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-d-import/processed/ukb-d-20477/ukb-d-20477.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-d-import/processed/ukb-d-20477/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 17:19:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20477/ukb-d-20477.vcf.gz ...
Read summary statistics for 9630472 SNPs.
Dropped 7219 SNPs with duplicated rs numbers.
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, 1274653 SNPs remain.
After merging with regression SNP LD, 1274653 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0996 (0.0799)
Lambda GC: 1.005
Mean Chi^2: 1.0073
Intercept: 0.9959 (0.0057)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:21:01 2019
Total time elapsed: 1.0m:34.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9396,
    "inflation_factor": 1.0039,
    "mean_EFFECT": 0,
    "n": 5788,
    "n_snps": 9630472,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1059213,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 192058,
    "n_est": 5799.1653,
    "ratio_se_n": 1.001,
    "mean_diff": 0,
    "ratio_diff": 8.5468,
    "sd_y_est1": 0.4099,
    "sd_y_est2": 0.4103,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1274653,
    "ldsc_nsnp_merge_regression_ld": 1274653,
    "ldsc_observed_scale_h2_beta": 0.0996,
    "ldsc_observed_scale_h2_se": 0.0799,
    "ldsc_intercept_beta": 0.9959,
    "ldsc_intercept_se": 0.0057,
    "ldsc_lambda_gc": 1.005,
    "ldsc_mean_chisq": 1.0073,
    "ldsc_ratio": -0.5616
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 9623796 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 46896 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29596 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.081155e+00 6.175264e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.872128e+07 5.610858e+07 302.0000000 3.243048e+07 6.959361e+07 1.147359e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.260000e-05 1.691330e-02 -0.1605950 -8.229900e-03 -3.980000e-05 8.118000e-03 1.899220e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.474370e-02 8.301000e-03 0.0063461 8.332700e-03 1.107420e-02 1.882800e-02 4.657580e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.994844e-01 2.890228e-01 0.0000005 2.492011e-01 4.991637e-01 7.502206e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.994568e-01 2.890394e-01 0.0000005 2.491532e-01 4.991371e-01 7.502097e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.633202e-01 2.628204e-01 0.0102043 4.541990e-02 1.619445e-01 4.188810e-01 9.897960e-01 ▇▂▂▁▁
numeric AF_reference 192058 0.9800573 NA NA NA NA NA 2.627520e-01 2.536472e-01 0.0000000 5.171730e-02 1.769170e-01 4.141370e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.788000e+03 0.000000e+00 5788.0000000 5.788000e+03 5.788000e+03 5.788000e+03 5.788000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0066211 0.0134294 0.6220095 0.6219902 0.1114370 0.1894970 5788
1 693731 rs12238997 A G -0.0012248 0.0126050 0.9225939 0.9225913 0.1163710 0.1417730 5788
1 707522 rs371890604 G C -0.0052939 0.0142122 0.7095418 0.7095282 0.0982066 0.1293930 5788
1 717587 rs144155419 G A -0.0159514 0.0351649 0.6501207 0.6501044 0.0144735 0.0045926 5788
1 730087 rs148120343 T C -0.0152413 0.0176540 0.3879877 0.3879538 0.0564711 0.0127796 5788
1 731718 rs142557973 T C -0.0054234 0.0120460 0.6525653 0.6525488 0.1216320 0.1543530 5788
1 732032 rs61770163 A C -0.0018926 0.0129442 0.8837599 0.8837551 0.1209240 0.1555510 5788
1 734349 rs141242758 T C -0.0041116 0.0120509 0.7329730 0.7329610 0.1210930 0.1525560 5788
1 749963 rs529266287 T TAA 0.0081631 0.0119120 0.4931942 0.4931649 0.8696050 0.7641770 5788
1 751343 rs28544273 T A -0.0087671 0.0117585 0.4559403 0.4559100 0.1228050 0.2426120 5788
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0032154 0.0140963 0.8195759 0.8195683 0.0563380 0.0309934 5788
23 154923374 rs111332691 T A 0.0030968 0.0148784 0.8351279 0.8351202 0.0476849 0.0116556 5788
23 154925045 rs509981 C T -0.0045306 0.0075639 0.5492094 0.5491870 0.2394350 0.3634440 5788
23 154925895 rs538470 C T -0.0066406 0.0077304 0.3903624 0.3903263 0.2364390 0.3634440 5788
23 154927581 rs644138 G A -0.0026366 0.0070960 0.7102316 0.7102173 0.2962840 0.4635760 5788
23 154929412 rs557132 C T -0.0044874 0.0075645 0.5530559 0.5530331 0.2393410 0.3568210 5788
23 154929637 rs35185538 CT C 0.0004538 0.0079089 0.9542411 0.9542394 0.2260290 0.3011920 5788
23 154929952 rs4012982 CAA C -0.0029163 0.0079705 0.7144684 0.7144544 0.2332690 0.3165560 5788
23 154930230 rs781880 A G -0.0053138 0.0075676 0.4825974 0.4825693 0.2395290 0.3618540 5788
23 154930487 rs781879 T A -0.0295948 0.0250191 0.2369021 0.2368534 0.0204764 0.1263580 5788

