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/dev/ukb-a-import/processed/ukb-a-247/ukb-a-247.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-247/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Sun Feb 16 02:20:42 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-247/ukb-a-247.vcf.gz ...
Read summary statistics for 10877936 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1281483 SNPs remain.
After merging with regression SNP LD, 1281483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0302 (0.0021)
Lambda GC: 1.1676
Mean Chi^2: 1.2016
Intercept: 1.0063 (0.0078)
Ratio: 0.0313 (0.0385)
Analysis finished at Sun Feb 16 02:22:19 2020
Total time elapsed: 1.0m:37.23s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9533,
    "inflation_factor": 1.1077,
    "mean_EFFECT": 4.7692e-06,
    "n": 335888,
    "n_snps": 10877936,
    "n_clumped_hits": 3,
    "n_p_sig": 1015,
    "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": 356865,
    "n_est": 334395.3609,
    "ratio_se_n": 0.9978,
    "mean_diff": 9.942e-06,
    "ratio_diff": 34.9472,
    "sd_y_est1": 0.3187,
    "sd_y_est2": 0.318,
    "r2_sum1": 0,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1281483,
    "ldsc_nsnp_merge_regression_ld": 1281483,
    "ldsc_observed_scale_h2_beta": 0.0302,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.0063,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.1676,
    "ldsc_mean_chisq": 1.2016,
    "ldsc_ratio": 0.0312
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 10877936 0 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
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.598638e+00 5.745666e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.911383e+07 5.624931e+07 8.28000e+02 3.287294e+07 6.988889e+07 1.148258e+08 2.492251e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.800000e-06 4.664700e-03 -5.20870e-02 -1.329000e-03 -5.600000e-06 1.320200e-03 5.758980e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.349600e-03 3.172400e-03 7.68400e-04 9.491000e-04 1.822900e-03 4.871000e-03 1.745580e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.831197e-01 2.934481e-01 0.00000e+00 2.249060e-01 4.777866e-01 7.374359e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.831192e-01 2.934484e-01 0.00000e+00 2.249048e-01 4.777865e-01 7.374362e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.820865e-01 2.503832e-01 1.00090e-03 6.878700e-03 5.191440e-02 2.739880e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 356865 0.9671937 NA NA NA NA NA 1.877709e-01 2.439191e-01 0.00000e+00 5.191700e-03 7.468050e-02 2.873400e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.358880e+05 0.000000e+00 3.35888e+05 3.358880e+05 3.358880e+05 3.358880e+05 3.358880e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 693731 rs12238997 A G -0.0009383 0.0012828 0.4645335 0.4645327 0.1169260 0.1417730 335888
1 717587 rs144155419 G A 0.0009073 0.0034451 0.7922678 0.7922681 0.0143862 0.0045926 335888
1 730087 rs148120343 T C -0.0009811 0.0017879 0.5831725 0.5831721 0.0554733 0.0127796 335888
1 731718 rs142557973 T C -0.0006114 0.0012170 0.6153851 0.6153855 0.1216580 0.1543530 335888
1 734349 rs141242758 T C -0.0006640 0.0012177 0.5855325 0.5855315 0.1215130 0.1525560 335888
1 740284 rs61770167 C T 0.0034661 0.0055447 0.5318951 0.5318944 0.0058556 0.0023962 335888
1 742813 rs112573343 C T 0.0008469 0.0104475 0.9353891 0.9353889 0.0015525 0.1030350 335888
1 753405 rs3115860 C A 0.0003859 0.0011569 0.7387253 0.7387252 0.8706760 0.7517970 335888
1 753541 rs2073813 G A -0.0002900 0.0011598 0.8025450 0.8025457 0.1288330 0.3019170 335888
1 754182 rs3131969 A G 0.0003061 0.0011557 0.7911266 0.7911273 0.8703180 0.6785140 335888
