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/497a488a-1423-4454-9d04-0e3d3f5faad3/call-ldsc/inputs/-261043450/ieu-b-4958.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4958/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 15:23:06 2022
Reading summary statistics from /data/cromwell-executions/qc/497a488a-1423-4454-9d04-0e3d3f5faad3/call-ldsc/inputs/-261043450/ieu-b-4958.vcf.gz ...
Read summary statistics for 8170335 SNPs.
Dropped 144457 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, 1168060 SNPs remain.
After merging with regression SNP LD, 1168060 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0006 (0.0012)
Lambda GC: 0.9978
Mean Chi^2: 0.9959
Intercept: 0.9911 (0.0068)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Fri Mar  4 15:24:43 2022
Total time elapsed: 1.0m:37.23s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9284,
    "inflation_factor": 1,
    "mean_EFFECT": 3.3578e-08,
    "n": "-Inf",
    "n_snps": 8171258,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1023939,
    "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": 1022191,
    "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": 1168060,
    "ldsc_nsnp_merge_regression_ld": 1168060,
    "ldsc_observed_scale_h2_beta": 0.0006,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 0.9911,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 0.9978,
    "ldsc_mean_chisq": 0.9959,
    "ldsc_ratio": 2.1707
}

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 TRUE
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 603 0.9999262 3 58 0 8145340 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 13592 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 55795 0 NA NA NA NA NA NA NA NA NA NA
logical N 8171258 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 8.862815e+00 5.955482e+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 7.837877e+07 5.643540e+07 302.0000000 3.194123e+07 6.876789e+07 1.143354e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 0.000000e+00 1.339000e-04 -0.0012025 -7.750000e-05 -4.000000e-07 7.650000e-05 1.307900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.256000e-04 4.780000e-05 0.0000670 8.740000e-05 1.062000e-04 1.515000e-04 4.349000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.007911e-01 2.880465e-01 0.0000001 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 5.007917e-01 2.880203e-01 0.0000001 2.514753e-01 5.009553e-01 7.497326e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.469356e-01 2.820627e-01 0.0270570 9.718900e-02 2.625740e-01 5.556580e-01 9.729430e-01 ▇▃▂▂▂
numeric AF_reference 1022191 0.8749041 NA NA NA NA NA NA NA 3.041162e-01 2.496757e-01 0.0000000 9.704470e-02 2.320290e-01 4.672520e-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 -0.0002773 0.0001218 0.0230001 0.0227830 0.601309 NA NA
1 10352 rs1557426776 TA T -0.0000683 0.0001254 0.5900000 0.5859308 0.606999 NA NA
1 11008 rs575272151 C G -0.0000505 0.0002085 0.8100000 0.8087037 0.086192 0.0880591 NA
1 11012 rs544419019 C G -0.0000505 0.0002085 0.8100000 0.8087037 0.086192 0.0880591 NA
1 13110 rs540538026 G A -0.0002476 0.0002770 0.3700002 0.3714965 0.058733 0.0267572 NA
1 13116 rs62635286 T G 0.0000247 0.0001640 0.8800001 0.8805388 0.189422 0.0970447 NA
1 13118 rs200579949 A G 0.0000247 0.0001640 0.8800001 0.8805388 0.189422 0.0970447 NA
1 13273 rs531730856 G C 0.0001679 0.0001923 0.3800004 0.3825195 0.133939 0.0950479 NA
1 14464 rs546169444 A T 0.0000624 0.0001746 0.7199992 0.7210149 0.157056 0.0958466 NA
1 14599 rs531646671 T A 0.0000051 0.0001592 0.9699999 0.9743142 0.191573 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0000020 7.80e-05 0.9800000 0.9800133 0.751496 0.643179 NA
23 154901964 rs697726 G A 0.0001125 8.23e-05 0.1700000 0.1714245 0.347500 0.117616 NA
23 154902105 rs696316 G T -0.0000018 7.80e-05 0.9800000 0.9819692 0.751449 0.636026 NA
23 154902889 rs697725 A T -0.0000004 7.79e-05 1.0000000 0.9960874 0.751121 0.584106 NA
23 154903118 rs479770 G A -0.0000021 7.80e-05 0.9800000 0.9785550 0.751539 0.643444 NA
23 154903224 rs480725 A T -0.0000021 7.80e-05 0.9800000 0.9784329 0.751542 0.643444 NA
23 154903937 rs674707 G A -0.0000021 7.80e-05 0.9800000 0.9780028 0.751552 0.643444 NA
23 154909055 rs473529 C G 0.0000077 7.34e-05 0.9199999 0.9168191 0.305117 0.463046 NA
23 154918266 rs642043 C T -0.0000045 7.37e-05 0.9500000 0.9517145 0.302978 0.478675 NA
23 154927581 rs644138 G A -0.0000040 7.37e-05 0.9599999 0.9563968 0.302850 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601309 ES:SE:LP:AF:ID  -0.000277261:0.000121763:1.63827:0.601309:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606999 ES:SE:LP:AF:ID  -6.83145e-05:0.000125407:0.229148:0.606999:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086192 ES:SE:LP:AF:ID  -5.04766e-05:0.000208496:0.091515:0.086192:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086192 ES:SE:LP:AF:ID  -5.04766e-05:0.000208496:0.091515:0.086192:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058733 ES:SE:LP:AF:ID  -0.000247553:0.000277006:0.431798:0.058733:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189422 ES:SE:LP:AF:ID  2.46528e-05:0.000164039:0.0555173:0.189422:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189422 