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/65574033-a9b5-4f4e-abec-8b62270b6a3a/call-ldsc/inputs/-261043451/ieu-b-4957.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4957/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 15:51:41 2022
Reading summary statistics from /data/cromwell-executions/qc/65574033-a9b5-4f4e-abec-8b62270b6a3a/call-ldsc/inputs/-261043451/ieu-b-4957.vcf.gz ...
Read summary statistics for 8614806 SNPs.
Dropped 152717 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, 1185388 SNPs remain.
After merging with regression SNP LD, 1185388 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0029 (0.0012)
Lambda GC: 1.0114
Mean Chi^2: 1.0155
Intercept: 0.9939 (0.0067)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Fri Mar  4 15:53:35 2022
Total time elapsed: 1.0m:53.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9325,
    "inflation_factor": 1,
    "mean_EFFECT": -1.7058e-07,
    "n": "-Inf",
    "n_snps": 8615746,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1063764,
    "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": 1064611,
    "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": 1185388,
    "ldsc_nsnp_merge_regression_ld": 1185388,
    "ldsc_observed_scale_h2_beta": 0.0029,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 0.9939,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0114,
    "ldsc_mean_chisq": 1.0155,
    "ldsc_ratio": -0.3935
}

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 612 0.9999290 3 58 0 8587792 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 14102 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 58196 0 NA NA NA NA NA NA NA NA NA NA
logical N 8615746 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 8.851161e+00 5.948992e+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 7.840593e+07 5.641495e+07 302.0000000 3.200312e+07 6.881737e+07 1.143366e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.000000e-07 1.662000e-04 -0.0016864 -9.250000e-05 -9.000000e-07 9.060000e-05 1.936100e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.520000e-04 6.510000e-05 0.0000765 1.005000e-04 1.249000e-04 1.866000e-04 7.869000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.984114e-01 2.889948e-01 0.0000002 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 4.984094e-01 2.889700e-01 0.0000002 2.478995e-01 4.974689e-01 7.488493e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.358819e-01 2.871006e-01 0.0207990 8.252930e-02 2.437890e-01 5.450010e-01 9.792010e-01 ▇▃▂▂▂
numeric AF_reference 1064611 0.8764343 NA NA NA NA NA NA NA 2.917119e-01 2.518594e-01 0.0000000 8.306710e-02 2.150560e-01 4.526760e-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 -0.0000015 0.0001389 0.9900000 0.9911584 0.601340 NA NA
1 10352 rs1557426776 TA T -0.0002642 0.0001431 0.0649995 0.0648186 0.606978 NA NA
1 11008 rs575272151 C G -0.0000985 0.0002379 0.6800001 0.6789227 0.086190 0.0880591 NA
1 11012 rs544419019 C G -0.0000985 0.0002379 0.6800001 0.6789227 0.086190 0.0880591 NA
1 13110 rs540538026 G A -0.0007419 0.0003161 0.0189998 0.0189015 0.058722 0.0267572 NA
1 13116 rs62635286 T G -0.0002193 0.0001872 0.2399999 0.2414297 0.189406 0.0970447 NA
1 13118 rs200579949 A G -0.0002193 0.0001872 0.2399999 0.2414297 0.189406 0.0970447 NA
1 13273 rs531730856 G C 0.0000405 0.0002194 0.8499999 0.8533967 0.133934 0.0950479 NA
1 14464 rs546169444 A T 0.0001635 0.0001992 0.4100001 0.4117910 0.157062 0.0958466 NA
1 14599 rs531646671 T A -0.0001140 0.0001816 0.5300002 0.5303915 0.191565 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0001262 8.89e-05 0.1600000 0.1558603 0.751462 0.643179 NA
23 154901964 rs697726 G A -0.0000932 9.39e-05 0.3200000 0.3206585 0.347450 0.117616 NA
23 154902105 rs696316 G T -0.0001260 8.89e-05 0.1600000 0.1565556 0.751415 0.636026 NA
23 154902889 rs697725 A T -0.0001241 8.89e-05 0.1600000 0.1626465 0.751087 0.584106 NA
23 154903118 rs479770 G A -0.0001265 8.89e-05 0.1499999 0.1549482 0.751505 0.643444 NA
23 154903224 rs480725 A T -0.0001265 8.89e-05 0.1499999 0.1548997 0.751508 0.643444 NA
23 154903937 rs674707 G A -0.0001266 8.89e-05 0.1499999 0.1547157 0.751517 0.643444 NA
23 154909055 rs473529 C G 0.0000438 8.38e-05 0.5999997 0.6011112 0.305128 0.463046 NA
23 154918266 rs642043 C T 0.0000490 8.40e-05 0.5600000 0.5601214 0.302994 0.478675 NA
23 154927581 rs644138 G A 0.0000496 8.40e-05 0.5500004 0.5549746 0.302866 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.60134  ES:SE:LP:AF:ID  -1.53939e-06:0.000138915:0.00436481:0.60134:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606978 ES:SE:LP:AF:ID  -0.000264189:0.000143075:1.18709:0.606978:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.08619  ES:SE:LP:AF:ID  -9.84653e-05:0.000237877:0.167491:0.08619:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.08619  ES:SE:LP:AF:ID  -9.84653e-05:0.000237877:0.167491:0.08619:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058722 ES:SE:LP:AF:ID  -0.000741917:0.00031605:1.72125:0.058722:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189406 ES:SE:LP:AF:ID  -0.000219256:0.000187171:0.619789:0.189406:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189406 