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/6998e2d8-cec2-4406-83d9-b6cc317ac4bc/call-ldsc/inputs/-261044383/ieu-b-4865.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4865/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Jan  7 23:35:51 2022
Reading summary statistics from /data/cromwell-executions/qc/6998e2d8-cec2-4406-83d9-b6cc317ac4bc/call-ldsc/inputs/-261044383/ieu-b-4865.vcf.gz ...
Read summary statistics for 0 SNPs.
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.
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
    sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
  File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
    raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.

Analysis finished at Fri Jan  7 23:37:13 2022
Total time elapsed: 1.0m:22.24s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 12321875,
    "n_clumped_hits": 167,
    "n_p_sig": 33317,
    "n_mono": 0,
    "n_ns": 1293897,
    "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": 1423040,
    "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": 0,
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}
 

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq NA
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio NA
ldsc_intercept_beta NA
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 675 0.9999452 3 58 0 12276232 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 17566 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 71704 0 NA NA NA NA NA NA NA NA NA NA
logical N 12321875 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 8.757492e+00 5.885387e+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 7.871202e+07 5.622121e+07 302.0000000 3.252510e+07 6.928045e+07 1.144492e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.100000e-05 1.508700e-02 -0.7433500 -4.905800e-03 -3.000000e-06 4.924300e-03 5.353450e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.027600e-02 9.872700e-03 0.0021926 3.598400e-03 5.778700e-03 1.333530e-02 1.585250e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.584619e-01 3.009297e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.584635e-01 3.009065e-01 0.0000000 1.873801e-01 4.447108e-01 7.191950e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594006e-01 3.020433e-01 0.0008570 1.660000e-02 1.145470e-01 4.378900e-01 9.992580e-01 ▇▂▁▁▁
numeric AF_reference 1423040 0.8845111 NA NA NA NA NA NA NA 2.132160e-01 2.513550e-01 0.0000000 1.218050e-02 1.056310e-01 3.376600e-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 0.0063997 0.0046216 0.1700000 0.1661370 0.600355 NA NA
1 10352 rs1557426776 TA T 0.0022789 0.0047644 0.6300007 0.6324237 0.607112 NA NA
1 11008 rs575272151 C G -0.0073908 0.0078778 0.3500000 0.3481508 0.086661 0.0880591 NA
1 11012 rs544419019 C G -0.0073908 0.0078778 0.3500000 0.3481508 0.086661 0.0880591 NA
1 13110 rs540538026 G A 0.0045748 0.0105411 0.6600001 0.6642938 0.058702 0.0267572 NA
1 13116 rs62635286 T G 0.0045746 0.0062331 0.4600002 0.4630013 0.189282 0.0970447 NA
1 13118 rs200579949 A G 0.0045746 0.0062331 0.4600002 0.4630013 0.189282 0.0970447 NA
1 13273 rs531730856 G C -0.0069174 0.0073107 0.3400001 0.3440448 0.134068 0.0950479 NA
1 14464 rs546169444 A T 0.0014804 0.0066503 0.8200001 0.8238442 0.156841 0.0958466 NA
1 14599 rs531646671 T A 0.0040167 0.0060399 0.5099998 0.5060399 0.192027 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0059530 0.0025407 0.0189998 0.0191257 0.752581 0.643179 NA
23 154901964 rs697726 G A -0.0069734 0.0026748 0.0091000 0.0091324 0.348965 0.117616 NA
23 154902105 rs696316 G T -0.0059716 0.0025406 0.0189998 0.0187481 0.752559 0.636026 NA
23 154902889 rs697725 A T -0.0060193 0.0025397 0.0179999 0.0177838 0.752263 0.584106 NA
23 154903118 rs479770 G A -0.0059208 0.0025408 0.0200000 0.0197927 0.752611 0.643444 NA
23 154903224 rs480725 A T -0.0059214 0.0025408 0.0200000 0.0197798 0.752613 0.643444 NA
23 154903937 rs674707 G A -0.0059182 0.0025409 0.0200000 0.0198488 0.752619 0.643444 NA
23 154909055 rs473529 C G 0.0071674 0.0023911 0.0027000 0.0027214 0.303684 0.463046 NA
23 154918266 rs642043 C T 0.0070964 0.0023986 0.0031000 0.0030903 0.301596 0.478675 NA
23 154927581 rs644138 G A 0.0070444 0.0023989 0.0033000 0.0033200 0.301497 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.600355 ES:SE:LP:AF:ID  0.00639968:0.00462163:0.769551:0.600355:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607112 ES:SE:LP:AF:ID  0.00227889:0.00476438:0.200659:0.607112:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086661 ES:SE:LP:AF:ID  -0.00739083:0.00787782:0.455932:0.086661:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086661 ES:SE:LP:AF:ID  -0.00739083:0.00787782:0.455932:0.086661:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058702 ES:SE:LP:AF:ID  0.00457476:0.0105411:0.180456:0.058702:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189282 ES:SE:LP:AF:ID  0.00457458:0.00623313:0.337242:0.189282:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189282 ES:SE:LP:AF:ID  