ES:SE:LP:AF:ID  2.46528e-05:0.000164039:0.0555173:0.189422:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133939 ES:SE:LP:AF:ID  0.000167905:0.000192273:0.420216:0.133939:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157056 ES:SE:LP:AF:ID  6.23605e-05:0.000174629:0.142668:0.157056:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191573 ES:SE:LP:AF:ID  5.12598e-06:0.000159202:0.0132283:0.191573:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191573 ES:SE:LP:AF:ID  5.12598e-06:0.000159202:0.0132283:0.191573:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.474001 ES:SE:LP:AF:ID  -1.04438e-05:0.000123488:0.0315171:0.474001:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045009 ES:SE:LP:AF:ID  5.77773e-05:0.000304119:0.0705811:0.045009:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741419 ES:SE:LP:AF:ID  4.4731e-06:0.000142811:0.00877392:0.741419:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275232 ES:SE:LP:AF:ID  0.000196686:0.000146432:0.744727:0.275232:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.58105  ES:SE:LP:AF:ID  0.000220854:0.000120746:1.17393:0.58105:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956506 ES:SE:LP:AF:ID  0.00056182:0.000343236:1:0.956506:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910281 ES:SE:LP:AF:ID  1.14279e-05:0.000228001:0.0177288:0.910281:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.06268  ES:SE:LP:AF:ID  0.000458514:0.000260086:1.10791:0.06268:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623625 ES:SE:LP:AF:ID  -0.000140262:0.000144871:0.481486:0.623625:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092963 ES:SE:LP:AF:ID  -0.000210261:0.00022284:0.455932:0.092963:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213488 ES:SE:LP:AF:ID  -6.09846e-05:0.000154868:0.161151:0.213488:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154531 ES:SE:LP:AF:ID  1.44927e-05:0.000174001:0.0315171:0.154531:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400417 ES:SE:LP:AF:ID  -5.73704e-05:0.000143508:0.161151:0.400417:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414826 ES:SE:LP:AF:ID  -0.000115493:0.000113446:0.508638:0.414826:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417225 ES:SE:LP:AF:ID  -1.66061e-05:0.000131017:0.0457575:0.417225:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253873 ES:SE:LP:AF:ID  8.11381e-05:0.000147389:0.236572:0.253873:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090038 ES:SE:LP:AF:ID  8.5737e-05:0.000224463:0.154902:0.090038:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088866 ES:SE:LP:AF:ID  -0.000178147:0.000225331:0.366532:0.088866:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.08102  ES:SE:LP:AF:ID  -9.84233e-05:0.000233736:0.173925:0.08102:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438476 ES:SE:LP:AF:ID  -7.83353e-05:0.000124556:0.275724:0.438476:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382109 ES:SE:LP:AF:ID  -2.52637e-05:0.000133898:0.0705811:0.382109:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158839 ES:SE:LP:AF:ID  -4.93172e-05:0.000170461:0.113509:0.158839:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683982 ES:SE:LP:AF:ID  8.61528e-05:0.000132711:0.283997:0.683982:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079628 ES:SE:LP:AF:ID  -9.65271e-05:0.000236575:0.167491:0.079628:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070775 ES:SE:LP:AF:ID  0.000626692:0.000239871:2.04576:0.070775:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032902 ES:SE:LP:AF:ID  0.000156138:0.000363089:0.173925:0.032902:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.07392  ES:SE:LP:AF:ID  0.000630347:0.000235941:2.12494:0.07392:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751162 ES:SE:LP:AF:ID  0.000111145:0.00015032:0.337242:0.751162:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034041 ES:SE:LP:AF:ID  -0.000269717:0.000345293:0.366532:0.034041:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034041 ES:SE:LP:AF:ID  -0.000269717:0.000345293:0.366532:0.034041:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077195 ES:SE:LP:AF:ID  -0.000231771:0.000241093:0.468521:0.077195:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077457 ES:SE:LP:AF:ID  0.000307064:0.000232796:0.721246:0.077457:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076998 ES:SE:LP:AF:ID  -0.000230937:0.000241156:0.468521:0.076998:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076998 ES:SE:LP:AF:ID  -0.000230937:0.000241156:0.468521:0.076998:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041523 ES:SE:LP:AF:ID  -2.76767e-05:0.000336051:0.0315171:0.041523:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.06098  ES:SE:LP:AF:ID  0.000574667:0.000255562:1.60206:0.06098:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075418 ES:SE:LP:AF:ID  0.000348777:0.000235733:0.853872:0.075418:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075445 ES:SE:LP:AF:ID  0.000348218:0.000235685:0.853872:0.075445:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352669 ES:SE:LP:AF:ID  -0.000212761:0.000134955:0.958607:0.352669:rs201754587