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_5/ukb-d-20554_5.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_5/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 16:51:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20554_5/ukb-d-20554_5.vcf.gz ...
Read summary statistics for 9663417 SNPs.
Dropped 7280 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, 1275101 SNPs remain.
After merging with regression SNP LD, 1275101 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0046 (0.0039)
Lambda GC: 1.0034
Mean Chi^2: 1.0077
Intercept: 0.9973 (0.0062)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:52:40 2019
Total time elapsed: 1.0m:35.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9398,
    "inflation_factor": 1.0058,
    "mean_EFFECT": -3.2484e-07,
    "n": 117733,
    "n_snps": 9663417,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1061560,
    "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": 192596,
    "n_est": 117688.3912,
    "ratio_se_n": 0.9998,
    "mean_diff": -2.1625e-06,
    "ratio_diff": 3.1991,
    "sd_y_est1": 0.1027,
    "sd_y_est2": 0.1027,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1275101,
    "ldsc_nsnp_merge_regression_ld": 1275101,
    "ldsc_observed_scale_h2_beta": 0.0046,
    "ldsc_observed_scale_h2_se": 0.0039,
    "ldsc_intercept_beta": 0.9973,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0034,
    "ldsc_mean_chisq": 1.0077,
    "ldsc_ratio": -0.3506
}

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 9656684 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47013 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29665 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079401e+00 6.175442e+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 7.873862e+07 5.611436e+07 3.02000e+02 3.243154e+07 6.962364e+07 1.147469e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.000000e-07 9.483000e-04 -8.46170e-03 -4.606000e-04 -4.400000e-06 4.511000e-04 1.037920e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.238000e-04 4.671000e-04 3.50700e-04 4.632000e-04 6.169000e-04 1.053600e-03 2.701000e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.994526e-01 2.888493e-01 0.00000e+00 2.491288e-01 4.987490e-01 7.501256e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.994512e-01 2.888501e-01 0.00000e+00 2.491262e-01 4.987471e-01 7.501244e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.625072e-01 2.628596e-01 1.00080e-02 4.475670e-02 1.607110e-01 4.175360e-01 9.899920e-01 ▇▂▂▁▁
numeric AF_reference 192596 0.9800696 NA NA NA NA NA 2.619783e-01 2.536682e-01 0.00000e+00 5.091850e-02 1.759190e-01 4.131390e-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 -0.0006199 0.0007374 0.4005327 0.4005305 0.1117700 0.1894970 117733
1 693731 rs12238997 A G -0.0003275 0.0006984 0.6390738 0.6390739 0.1167970 0.1417730 117733
1 707522 rs371890604 G C -0.0000928 0.0007835 0.9057230 0.9057227 0.0984203 0.1293930 117733
1 717587 rs144155419 G A -0.0001103 0.0018776 0.9531479 0.9531483 0.0157696 0.0045926 117733
1 730087 rs148120343 T C -0.0004123 0.0009717 0.6713546 0.6713531 0.0569438 0.0127796 117733
1 731718 rs142557973 T C -0.0004732 0.0006626 0.4751229 0.4751221 0.1227180 0.1543530 117733
1 732032 rs61770163 A C -0.0001186 0.0007062 0.8665881 0.8665876 0.1223370 0.1555510 117733
1 734349 rs141242758 T C -0.0004356 0.0006630 0.5111884 0.5111866 0.1219750 0.1525560 117733
1 749963 rs529266287 T TAA 0.0002866 0.0006532 0.6608136 0.6608116 0.8689330 0.7641770 117733
1 751343 rs28544273 T A -0.0003129 0.0006472 0.6287674 0.6287663 0.1237660 0.2426120 117733
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0004300 0.0007793 0.5811028 0.5811022 0.0554864 0.0309934 117733
23 154923374 rs111332691 T A -0.0012495 0.0008495 0.1413211 0.1413185 0.0447750 0.0116556 117733
23 154925045 rs509981 C T 0.0008773 0.0004090 0.0319558 0.0319533 0.2447700 0.3634440 117733
23 154925895 rs538470 C T 0.0009122 0.0004182 0.0291743 0.0291728 0.2412000 0.3634440 117733
23 154927581 rs644138 G A 0.0008904 0.0003848 0.0206814 0.0206799 0.3006190 0.4635760 117733
23 154929412 rs557132 C T 0.0008934 0.0004091 0.0289821 0.0289804 0.2446450 0.3568210 117733
23 154929637 rs35185538 CT C 0.0007967 0.0004274 0.0623146 0.0623123 0.2288480 0.3011920 117733
23 154929952 rs4012982 CAA C 0.0008663 0.0004306 0.0442232 0.0442211 0.2387180 0.3165560 117733
23 154930230 rs781880 A G 0.0008998 0.0004090 0.0278099 0.0278080 0.2450680 0.3618540 117733
23 154930487 rs781879 T A 0.0013043 0.0013901 0.3481080 0.3481084 0.0196901 0.1263580 117733

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11177  ES:SE:LP:AF:SS:ID   -0.000619919:0.000737407:0.397362:0.11177:117733:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116797 ES:SE:LP:AF:SS:ID   -0.000327529:0.000698365:0.194449:0.116797:117733:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0984203    ES:SE:LP:AF:SS:ID   -9.27935e-05:0.000783495:0.0430046:0.0984203:117733:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157696    ES:SE:LP:AF:SS:ID   -0.000110317:0.00187762:0.0208397:0.0157696:117733:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569438    ES:SE:LP:AF:SS:ID   -0.000412291:0.000971716:0.173048:0.0569438:117733:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122718 ES:SE:LP:AF:SS:ID   -0.000473229:0.000662628:0.323194:0.122718:117733:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122337 ES:SE:LP:AF:SS:ID   -0.000118635:0.000706184:0.0621873:0.122337:117733:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121975 