ES:SE:LP:AF:ID  -0.000219256:0.000187171:0.619789:0.189406:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133934 ES:SE:LP:AF:ID  4.05408e-05:0.000219393:0.0705811:0.133934:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157062 ES:SE:LP:AF:ID  0.000163509:0.00019922:0.387216:0.157062:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191565 ES:SE:LP:AF:ID  -0.000113965:0.000181644:0.275724:0.191565:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191565 ES:SE:LP:AF:ID  -0.000113965:0.000181644:0.275724:0.191565:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474027 ES:SE:LP:AF:ID  0.000228361:0.000140894:0.958607:0.474027:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.04501  ES:SE:LP:AF:ID  0.000131414:0.000346963:0.154902:0.04501:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741397 ES:SE:LP:AF:ID  -0.000262483:0.000162942:0.958607:0.741397:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275237 ES:SE:LP:AF:ID  0.000263045:0.000167059:0.920819:0.275237:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581015 ES:SE:LP:AF:ID  -7.84198e-05:0.000137766:0.244125:0.581015:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956493 ES:SE:LP:AF:ID  -0.000367638:0.000391493:0.455932:0.956493:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910267 ES:SE:LP:AF:ID  -0.000449486:0.000260075:1.07572:0.910267:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062656 ES:SE:LP:AF:ID  -0.000512886:0.000296833:1.07572:0.062656:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623636 ES:SE:LP:AF:ID  -2.39813e-06:0.000165281:0.00436481:0.623636:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092954 ES:SE:LP:AF:ID  -0.00046492:0.000254248:1.17393:0.092954:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213517 ES:SE:LP:AF:ID  0.000359602:0.000176673:1.37675:0.213517:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154541 ES:SE:LP:AF:ID  0.000206749:0.000198516:0.522879:0.154541:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400433 ES:SE:LP:AF:ID  0.0001434:0.00016373:0.420216:0.400433:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414852 ES:SE:LP:AF:ID  8.11009e-05:0.000129436:0.275724:0.414852:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417226 ES:SE:LP:AF:ID  -1.1509e-06:0.000149473:0.00436481:0.417226:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253841 ES:SE:LP:AF:ID  -0.000343312:0.000168174:1.38722:0.253841:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.09002  ES:SE:LP:AF:ID  -0.000453288:0.000256113:1.11351:0.09002:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088856 ES:SE:LP:AF:ID  -0.000486227:0.000257092:1.22915:0.088856:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081006 ES:SE:LP:AF:ID  -0.000537376:0.000266687:1.35655:0.081006:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.43851  ES:SE:LP:AF:ID  0.000230632:0.000142108:1:0.43851:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382083 ES:SE:LP:AF:ID  -0.000309582:0.000152771:1.36653:0.382083:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158832 ES:SE:LP:AF:ID  -0.000181304:0.000194493:0.455932:0.158832:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683996 ES:SE:LP:AF:ID  0.000237639:0.000151419:0.920819:0.683996:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079614 ES:SE:LP:AF:ID  -0.000548512:0.000269922:1.37675:0.079614:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070764 ES:SE:LP:AF:ID  0.000232039:0.000273712:0.39794:0.070764:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032896 ES:SE:LP:AF:ID  -0.000314928:0.000414304:0.346787:0.032896:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073906 ES:SE:LP:AF:ID  0.000143367:0.000269241:0.229148:0.073906:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751185 ES:SE:LP:AF:ID  0.000415516:0.000171502:1.82391:0.751185:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034041 ES:SE:LP:AF:ID  -0.0003056:0.000393979:0.356547:0.034041:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034041 ES:SE:LP:AF:ID  -0.0003056:0.000393979:0.356547:0.034041:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077186 ES:SE:LP:AF:ID  -0.000540794:0.000275067:1.3098:0.077186:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077438 ES:SE:LP:AF:ID  -0.000313738:0.00026565:0.619789:0.077438:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.07699  ES:SE:LP:AF:ID  -0.000539215:0.00027514:1.30103:0.07699:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.07699  ES:SE:LP:AF:ID  -0.000539215:0.00027514:1.30103:0.07699:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041533 ES:SE:LP:AF:ID  0.000655533:0.000383344:1.06048:0.041533:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060968 ES:SE:LP:AF:ID  9.28022e-05:0.00029163:0.124939:0.060968:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075399 ES:SE:LP:AF:ID  -0.000305412:0.00026901:0.585027:0.075399:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075426 ES:SE:LP:AF:ID  -0.00030553:0.000268955:0.585027:0.075426:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352689 ES:SE:LP:AF:ID  4.3983e-06:0.000153967:0.00877392:0.352689:rs201754587