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/f3b5d1bb-c94f-4310-973f-39459303bf84/call-ldsc/inputs/-261043365/ieu-b-4980.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4980/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sat Apr 23 02:24:00 2022
Reading summary statistics from /data/cromwell-executions/qc/f3b5d1bb-c94f-4310-973f-39459303bf84/call-ldsc/inputs/-261043365/ieu-b-4980.vcf.gz ...
Read summary statistics for 12242539 SNPs.
Dropped 231421 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, 1220578 SNPs remain.
After merging with regression SNP LD, 1220578 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0026 (0.001)
Lambda GC: 1.0354
Mean Chi^2: 1.0373
Intercept: 1.0124 (0.0064)
Ratio: 0.3313 (0.1716)
Analysis finished at Sat Apr 23 02:25:59 2022
Total time elapsed: 1.0m:59.27s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.95,
    "inflation_factor": 1.0269,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 12243539,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1279901,
    "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": 404183,
    "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": 1220578,
    "ldsc_nsnp_merge_regression_ld": 1220578,
    "ldsc_observed_scale_h2_beta": 0.0026,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0124,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0354,
    "ldsc_mean_chisq": 1.0373,
    "ldsc_ratio": 0.3324
}

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 566 0.9999538 3 58 0 12193988 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 101 0 56052 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 34526 0 NA NA NA NA NA NA NA NA NA NA
logical N 12243539 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 8.635974e+00 5.758636e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.869395e+07 5.629933e+07 302.0000000 3.250309e+07 6.911924e+07 1.143453e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.460000e-05 8.931940e-02 -35.5853000 -1.923390e-02 -1.181000e-04 1.891750e-02 3.350980e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.772760e-02 8.445900e-02 0.0131771 1.599440e-02 2.586070e-02 5.970110e-02 2.138550e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.955961e-01 2.900080e-01 0.0000001 2.432372e-01 4.942902e-01 7.467909e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.955961e-01 2.900080e-01 0.0000001 2.432370e-01 4.942898e-01 7.467916e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.127948e-01 2.602010e-01 0.0000054 1.457910e-02 8.849500e-02 3.382500e-01 9.999950e-01 ▇▂▁▁▁
numeric AF_reference 404183 0.9669881 NA NA NA NA NA NA NA 2.160784e-01 2.512172e-01 0.0000000 1.357830e-02 1.106230e-01 3.426520e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10177 rs367896724 A AC 0.0331249 0.0203867 0.1041984 0.1041990 0.3989060 0.4253190 NA
1 10352 rs555500075 T TA 0.0225569 0.0209699 0.2820694 0.2820704 0.3932360 0.4375000 NA
1 11008 rs575272151 C G -0.0268244 0.0348188 0.4410624 0.4410627 0.0862242 0.0880591 NA
1 11012 rs544419019 C G -0.0268244 0.0348188 0.4410624 0.4410627 0.0862242 0.0880591 NA
1 13110 rs540538026 G A 0.0223253 0.0464379 0.6306901 0.6306899 0.0586843 0.0267572 NA
1 13116 rs62635286 T G -0.0127556 0.0274342 0.6419645 0.6419655 0.1891810 0.0970447 NA
1 13118 rs200579949 A G -0.0127556 0.0274342 0.6419645 0.6419655 0.1891810 0.0970447 NA
1 13273 rs531730856 G C 0.0508471 0.0321278 0.1135011 0.1135010 0.1341340 0.0950479 NA
1 14464 rs546169444 A T -0.0683083 0.0292482 0.0195191 0.0195189 0.1568980 0.0958466 NA
1 14599 rs531646671 T A 0.0264531 0.0266223 0.3203967 0.3203960 0.1915570 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51233182 rs4040317 G A 0.0283359 0.0166715 0.0891949 0.0891947 0.3200860 0.2633790 NA
22 51233300 rs9616839 C T 0.0263500 0.0166345 0.1131803 0.1131807 0.3343140 0.3146960 NA
22 51233312 rs62240043 A G 0.0199090 0.0175327 0.2561492 0.2561511 0.2729950 0.2134580 NA
22 51233347 rs62240044 T C 0.0199090 0.0175327 0.2561492 0.2561511 0.2729950 0.2134580 NA
22 51234799 rs191117135 G A -0.1456200 0.0620959 0.0190226 0.0190229 0.0156550 0.0059904 NA
22 51235959 rs200189535 T C 0.0200033 0.0204052 0.3269362 0.3269361 0.1953500 0.1996810 NA
22 51235979 rs62240045 G A -0.0328734 0.0226670 0.1469823 0.1469816 0.2637980 0.2400160 NA
22 51236013 rs200507571 A AT -0.0035221 0.0175541 0.8409762 0.8409763 0.2513400 0.1487620 NA
22 51237063 rs3896457 T C 0.0138887 0.0161211 0.3889493 0.3889500 0.2979820 0.2050720 NA
22 51237712 rs370652263 G A -0.0864833 0.0322290 0.0072877 0.0072878 0.0553522 0.0690895 NA

