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-20554_1/ukb-d-20554_1.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-20554_1/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 16:50:22 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20554_1/ukb-d-20554_1.vcf.gz ...
Read summary statistics for 10169093 SNPs.
Dropped 7928 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, 1279232 SNPs remain.
After merging with regression SNP LD, 1279232 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.013 (0.0038)
Lambda GC: 1.0407
Mean Chi^2: 1.0359
Intercept: 1.006 (0.0062)
Ratio: 0.1664 (0.1731)
Analysis finished at Mon Nov 25 16:52:05 2019
Total time elapsed: 1.0m:42.51s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9425,
    "inflation_factor": 1.0296,
    "mean_EFFECT": 1.064e-06,
    "n": 117733,
    "n_snps": 10169093,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1093186,
    "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": 200410,
    "n_est": 117762.6461,
    "ratio_se_n": 1.0001,
    "mean_diff": 9.062e-06,
    "ratio_diff": 7.4914,
    "sd_y_est1": 0.1193,
    "sd_y_est2": 0.1193,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1279232,
    "ldsc_nsnp_merge_regression_ld": 1279232,
    "ldsc_observed_scale_h2_beta": 0.013,
    "ldsc_observed_scale_h2_se": 0.0038,
    "ldsc_intercept_beta": 1.006,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0407,
    "ldsc_mean_chisq": 1.0359,
    "ldsc_ratio": 0.1671
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
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 10161722 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 48731 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30368 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079617e+00 6.178065e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.876667e+07 5.606880e+07 3.02000e+02 3.251207e+07 6.968196e+07 1.147236e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.100000e-06 1.241100e-03 -1.11752e-02 -5.668000e-04 -7.300000e-06 5.535000e-04 1.278750e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.045500e-03 6.563000e-04 4.07500e-04 5.434000e-04 7.480000e-04 1.359500e-03 3.783400e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.956743e-01 2.898467e-01 3.00000e-07 2.430620e-01 4.937294e-01 7.468304e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.956729e-01 2.898475e-01 3.00000e-07 2.430598e-01 4.937270e-01 7.468303e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.507319e-01 2.629242e-01 7.38340e-03 3.566540e-02 1.437150e-01 4.004710e-01 9.926160e-01 ▇▂▂▁▁
numeric AF_reference 200410 0.9802922 NA NA NA NA NA 2.504648e-01 2.537849e-01 0.00000e+00 3.893770e-02 1.601440e-01 3.969650e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.177330e+05 0.000000e+00 1.17733e+05 1.177330e+05 1.177330e+05 1.177330e+05 1.177330e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0010018 0.0008567 0.2422942 0.2422912 0.1117700 0.1894970 117733
1 693731 rs12238997 A G -0.0006122 0.0008114 0.4505355 0.4505340 0.1167970 0.1417730 117733
1 707522 rs371890604 G C -0.0004155 0.0009103 0.6480925 0.6480915 0.0984203 0.1293930 117733
1 717587 rs144155419 G A -0.0010237 0.0021815 0.6388737 0.6388746 0.0157696 0.0045926 117733
1 730087 rs148120343 T C -0.0004322 0.0011290 0.7018544 0.7018535 0.0569438 0.0127796 117733
1 731718 rs142557973 T C -0.0006440 0.0007699 0.4028274 0.4028260 0.1227180 0.1543530 117733
1 732032 rs61770163 A C -0.0007602 0.0008205 0.3541474 0.3541447 0.1223370 0.1555510 117733
1 734349 rs141242758 T C -0.0005486 0.0007703 0.4763410 0.4763400 0.1219750 0.1525560 117733
1 749963 rs529266287 T TAA 0.0006266 0.0007590 0.4090120 0.4090109 0.8689330 0.7641770 117733
1 751343 rs28544273 T A -0.0005267 0.0007520 0.4836464 0.4836456 0.1237660 0.2426120 117733
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0014060 0.0009054 0.1204229 0.1204205 0.0554864 0.0309934 117733
23 154923374 rs111332691 T A -0.0004536 0.0009869 0.6457821 0.6457817 0.0447750 0.0116556 117733
23 154925045 rs509981 C T 0.0014615 0.0004752 0.0021013 0.0021008 0.2447700 0.3634440 117733
23 154925895 rs538470 C T 0.0013664 0.0004859 0.0049232 0.0049225 0.2412000 0.3634440 117733
23 154927581 rs644138 G A 0.0009689 0.0004471 0.0302287 0.0302267 0.3006190 0.4635760 117733
23 154929412 rs557132 C T 0.0014796 0.0004753 0.0018526 0.0018521 0.2446450 0.3568210 117733
23 154929637 rs35185538 CT C 0.0015118 0.0004966 0.0023298 0.0023292 0.2288480 0.3011920 117733
23 154929952 rs4012982 CAA C 0.0014883 0.0005002 0.0029287 0.0029283 0.2387180 0.3165560 117733
23 154930230 rs781880 A G 0.0014558 0.0004752 0.0021858 0.0021854 0.2450680 0.3618540 117733
23 154930487 rs781879 T A 0.0048121 0.0016150 0.0028872 0.0028865 0.0196901 0.1263580 117733

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11177  ES:SE:LP:AF:SS:ID   -0.00100176:0.000856733:0.615657:0.11177:117733:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116797 ES:SE:LP:AF:SS:ID   -0.000612202:0.000811374:0.346271:0.116797:117733:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0984203    ES:SE:LP:AF:SS:ID   -0.000415466:0.000910281:0.188363:0.0984203:117733:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157696    ES:SE:LP:AF:SS:ID   -0.0010237:0.00218146:0.194585:0.0157696:117733:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569438    ES:SE:LP:AF:SS:ID   -0.000432188:0.00112896:0.153753:0.0569438:117733:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122718 ES:SE:LP:AF:SS:ID   -0.000644049:0.000769855:0.394881:0.122718:117733:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122337 ES:SE:LP:AF:SS:ID   -0.000760219:0.000820457:0.450816:0.122337:117733:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121975 ES:SE:LP:AF:SS:ID   -0.000548581:0.000770261:0.322082:0.121975:117733:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868933 ES:SE:LP:AF:SS:ID   0.000626616:0.00075895:0.388264:0.868933:117733:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123766 ES:SE:LP:AF:SS:ID   -0.000526712:0.000751961:0.315472:0.123766:117733:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1434   ES:SE:LP:AF:SS:ID   -0.000199941:0.00074372:0.103444:0.1434:117733:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123888 ES:SE:LP:AF:SS:ID   -0.000526006:0.00075092:0.315489:0.123888:117733:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869714 ES:SE:LP:AF:SS:ID   0.000514316:0.000731333:0.317046:0.869714:117733:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874485 ES:SE:LP:AF:SS:ID   0.000332383:0.000743589:0.18384:0.874485:117733:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129745 ES:SE:LP:AF:SS:ID   -0.000497472:0.000733381:0.303149:0.129745:117733:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365403    ES:SE:LP:AF:SS:ID   -0.00332713:0.00133192:1.90339:0.0365403:117733:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869307 ES:SE:LP:AF:SS:ID   0.000459005:0.000730638:0.27584:0.869307:117733:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869378 ES:SE:LP:AF:SS:ID   0.00044922:0.000730909:0.268559:0.869378:117733:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869306 ES:SE:LP:AF:SS:ID   0.000457172:0.000730619:0.274503:0.869306:117733:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.86938  ES:SE:LP:AF:SS:ID   0.000514676:0.000729274:0.31844:0.86938:117733:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127028 ES:SE:LP:AF:SS:ID   -0.000587878:0.000744397:0.366852:0.127028:117733:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868903 ES:SE:LP:AF:SS:ID   0.000533261:0.000727361:0.333977:0.868903:117733:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868299 ES:SE:LP:AF:SS:ID   0.000413895:0.000727078:0.244749:0.868299:117733:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869089 ES:SE:LP:AF:SS:ID   0.000541884:0.000728078:0.340354:0.869089:117733:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869096 ES:SE:LP:AF:SS:ID   0.00054195:0.00072813:0.340375:0.869096:117733:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869098 ES:SE:LP:AF:SS:ID   0.000541992:0.000728133:0.340406:0.869098:117733:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869534 ES:SE:LP:AF:SS:ID   0.000510901:0.000729999:0.315143:0.869534:117733:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996366    ES:SE:LP:AF:SS:ID   -0.000512081:0.000848559:0.262651:0.0996366:117733:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873583 ES:SE:LP:AF:SS:ID   0.000469974:0.000741152:0.279008:0.873583:117733:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862878 ES:SE:LP:AF:SS:ID   0.000393411:0.000726891:0.230361:0.862878:117733:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868273 ES:SE:LP:AF:SS:ID   0.000662735:0.000733867:0.435939:0.868273:117733:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865286 ES:SE:LP:AF:SS:ID   0.000652618:0.000733967:0.427226:0.865286:117733:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0998136    ES:SE:LP:AF:SS:ID   -0.000521173:0.000877064:0.257775:0.0998136:117733:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870572 ES:SE:LP:AF:SS:ID   0.000527979:0.000742622:0.321384:0.870572:117733:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870572 ES:SE:LP:AF:SS:ID   0.000527983:0.000742622:0.321387:0.870572:117733:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870571 ES:SE:LP:AF:SS:ID   0.000528005:0.000742623:0.321404:0.870571:117733:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870892 ES:SE:LP:AF:SS:ID   0.000501755:0.000742937:0.301513:0.870892:117733:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126623 ES:SE:LP:AF:SS:ID   -0.000637451:0.000743575:0.407498:0.126623:117733:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106376 ES:SE:LP:AF:SS:ID   -0.000532643:0.00080814:0.292571:0.106376:117733:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854328 ES:SE:LP:AF:SS:ID   0.000290982:0.00072671:0.161872:0.854328:117733:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839072 ES:SE:LP:AF:SS:ID   -0.000963336:0.00072016:0.742305:0.839072:117733:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762955 ES:SE:LP:AF:SS:ID   -0.000228874:0.000577184:0.160075:0.762955:117733:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105259 ES:SE:LP:AF:SS:ID   0.000835086:0.000798529:0.5292:0.105259:117733:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00772744   ES:SE:LP:AF:SS:ID   -0.00184296:0.00295021:0.273943:0.00772744:117733:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.130028 ES:SE:LP:AF:SS:ID   -0.000758582:0.000732996:0.521845:0.130028:117733:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.12973  ES:SE:LP:AF:SS:ID   -0.000615734:0.000732113:0.397583:0.12973:117733:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104502 ES:SE:LP:AF:SS:ID   0.000888542:0.000804794:0.56933:0.104502:117733:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00918492   ES:SE:LP:AF:SS:ID   2.57934e-05:0.00281302:0.00318898:0.00918492:117733:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00774957   ES:SE:LP:AF:SS:ID   -0.00181517:0.00296278:0.267524:0.00774957:117733:rs112563271
1   770886  rs371458725 G   A   .   PASS    AF=0.103549 ES:SE:LP:AF:SS:ID   0.000854059:0.000811498:0.53373:0.103549:117733:rs371458725