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/116fc9b2-c0ab-4b2f-b651-5be12b0cc3e8/call-ldsc/inputs/-261043426/ieu-b-4961.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4961/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 16:21:42 2022
Reading summary statistics from /data/cromwell-executions/qc/116fc9b2-c0ab-4b2f-b651-5be12b0cc3e8/call-ldsc/inputs/-261043426/ieu-b-4961.vcf.gz ...
Read summary statistics for 7722219 SNPs.
Dropped 134963 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, 1146388 SNPs remain.
After merging with regression SNP LD, 1146388 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0006 (0.0013)
Lambda GC: 1.0026
Mean Chi^2: 1.0071
Intercept: 1.0022 (0.0073)
Ratio: 0.3129 (1.0394)
Analysis finished at Fri Mar  4 16:23:26 2022
Total time elapsed: 1.0m:43.94s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9235,
    "inflation_factor": 1,
    "mean_EFFECT": 3.6285e-07,
    "n": "-Inf",
    "n_snps": 7723107,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 981087,
    "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": 975701,
    "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": 1146388,
    "ldsc_nsnp_merge_regression_ld": 1146388,
    "ldsc_observed_scale_h2_beta": 0.0006,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0022,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0026,
    "ldsc_mean_chisq": 1.0071,
    "ldsc_ratio": 0.3099
}

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 576 0.9999254 3 58 0 7699739 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 12992 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 53312 0 NA NA NA NA NA NA NA NA NA NA
logical N 7723107 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 8.876948e+00 5.962900e+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 7.836238e+07 5.643968e+07 302.0000000 3.191590e+07 6.878088e+07 1.143133e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.000000e-07 1.108000e-04 -0.0012942 -6.600000e-05 -3.000000e-07 6.550000e-05 1.287800e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.045000e-04 3.510000e-05 0.0000590 7.640000e-05 9.080000e-05 1.241000e-04 3.570000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.986071e-01 2.894508e-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 4.986093e-01 2.894243e-01 0.0000002 2.474502e-01 4.983825e-01 7.490489e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.584636e-01 2.759993e-01 0.0350150 1.133430e-01 2.817120e-01 5.660030e-01 9.649850e-01 ▇▃▃▂▂
numeric AF_reference 975701 0.8736647 NA NA NA NA NA NA NA 3.170555e-01 2.467276e-01 0.0000000 1.124200e-01 2.500000e-01 4.816290e-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 -0.0001012 0.0001071 0.3400001 0.3448498 0.601329 NA NA
1 10352 rs1557426776 TA T -0.0000411 0.0001103 0.7099994 0.7096361 0.607002 NA NA
1 11008 rs575272151 C G 0.0002017 0.0001833 0.2700001 0.2712366 0.086201 0.0880591 NA
1 11012 rs544419019 C G 0.0002017 0.0001833 0.2700001 0.2712366 0.086201 0.0880591 NA
1 13110 rs540538026 G A -0.0001235 0.0002436 0.6100002 0.6122246 0.058736 0.0267572 NA
1 13116 rs62635286 T G 0.0002761 0.0001443 0.0560003 0.0556032 0.189437 0.0970447 NA
1 13118 rs200579949 A G 0.0002761 0.0001443 0.0560003 0.0556032 0.189437 0.0970447 NA
1 13273 rs531730856 G C -0.0000126 0.0001691 0.9400001 0.9403949 0.133931 0.0950479 NA
1 14464 rs546169444 A T 0.0001117 0.0001536 0.4700002 0.4669056 0.157059 0.0958466 NA
1 14599 rs531646671 T A 0.0001975 0.0001400 0.1600000 0.1582371 0.191586 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0001492 6.86e-05 0.0299999 0.0295786 0.751456 0.643179 NA
23 154901964 rs697726 G A -0.0000212 7.24e-05 0.7700005 0.7695600 0.347467 0.117616 NA
23 154902105 rs696316 G T -0.0001490 6.86e-05 0.0299999 0.0297376 0.751408 0.636026 NA
23 154902889 rs697725 A T -0.0001479 6.85e-05 0.0309999 0.0309660 0.751080 0.584106 NA
23 154903118 rs479770 G A -0.0001493 6.86e-05 0.0290001 0.0293995 0.751499 0.643444 NA