bcf preview

1   10177   rs1264289758    A   AC  .   PASS    AF=0.398906 ES:SE:LP:AF:ID  0.0331249:0.0203867:0.982139:0.398906:rs1264289758
1   10352   rs1557426776    T   TA  .   PASS    AF=0.393236 ES:SE:LP:AF:ID  0.0225569:0.0209699:0.549644:0.393236:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.0862242    ES:SE:LP:AF:ID  -0.0268244:0.0348188:0.3555:0.0862242:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.0862242    ES:SE:LP:AF:ID  -0.0268244:0.0348188:0.3555:0.0862242:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.0586843    ES:SE:LP:AF:ID  0.0223253:0.0464379:0.200184:0.0586843:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  -0.0127556:0.0274342:0.192489:0.189181:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189181 ES:SE:LP:AF:ID  -0.0127556:0.0274342:0.192489:0.189181:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134134 ES:SE:LP:AF:ID  0.0508471:0.0321278:0.945:0.134134:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156898 ES:SE:LP:AF:ID  -0.0683083:0.0292482:1.70954:0.156898:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191557 ES:SE:LP:AF:ID  0.0264531:0.0266223:0.494312:0.191557:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191557 ES:SE:LP:AF:ID  0.0264531:0.0266223:0.494312:0.191557:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473819 ES:SE:LP:AF:ID  0.00419188:0.0206598:0.0761278:0.473819:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.0450802    ES:SE:LP:AF:ID  -0.046046:0.0507537:0.438568:0.0450802:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741355 ES:SE:LP:AF:ID  -0.00344106:0.0238912:0.052823:0.741355:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275124 ES:SE:LP:AF:ID  -0.00403277:0.0244803:0.0609043:0.275124:rs1316988498
1   15903   rs557514207 G   GC  .   PASS    AF=0.41884  ES:SE:LP:AF:ID  -0.019853:0.0202128:0.486781:0.41884:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956571 ES:SE:LP:AF:ID  0.0764548:0.0575723:0.734745:0.956571:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910221 ES:SE:LP:AF:ID  0.00274484:0.0381649:0.0256426:0.910221:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.0627121    ES:SE:LP:AF:ID  0.0288105:0.0434476:0.294769:0.0627121:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623768 ES:SE:LP:AF:ID  0.00969358:0.0242282:0.161726:0.623768:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.0929554    ES:SE:LP:AF:ID  -0.0424186:0.0373114:0.59246:0.0929554:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.21326  ES:SE:LP:AF:ID  -0.0389461:0.0259303:0.875791:0.21326:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154391 ES:SE:LP:AF:ID  -0.0155354:0.0291067:0.226564:0.154391:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400396 ES:SE:LP:AF:ID  0.0244268:0.0240163:0.509886:0.400396:rs2462492
1   54712   rs573184866 T   TTTTC   .   PASS    AF=0.585268 ES:SE:LP:AF:ID  0.0229796:0.0189922:0.64532:0.585268:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417371 ES:SE:LP:AF:ID  0.0028675:0.021926:0.0477168:0.417371:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253777 ES:SE:LP:AF:ID  -0.0290293:0.0246856:0.620496:0.253777:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.0899979    ES:SE:LP:AF:ID  -0.0496858:0.0376642:0.727905:0.0899979:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.0887883    ES:SE:LP:AF:ID  -0.0670067:0.0377779:1.11854:0.0887883:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.0809837    ES:SE:LP:AF:ID  -0.0591984:0.0392038:0.8826:0.0809837:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438273 ES:SE:LP:AF:ID  -0.0108752:0.0208388:0.220578:0.438273:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382186 ES:SE:LP:AF:ID  -0.0137621:0.0224189:0.268163:0.382186:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158756 ES:SE:LP:AF:ID  -0.05931:0.028526:1.42477:0.158756:rs80011619
1   63735   rs61158452  CCTA    C   .   PASS    AF=0.315972 ES:SE:LP:AF:ID  -0.0133671:0.0222149:0.261725:0.315972:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.0795793    ES:SE:LP:AF:ID  -0.0570865:0.0396805:0.823191:0.0795793:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.0707801    ES:SE:LP:AF:ID  -0.00195157:0.0400868:0.0171991:0.0707801:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.0329199    ES:SE:LP:AF:ID  -0.085965:0.0607718:0.80355:0.0329199:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.0738738    ES:SE:LP:AF:ID  0.0262072:0.0394757:0.295193:0.0738738:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751218 ES:SE:LP:AF:ID  0.035788:0.0251823:0.808908:0.751218:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.0340921    ES:SE:LP:AF:ID  -0.0940461:0.0574933:0.991882:0.0340921:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.0340921    ES:SE:LP:AF:ID  -0.0940461:0.0574933:0.991882:0.0340921:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.0771356    ES:SE:LP:AF:ID  -0.0676446:0.0403427:1.02877:0.0771356:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.0775037    ES:SE:LP:AF:ID  0.0194801:0.0388913:0.210101:0.0775037:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.0769408    ES:SE:LP:AF:ID  -0.0689846:0.0403538:1.05869:0.0769408:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.0769408    ES:SE:LP:AF:ID  -0.0689846:0.0403538:1.05869:0.0769408:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.0414632    ES:SE:LP:AF:ID  0.138222:0.0562367:1.8546:0.0414632:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.0609432    ES:SE:LP:AF:ID  -0.0121099:0.0427227:0.109674:0.0609432:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.0754482    ES:SE:LP:AF:ID  0.0147246:0.0393946:0.149615:0.0754482:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.0754758    ES:SE:LP:AF:ID  0.0136928:0.0393873:0.137805:0.0754758:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352798 ES:SE:LP:AF:ID  0.0417703:0.0225563:1.19348:0.352798:rs201754587