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111437 ES:SE:LP:AF:SS:ID   -0.00662112:0.0134294:0.206203:0.111437:5788:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116371 ES:SE:LP:AF:SS:ID   -0.00122483:0.012605:0.0349894:0.116371:5788:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0982066    ES:SE:LP:AF:SS:ID   -0.0052939:0.0142122:0.149022:0.0982066:5788:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0144735    ES:SE:LP:AF:SS:ID   -0.0159514:0.0351649:0.187006:0.0144735:5788:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0564711    ES:SE:LP:AF:SS:ID   -0.0152413:0.017654:0.411182:0.0564711:5788:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121632 ES:SE:LP:AF:SS:ID   -0.0054234:0.012046:0.185376:0.121632:5788:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.120924 ES:SE:LP:AF:SS:ID   -0.00189258:0.0129442:0.0536657:0.120924:5788:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121093 ES:SE:LP:AF:SS:ID   -0.00411164:0.0120509:0.134912:0.121093:5788:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.869605 ES:SE:LP:AF:SS:ID   0.0081631:0.011912:0.306982:0.869605:5788:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.122805 ES:SE:LP:AF:SS:ID   -0.00876712:0.0117585:0.341092:0.122805:5788:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142701 ES:SE:LP:AF:SS:ID   -0.0133461:0.0115863:0.603076:0.142701:5788:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123136 ES:SE:LP:AF:SS:ID   -0.00942521:0.011736:0.37474:0.123136:5788:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870149 ES:SE:LP:AF:SS:ID   0.00719764:0.0114404:0.276315:0.870149:5788:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874578 ES:SE:LP:AF:SS:ID   0.00883132:0.0116061:0.34995:0.874578:5788:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129788 ES:SE:LP:AF:SS:ID   -0.00822026:0.0114451:0.325467:0.129788:5788:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0378369    ES:SE:LP:AF:SS:ID   0.0091677:0.0203009:0.186032:0.0378369:5788:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869286 ES:SE:LP:AF:SS:ID   0.00727304:0.0114182:0.280529:0.869286:5788:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869465 ES:SE:LP:AF:SS:ID   0.00688267:0.0114238:0.262112:0.869465:5788:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869264 ES:SE:LP:AF:SS:ID   0.00726663:0.0114171:0.280259:0.869264:5788:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869676 ES:SE:LP:AF:SS:ID   0.0077779:0.0114064:0.305098:0.869676:5788:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126599 ES:SE:LP:AF:SS:ID   -0.00858026:0.0116444:0.336075:0.126599:5788:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869299 ES:SE:LP:AF:SS:ID   0.0084044:0.0113782:0.337097:0.869299:5788:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868219 ES:SE:LP:AF:SS:ID   0.00843664:0.0113659:0.339182:0.868219:5788:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869427 ES:SE:LP:AF:SS:ID   0.00771138:0.0113894:0.302429:0.869427:5788:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869434 ES:SE:LP:AF:SS:ID   0.0077076:0.0113903:0.302217:0.869434:5788:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869441 ES:SE:LP:AF:SS:ID   0.00769295:0.0113905:0.3015:0.869441:5788:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869759 ES:SE:LP:AF:SS:ID   0.00778763:0.0114148:0.305294:0.869759:5788:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0999553    ES:SE:LP:AF:SS:ID   -0.0138766:0.0131623:0.534909:0.0999553:5788:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.87403  ES:SE:LP:AF:SS:ID   0.00919217:0.0115752:0.369416:0.87403:5788:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862045 ES:SE:LP:AF:SS:ID   0.00707091:0.0113429:0.273221:0.862045:5788:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868415 ES:SE:LP:AF:SS:ID   0.00589413:0.0114723:0.216503:0.868415:5788:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865748 ES:SE:LP:AF:SS:ID   0.00538495:0.0114998:0.194083:0.865748:5788:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.099936 ES:SE:LP:AF:SS:ID   -0.00778647:0.0135847:0.246764:0.099936:5788:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870871 ES:SE:LP:AF:SS:ID   0.00808846:0.0116117:0.31328:0.870871:5788:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870871 ES:SE:LP:AF:SS:ID   0.00808846:0.0116117:0.31328:0.870871:5788:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870868 ES:SE:LP:AF:SS:ID   0.00808843:0.0116118:0.313275:0.870868:5788:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871205 ES:SE:LP:AF:SS:ID   0.00910076:0.0116175:0.363067:0.871205:5788:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126025 ES:SE:LP:AF:SS:ID   -0.0100808:0.0116191:0.413809:0.126025:5788:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106791 ES:SE:LP:AF:SS:ID   -0.007451:0.012553:0.257411:0.106791:5788:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854662 ES:SE:LP:AF:SS:ID   0.00605098:0.0113619:0.225956:0.854662:5788:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839333 ES:SE:LP:AF:SS:ID   0.0190976:0.0110617:1.07408:0.839333:5788:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762639 ES:SE:LP:AF:SS:ID   0.0167636:0.00893993:1.21593:0.762639:5788:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105563 ES:SE:LP:AF:SS:ID   -0.0235696:0.0123112:1.25487:0.105563:5788:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.129921 ES:SE:LP:AF:SS:ID   -0.0078802:0.011441:0.308922:0.129921:5788:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129489 ES:SE:LP:AF:SS:ID   -0.00719518:0.0114314:0.276464:0.129489:5788:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.105249 ES:SE:LP:AF:SS:ID   -0.0249727:0.0123743:1.36024:0.105249:5788:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.104308 ES:SE:LP:AF:SS:ID   -0.0246657:0.0124961:1.31476:0.104308:5788:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.831409 ES:SE:LP:AF:SS:ID   0.00423121:0.0112588:0.150539:0.831409:5788:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.868843 ES:SE:LP:AF:SS:ID   0.00631798:0.0113741:0.237626:0.868843:5788:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129551 ES:SE:LP:AF:SS:ID   -0.00717342:0.0114259:0.275604:0.129551:5788:rs59066358