Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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 /data/cromwell-executions/qc/963924ff-2675-4e14-bc36-bf5a43ad73bf/call-ldsc/inputs/-261043579/ieu-b-4913.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4913/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 03:22:37 2022
Reading summary statistics from /data/cromwell-executions/qc/963924ff-2675-4e14-bc36-bf5a43ad73bf/call-ldsc/inputs/-261043579/ieu-b-4913.vcf.gz ...
Read summary statistics for 7238681 SNPs.
Dropped 124096 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1115382 SNPs remain.
After merging with regression SNP LD, 1115382 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0025 (0.0012)
Lambda GC: 0.9911
Mean Chi^2: 0.9939
Intercept: 1.013 (0.0069)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Fri Mar  4 03:24:02 2022
Total time elapsed: 1.0m:24.99s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9171,
    "inflation_factor": 1,
    "mean_EFFECT": -7.4415e-08,
    "n": "-Inf",
    "n_snps": 7239512,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 931760,
    "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": 921935,
    "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": 1115382,
    "ldsc_nsnp_merge_regression_ld": 1115382,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.013,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 0.9911,
    "ldsc_mean_chisq": 0.9939,
    "ldsc_ratio": -2.1311
}

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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 540 0.9999254 3 58 0 7219095 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 12299 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 50514 0 NA NA NA NA NA NA NA NA NA NA
logical N 7239512 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 8.888205e+00 5.973368e+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 NA NA 7.836990e+07 5.646775e+07 302.0000000 3.193214e+07 6.876511e+07 1.143428e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.000000e-07 9.000000e-05 -0.0009332 -5.550000e-05 -7.000000e-07 5.440000e-05 9.121000e-04 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 8.660000e-05 2.500000e-05 0.0000516 6.630000e-05 7.720000e-05 1.011000e-04 2.865000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.013569e-01 2.890262e-01 0.0000003 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 5.013580e-01 2.890006e-01 0.0000003 2.508019e-01 5.025374e-01 7.519612e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.710052e-01 2.681120e-01 0.0457880 1.321140e-01 3.023950e-01 5.760400e-01 9.542120e-01 ▇▃▃▂▂
numeric AF_reference 921935 0.8726523 NA NA NA NA NA NA NA 3.311217e-01 2.426082e-01 0.0000000 1.295930e-01 2.695690e-01 4.966050e-01 1.000000e+00 ▇▆▃▂▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10177 rs1264289758 AC A 0.0000025 0.0000937 0.9800000 0.9791073 0.601340 NA NA
1 10352 rs1557426776 TA T 0.0001968 0.0000965 0.0409996 0.0413819 0.607027 NA NA
1 11008 rs575272151 C G -0.0001825 0.0001604 0.2599998 0.2550421 0.086187 0.0880591 NA
1 11012 rs544419019 C G -0.0001825 0.0001604 0.2599998 0.2550421 0.086187 0.0880591 NA
1 13110 rs540538026 G A 0.0004835 0.0002130 0.0230001 0.0232157 0.058749 0.0267572 NA
1 13116 rs62635286 T G 0.0000783 0.0001262 0.5300002 0.5347623 0.189425 0.0970447 NA
1 13118 rs200579949 A G 0.0000783 0.0001262 0.5300002 0.5347623 0.189425 0.0970447 NA
1 13273 rs531730856 G C -0.0000305 0.0001479 0.8400000 0.8365377 0.133931 0.0950479 NA
1 14464 rs546169444 A T 0.0000357 0.0001343 0.7899998 0.7906527 0.157055 0.0958466 NA
1 14599 rs531646671 T A 0.0001432 0.0001225 0.2399999 0.2423221 0.191582 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.00e+00 6.00e-05 1.0000000 0.9996961 0.751496 0.643179 NA
23 154901964 rs697726 G A 6.73e-05 6.33e-05 0.2900000 0.2875335 0.347489 0.117616 NA
23 154902105 rs696316 G T -4.90e-06 6.00e-05 0.9400001 0.9350423 0.751448 0.636026 NA
23 154902889 rs697725 A T 3.00e-07 5.99e-05 1.0000000 0.9954944 0.751120 0.584106 NA
23 154903118 rs479770 G A -2.00e-07 6.00e-05 1.0000000 0.9968245 0.751539 0.643444 NA
23 154903224 rs480725 A T -2.00e-07 6.00e-05 1.0000000 0.9967541 0.751542 0.643444 NA
23 154903937 rs674707 G A -3.00e-07 6.00e-05 1.0000000 0.9965371 0.751552 0.643444 NA
23 154909055 rs473529 C G -1.34e-05 5.65e-05 0.8100000 0.8118468 0.305111 0.463046 NA
23 154918266 rs642043 C T -1.13e-05 5.66e-05 0.8400000 0.8419158 0.302976 0.478675 NA
23 154927581 rs644138 G A -1.11e-05 5.67e-05 0.8400000 0.8446365 0.302848 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.60134  ES:SE:LP:AF:ID  2.45288e-06:9.3664e-05:0.00877392:0.60134:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607027 ES:SE:LP:AF:ID  0.000196758:9.6465e-05:1.38722:0.607027:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086187 ES:SE:LP:AF:ID  -0.000182538:0.000160376:0.585027:0.086187:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086187 ES:SE:LP:AF:ID  -0.000182538:0.000160376:0.585027:0.086187:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058749 ES:SE:LP:AF:ID  0.00048347:0.000212995:1.63827:0.058749:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189425 ES:SE:LP:AF:ID  7.83241e-05:0.000126176:0.275724:0.189425:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189425 ES:SE:LP:AF:ID  7.83241e-05:0.000126176:0.275724:0.189425:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133931 ES:SE:LP:AF:ID  -3.0517e-05:0.000147908:0.0757207:0.133931:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157055 ES:SE:LP:AF:ID  3.56578e-05:0.000134323:0.102373:0.157055:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191582 ES:SE:LP:AF:ID  0.00014317:0.000122451:0.619789:0.191582:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191582 ES:SE:LP:AF:ID  0.00014317:0.000122451:0.619789:0.191582:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473998 ES:SE:LP:AF:ID  -3.75241e-05:9.49867e-05:0.161151:0.473998:rs6682385
