:ID  0.00255095:0.00616997:0.167491:0.129595:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868515 ES:SE:LP:AF:ID  -0.00326623:0.0061344:0.229148:0.868515:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.270444 ES:SE:LP:AF:ID  -0.00317376:0.00540364:0.251812:0.270444:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869387 ES:SE:LP:AF:ID  -0.00360502:0.00614016:0.251812:0.869387:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.090687 ES:SE:LP:AF:ID  0.0144711:0.00729997:1.3279:0.090687:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128832 ES:SE:LP:AF:ID  0.0032597:0.00617259:0.221849:0.128832:rs1055606