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219387 rs9616832 T C -0.0006824 0.0014900 0.6469355 0.6469351 0.0729806 0.0654952 335888
22 51219704 rs147475742 G A -0.0009034 0.0019975 0.6510705 0.6510699 0.0418225 0.0473243 335888
22 51219766 rs182321900 C T -0.0031070 0.0102818 0.7625143 0.7625137 0.0014546 NA 335888
22 51220088 rs566371895 G A -0.0020754 0.0067085 0.7570438 0.7570423 0.0039843 0.0003994 335888
22 51220146 rs868950473 C T -0.0046565 0.0101269 0.6456483 0.6456483 0.0015139 NA 335888
22 51221731 rs115055839 T C -0.0007079 0.0014909 0.6349127 0.6349107 0.0728101 0.0625000 335888
22 51223637 rs375798137 G A -0.0002758 0.0017562 0.8752169 0.8752162 0.0540289 0.0788738 335888
22 51226692 rs150189434 G A 0.0006235 0.0105183 0.9527279 0.9527279 0.0013983 0.0155751 335888
22 51229805 rs9616985 T C -0.0006764 0.0014965 0.6512609 0.6512594 0.0727671 0.0730831 335888
22 51237063 rs3896457 T C -0.0006619 0.0009109 0.4674111 0.4674103 0.2968410 0.2050720 335888

bcf preview

1   693731  rs12238997  A   G   .   PASS    AF=0.116926 ES:SE:LP:AF:SS:ID   -0.000938259:0.00128282:0.332983:0.116926:335888:rs12238997
1   717587  rs144155419 G   A   .   PASS    AF=0.0143862    ES:SE:LP:AF:SS:ID   0.000907332:0.00344513:0.101128:0.0143862:335888:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0554733    ES:SE:LP:AF:SS:ID   -0.000981123:0.0017879:0.234203:0.0554733:335888:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121658 ES:SE:LP:AF:SS:ID   -0.000611437:0.00121703:0.210853:0.121658:335888:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121513 ES:SE:LP:AF:SS:ID   -0.000664045:0.00121771:0.232449:0.121513:335888:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00585559   ES:SE:LP:AF:SS:ID   0.00346606:0.00554466:0.274174:0.00585559:335888:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0015525    ES:SE:LP:AF:SS:ID   0.000846944:0.0104475:0.0290077:0.0015525:335888:rs112573343
1   753405  rs3115860   C   A   .   PASS    AF=0.870676 ES:SE:LP:AF:SS:ID   0.000385878:0.00115691:0.131517:0.870676:335888:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.128833 ES:SE:LP:AF:SS:ID   -0.000290015:0.00115981:0.0955306:0.128833:335888:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.870318 ES:SE:LP:AF:SS:ID   0.000306081:0.00115569:0.101754:0.870318:335888:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870409 ES:SE:LP:AF:SS:ID   0.000335233:0.00115624:0.112458:0.870409:335888:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870037 ES:SE:LP:AF:SS:ID   0.000298689:0.00115564:0.0990591:0.870037:335888:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00465304   ES:SE:LP:AF:SS:ID   0.00429478:0.00589498:0.331354:0.00465304:335888:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00464711   ES:SE:LP:AF:SS:ID   0.00411761:0.00591101:0.313315:0.00464711:335888:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00590897   ES:SE:LP:AF:SS:ID   0.00236513:0.00575914:0.166654:0.00590897:335888:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870329 ES:SE:LP:AF:SS:ID   0.000489115:0.00115364:0.1729:0.870329:335888:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.87002  ES:SE:LP:AF:SS:ID   0.000454275:0.00115088:0.159236:0.87002:335888:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869421 ES:SE:LP:AF:SS:ID   0.00043412:0.00114977:0.15135:0.869421:335888:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   0.000506039:0.00115182:0.180182:0.870219:335888:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   0.000502886:0.0011519:0.178864:0.870219:335888:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870222 ES:SE:LP:AF:SS:ID   0.000519271:0.00115194:0.185653:0.870222:335888:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870396 ES:SE:LP:AF:SS:ID   0.00048445:0.0011549:0.17078:0.870396:335888:rs3131954