1   15211   rs3982632   T   G   .   PASS    AF=0.741422 ES:SE:LP:AF:ID  3.63155e-05:0.00010985:0.130768:0.741422:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275226 ES:SE:LP:AF:ID  0.000127386:0.00011264:0.585027:0.275226:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581025 ES:SE:LP:AF:ID  -6.32402e-07:9.28739e-05:0.00436481:0.581025:rs557514207
1   30923   rs1165072081    G   T   .   PASS    AF=0.910278 ES:SE:LP:AF:ID  -0.000103497:0.00017536:0.251812:0.910278:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062674 ES:SE:LP:AF:ID  0.00019104:0.000200076:0.468521:0.062674:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623642 ES:SE:LP:AF:ID  6.71488e-05:0.000111428:0.259637:0.623642:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092976 ES:SE:LP:AF:ID  0.00018662:0.000171379:0.552842:0.092976:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213485 ES:SE:LP:AF:ID  -0.000108414:0.000119121:0.443698:0.213485:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154524 ES:SE:LP:AF:ID  -0.000100474:0.000133842:0.346787:0.154524:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400422 ES:SE:LP:AF:ID  4.79429e-06:0.000110382:0.0132283:0.400422:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414843 ES:SE:LP:AF:ID  2.05601e-05:8.72596e-05:0.091515:0.414843:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417234 ES:SE:LP:AF:ID  7.44966e-05:0.000100776:0.337242:0.417234:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253877 ES:SE:LP:AF:ID  0.000129392:0.00011337:0.60206:0.253877:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090046 ES:SE:LP:AF:ID  0.000350995:0.00017263:1.37675:0.090046:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088882 ES:SE:LP:AF:ID  0.000333657:0.000173289:1.26761:0.088882:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081034 ES:SE:LP:AF:ID  0.000372065:0.000179753:1.42022:0.081034:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438475 ES:SE:LP:AF:ID  -9.98136e-05:9.58067e-05:0.522879:0.438475:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382128 ES:SE:LP:AF:ID  0.0001783:0.00010299:1.08092:0.382128:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158844 ES:SE:LP:AF:ID  2.89744e-05:0.000131118:0.0809219:0.158844:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683994 ES:SE:LP:AF:ID  0.000211638:0.000102076:1.42022:0.683994:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.07964  ES:SE:LP:AF:ID  0.000313549:0.000181935:1.07058:0.07964:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070756 ES:SE:LP:AF:ID  -4.83652e-05:0.000184532:0.102373:0.070756:rs367789441
1   69761   rs200505207 A   T   .   PASS    AF=0.073897 ES:SE:LP:AF:ID  -0.000139676:0.000181515:0.356547:0.073897:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751141 ES:SE:LP:AF:ID  -0.000183301:0.000115617:0.958607:0.751141:rs200676709
1   76838   rs563953605 T   G   .   PASS    AF=0.077207 ES:SE:LP:AF:ID  0.000186913:0.000185416:0.508638:0.077207:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077453 ES:SE:LP:AF:ID  0.000177556:0.000179075:0.49485:0.077453:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.07701  ES:SE:LP:AF:ID  0.000173722:0.000185466:0.455932:0.07701:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.07701  ES:SE:LP:AF:ID  0.000173722:0.000185466:0.455932:0.07701:rs62641297
1   81587   rs536406113 C   T   .   PASS    AF=0.060963 ES:SE:LP:AF:ID  -0.000105368:0.000196601:0.229148:0.060963:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075413 ES:SE:LP:AF:ID  0.000161275:0.000181337:0.431798:0.075413:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.07544  ES:SE:LP:AF:ID  0.000160769:0.0001813:0.420216:0.07544:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352686 ES:SE:LP:AF:ID  -2.60012e-05:0.000103804:0.09691:0.352686:rs201754587
1   86028   rs114608975 T   C   .   PASS    AF=0.103486 ES:SE:LP:AF:ID  -0.000196954:0.000176581:0.585027:0.103486:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.076103 ES:SE:LP:AF:ID  0.000156395:0.000181837:0.408935:0.076103:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.109614 ES:SE:LP:AF:ID  -3.24606e-05:0.000159951:0.0757207:0.109614:rs115209712
1   87409   rs139490478 C   T   .   PASS    AF=0.076699 ES:SE:LP:AF:ID  0.000156631:0.000181247:0.408935:0.076699:rs139490478
1   88169   rs940550    C   T   .   PASS    AF=0.208367 ES:SE:LP:AF:ID  6.96011e-05:0.00011802:0.251812:0.208367:rs940550
1   88172   rs940551    G   A   .   PASS    AF=0.071702 ES:SE:LP:AF:ID  -0.000120683:0.00018345:0.29243:0.071702:rs940551