0.00457458:0.00623313:0.337242:0.189282:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134068 ES:SE:LP:AF:ID  -0.00691741:0.0073107:0.468521:0.134068:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156841 ES:SE:LP:AF:ID  0.00148037:0.00665026:0.0861861:0.156841:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.192027 ES:SE:LP:AF:ID  0.00401666:0.00603994:0.29243:0.192027:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.192027 ES:SE:LP:AF:ID  0.00401666:0.00603994:0.29243:0.192027:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473821 ES:SE:LP:AF:ID  -0.00338022:0.00469218:0.327902:0.473821:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045089 ES:SE:LP:AF:ID  -0.0103192:0.0115275:0.431798:0.045089:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741652 ES:SE:LP:AF:ID  -0.00653485:0.00542522:0.638272:0.741652:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275145 ES:SE:LP:AF:ID  0.00214203:0.00556169:0.154902:0.275145:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581143 ES:SE:LP:AF:ID  2.87767e-06:0.00458539:-0:0.581143:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956528 ES:SE:LP:AF:ID  -0.0169907:0.013065:0.721246:0.956528:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.91013  ES:SE:LP:AF:ID  -0.00248714:0.00864878:0.113509:0.91013:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.06269  ES:SE:LP:AF:ID  -0.0134391:0.00986278:0.769551:0.06269:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.624053 ES:SE:LP:AF:ID  0.00410818:0.00548811:0.346787:0.624053:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092773 ES:SE:LP:AF:ID  0.00689887:0.00848232:0.376751:0.092773:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213373 ES:SE:LP:AF:ID  0.00447778:0.0058858:0.346787:0.213373:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154553 ES:SE:LP:AF:ID  0.00440993:0.00660955:0.30103:0.154553:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.399661 ES:SE:LP:AF:ID  -0.00585884:0.00545195:0.552842:0.399661:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414714 ES:SE:LP:AF:ID  0.00450166:0.00430455:0.522879:0.414714:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417651 ES:SE:LP:AF:ID  -0.00856886:0.00497581:1.07058:0.417651:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.25373  ES:SE:LP:AF:ID  -0.00651747:0.00559275:0.619789:0.25373:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089731 ES:SE:LP:AF:ID  0.00469783:0.00854861:0.236572:0.089731:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088577 ES:SE:LP:AF:ID  0.00345765:0.0085767:0.161151:0.088577:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080751 ES:SE:LP:AF:ID  0.0061356:0.00890032:0.309804:0.080751:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438243 ES:SE:LP:AF:ID  0.00571336:0.00472416:0.638272:0.438243:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.381723 ES:SE:LP:AF:ID  -0.00712844:0.00508542:0.79588:0.381723:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158408 ES:SE:LP:AF:ID  -0.00322296:0.00647306:0.207608:0.158408:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.68357  ES:SE:LP:AF:ID  -0.00289003:0.00503904:0.244125:0.68357:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079307 ES:SE:LP:AF:ID  0.00598681:0.00901765:0.29243:0.079307:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070784 ES:SE:LP:AF:ID  0.00558536:0.00910176:0.267606:0.070784:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032817 ES:SE:LP:AF:ID  -0.0232495:0.0138295:1.03152:0.032817:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073853 ES:SE:LP:AF:ID  0.00477962:0.00896599:0.229148:0.073853:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.75163  ES:SE:LP:AF:ID  0.00704301:0.00571286:0.657577:0.75163:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034059 ES:SE:LP:AF:ID  0.0164143:0.0130617:0.677781:0.034059:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034059 ES:SE:LP:AF:ID  0.0164143:0.0130617:0.677781:0.034059:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.076975 ES:SE:LP:AF:ID  0.00114874:0.00917893:0.0457575:0.076975:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077664 ES:SE:LP:AF:ID  -0.0245689:0.00881403:2.27572:0.077664:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.07678  ES:SE:LP:AF:ID  0.0011467:0.00918058:0.0457575:0.07678:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.07678  ES:SE:LP:AF:ID  0.0011467:0.00918058:0.0457575:0.07678:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041612 ES:SE:LP:AF:ID  -0.00236736:0.0127061:0.0705811:0.041612:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060886 ES:SE:LP:AF:ID  0.00742505:0.00971118:0.356547:0.060886:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075585 ES:SE:LP:AF:ID  -0.0252656:0.00892759:2.3279:0.075585:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075601 ES:SE:LP:AF:ID  -0.0254436:0.00892687:2.35655:0.075601:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352758 ES:SE:LP:AF:ID  0.000591112:0.00511648:0.0409586:0.352758:rs201754587