ES:SE:LP:AF:SS:ID   -0.00043557:0.000662977:0.291419:0.121975:117733:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868933 ES:SE:LP:AF:SS:ID   0.000286638:0.000653242:0.179921:0.868933:117733:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123766 ES:SE:LP:AF:SS:ID   -0.000312911:0.000647227:0.20151:0.123766:117733:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1434   ES:SE:LP:AF:SS:ID   -6.39374e-05:0.000640133:0.036005:0.1434:117733:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123888 ES:SE:LP:AF:SS:ID   -0.000301557:0.00064633:0.193271:0.123888:117733:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869714 ES:SE:LP:AF:SS:ID   0.000115683:0.000629472:0.0684465:0.869714:117733:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874485 ES:SE:LP:AF:SS:ID   -6.04236e-05:0.00064002:0.0339597:0.874485:117733:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129745 ES:SE:LP:AF:SS:ID   -0.000286825:0.000631235:0.187387:0.129745:117733:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365403    ES:SE:LP:AF:SS:ID   -0.000368124:0.00114644:0.126021:0.0365403:117733:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869307 ES:SE:LP:AF:SS:ID   0.000101001:0.000628874:0.0592824:0.869307:117733:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869378 ES:SE:LP:AF:SS:ID   9.24209e-05:0.000629107:0.0539385:0.869378:117733:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869306 ES:SE:LP:AF:SS:ID   9.8227e-05:0.000628857:0.0575574:0.869306:117733:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.86938  ES:SE:LP:AF:SS:ID   0.000116327:0.0006277:0.0690627:0.86938:117733:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127028 ES:SE:LP:AF:SS:ID   -0.000354827:0.000640716:0.236782:0.127028:117733:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868903 ES:SE:LP:AF:SS:ID   0.000153578:0.000626054:0.0935486:0.868903:117733:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868299 ES:SE:LP:AF:SS:ID   0.000107671:0.00062581:0.063789:0.868299:117733:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869089 ES:SE:LP:AF:SS:ID   0.000137489:0.00062667:0.0828402:0.869089:117733:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869096 ES:SE:LP:AF:SS:ID   0.000137274:0.000626715:0.082693:0.869096:117733:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869098 ES:SE:LP:AF:SS:ID   0.000137967:0.000626718:0.0831456:0.869098:117733:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869534 ES:SE:LP:AF:SS:ID   0.000102121:0.000628324:0.0600372:0.869534:117733:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996366    ES:SE:LP:AF:SS:ID   -0.000375581:0.00073037:0.216748:0.0996366:117733:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873583 ES:SE:LP:AF:SS:ID   0.000120787:0.000637923:0.0706715:0.873583:117733:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862878 ES:SE:LP:AF:SS:ID   3.03979e-05:0.000625648:0.0171641:0.862878:117733:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868273 ES:SE:LP:AF:SS:ID   0.000223644:0.000631654:0.140686:0.868273:117733:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865286 ES:SE:LP:AF:SS:ID   0.000242815:0.00063174:0.15446:0.865286:117733:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0998136    ES:SE:LP:AF:SS:ID   -0.000299556:0.000754905:0.160204:0.0998136:117733:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870572 ES:SE:LP:AF:SS:ID   0.000274685:0.000639188:0.175624:0.870572:117733:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870572 ES:SE:LP:AF:SS:ID   0.000274688:0.000639188:0.175626:0.870572:117733:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870571 ES:SE:LP:AF:SS:ID   0.000274503:0.00063919:0.175488:0.870571:117733:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870892 ES:SE:LP:AF:SS:ID   0.00026016:0.00063946:0.164865:0.870892:117733:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126623 ES:SE:LP:AF:SS:ID   -0.000394846:0.000640009:0.269803:0.126623:117733:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106376 ES:SE:LP:AF:SS:ID   -0.00056826:0.000695579:0.383049:0.106376:117733:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854328 ES:SE:LP:AF:SS:ID   0.000103205:0.000625493:0.0610077:0.854328:117733:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839072 ES:SE:LP:AF:SS:ID   -0.000369598:0.000619858:0.258848:0.839072:117733:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762955 ES:SE:LP:AF:SS:ID   -2.61881e-05:0.000496792:0.0186526:0.762955:117733:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105259 ES:SE:LP:AF:SS:ID   0.000107042:0.000687311:0.0573779:0.105259:117733:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.130028 ES:SE:LP:AF:SS:ID   -0.000521703:0.000630903:0.389034:0.130028:117733:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.12973  ES:SE:LP:AF:SS:ID   -0.000437362:0.000630143:0.3119:0.12973:117733:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104502 ES:SE:LP:AF:SS:ID   0.000121532:0.000692704:0.0651331:0.104502:117733:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.103549 ES:SE:LP:AF:SS:ID   4.7974e-05:0.000698474:0.0244574:0.103549:117733:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.82917  ES:SE:LP:AF:SS:ID   -6.29833e-05:0.000614775:0.0369681:0.82917:117733:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.868945 ES:SE:LP:AF:SS:ID   0.000225149:0.000627201:0.1429:0.868945:117733:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129808 ES:SE:LP:AF:SS:ID   -0.000416085:0.000629799:0.293428:0.129808:117733:rs59066358