1   761732  rs2286139   C   T   .   PASS    AF=0.867743 ES:SE:LP:AF:SS:ID   0.000377127:0.00114937:0.129114:0.867743:335888:rs2286139
1   766007  rs61768174  A   C   .   PASS    AF=0.106958 ES:SE:LP:AF:SS:ID   -0.00112572:0.0012798:0.421277:0.106958:335888:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.763932 ES:SE:LP:AF:SS:ID   -0.000561885:0.000912016:0.269352:0.763932:335888:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105257 ES:SE:LP:AF:SS:ID   0.00155392:0.00125923:0.66315:0.105257:335888:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00692766   ES:SE:LP:AF:SS:ID   0.0132512:0.00468252:2.33198:0.00692766:335888:rs12562811
1   769223  rs60320384  C   G   .   PASS    AF=0.128651 ES:SE:LP:AF:SS:ID   -0.000544927:0.00115807:0.195204:0.128651:335888:rs60320384
1   769224  rs141644775 G   A   .   PASS    AF=0.00143239   ES:SE:LP:AF:SS:ID   0.018665:0.010885:1.06353:0.00143239:335888:rs141644775
1   770181  rs146076599 A   G   .   PASS    AF=0.00907328   ES:SE:LP:AF:SS:ID   -0.00242895:0.00443767:0.233483:0.00907328:335888:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00692321   ES:SE:LP:AF:SS:ID   0.0132272:0.00470288:2.30848:0.00692321:335888:rs112563271
1   771823  rs2977605   T   C   .   PASS    AF=0.869934 ES:SE:LP:AF:SS:ID   0.000410089:0.00115293:0.141421:0.869934:335888:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.128709 ES:SE:LP:AF:SS:ID   -0.000487086:0.00115755:0.1714:0.128709:335888:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.870112 ES:SE:LP:AF:SS:ID   0.000420002:0.00115298:0.145297:0.870112:335888:rs2905039
1   774736  rs28830877  A   C   .   PASS    AF=0.998797 ES:SE:LP:AF:SS:ID   -0.00540658:0.011964:0.186193:0.998797:335888:rs28830877
1   776556  rs151160018 C   T   .   PASS    AF=0.00851871   ES:SE:LP:AF:SS:ID   -0.00742708:0.00432531:1.06571:0.00851871:335888:rs151160018
1   777122  rs2980319   A   T   .   PASS    AF=0.871122 ES:SE:LP:AF:SS:ID   0.000461241:0.00115493:0.161388:0.871122:335888:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.0961319    ES:SE:LP:AF:SS:ID   0.000878378:0.0013336:0.292329:0.0961319:335888:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.127871 ES:SE:LP:AF:SS:ID   -0.000541661:0.00115874:0.193703:0.127871:335888:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.127984 ES:SE:LP:AF:SS:ID   -0.000580571:0.00115718:0.210511:0.127984:335888:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.870455 ES:SE:LP:AF:SS:ID   0.000454788:0.00115304:0.1591:0.870455:335888:rs2977612
1   781367  rs149821290 A   C   .   PASS    AF=0.00989772   ES:SE:LP:AF:SS:ID   -0.00575767:0.00410257:0.794555:0.00989772:335888:rs149821290
1   781845  rs61768199  A   G   .   PASS    AF=0.1044   ES:SE:LP:AF:SS:ID   -0.000997015:0.00129661:0.354646:0.1044:335888:rs61768199
1   782721  rs185280546 G   A   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   0.000993455:0.00350838:0.109551:0.0143713:335888:rs185280546
1   782981  rs6594026   C   T   .   PASS    AF=0.128338 ES:SE:LP:AF:SS:ID   -0.000555119:0.00115781:0.199549:0.128338:335888:rs6594026
1   783193  rs145767270 G   C   .   PASS    AF=0.0143639    ES:SE:LP:AF:SS:ID   0.000206805:0.00352328:0.0208187:0.0143639:335888:rs145767270
1   783194  rs138555831 G   T   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   0.000227018:0.00352285:0.0229082:0.0143713:335888:rs138555831
1   783711  rs184266993 G   A   .   PASS    AF=0.00541372   ES:SE:LP:AF:SS:ID   -0.00071303:0.00563498:0.046092:0.00541372:335888:rs184266993
1   785050  rs2905062   G   A   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   0.000422926:0.00115321:0.146414:0.87014:335888:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.87009  ES:SE:LP:AF:SS:ID   0.000450509:0.00115394:0.157244:0.87009:335888:rs2980300