23 154903224 rs480725 A T -0.0001493 6.86e-05 0.0290001 0.0294106 0.751501 0.643444 NA
23 154903937 rs674707 G A -0.0001494 6.86e-05 0.0290001 0.0293727 0.751511 0.643444 NA
23 154909055 rs473529 C G 0.0000896 6.46e-05 0.1700000 0.1653489 0.305143 0.463046 NA
23 154918266 rs642043 C T 0.0000823 6.48e-05 0.2000000 0.2039062 0.303004 0.478675 NA
23 154927581 rs644138 G A 0.0000816 6.48e-05 0.2099999 0.2075574 0.302877 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601329 ES:SE:LP:AF:ID  -0.00010116:0.00010709:0.468521:0.601329:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607002 ES:SE:LP:AF:ID  -4.10689e-05:0.000110298:0.148742:0.607002:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086201 ES:SE:LP:AF:ID  0.000201712:0.000183338:0.568636:0.086201:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086201 ES:SE:LP:AF:ID  0.000201712:0.000183338:0.568636:0.086201:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058736 ES:SE:LP:AF:ID  -0.000123482:0.000243602:0.21467:0.058736:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189437 ES:SE:LP:AF:ID  0.000276127:0.000144257:1.25181:0.189437:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189437 ES:SE:LP:AF:ID  0.000276127:0.000144257:1.25181:0.189437:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133931 ES:SE:LP:AF:ID  -1.26448e-05:0.000169108:0.0268721:0.133931:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157059 ES:SE:LP:AF:ID  0.000111733:0.00015358:0.327902:0.157059:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191586 ES:SE:LP:AF:ID  0.000197545:0.000140001:0.79588:0.191586:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191586 ES:SE:LP:AF:ID  0.000197545:0.000140001:0.79588:0.191586:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473991 ES:SE:LP:AF:ID  -9.77315e-05:0.000108605:0.431798:0.473991:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045001 ES:SE:LP:AF:ID  -0.000409135:0.0002675:0.886057:0.045001:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741431 ES:SE:LP:AF:ID  0.000152801:0.000125604:0.657577:0.741431:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275208 ES:SE:LP:AF:ID  -0.000107722:0.000128789:0.39794:0.275208:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581015 ES:SE:LP:AF:ID  -8.46018e-05:0.000106192:0.366532:0.581015:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956502 ES:SE:LP:AF:ID  0.000298653:0.000301856:0.49485:0.956502:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910287 ES:SE:LP:AF:ID  0.000198379:0.000200514:0.49485:0.910287:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062664 ES:SE:LP:AF:ID  -0.000197398:0.000228804:0.408935:0.062664:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623648 ES:SE:LP:AF:ID  0.000145749:0.00012741:0.60206:0.623648:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092974 ES:SE:LP:AF:ID  0.000142668:0.000195945:0.327902:0.092974:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213492 ES:SE:LP:AF:ID  -1.26432e-05:0.0001362:0.0315171:0.213492:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154536 ES:SE:LP:AF:ID  0.000112645:0.000153028:0.337242:0.154536:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  -0.000187571:0.000126218:0.853872:0.400407:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414837 ES:SE:LP:AF:ID  -3.23837e-05:9.97682e-05:0.124939:0.414837:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417223 ES:SE:LP:AF:ID  -3.14094e-05:0.000115224:0.102373:0.417223:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253866 ES:SE:LP:AF:ID  -1.0218e-05:0.000129627:0.0268721:0.253866:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090033 ES:SE:LP:AF:ID  -6.46963e-05:0.000197411:0.130768:0.090033:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088871 ES:SE:LP:AF:ID  -3.14892e-05:0.000198154:0.0604807:0.088871:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.08102  ES:SE:LP:AF:ID  -0.000106996:0.000205554:0.221849:0.08102:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438502 ES:SE:LP:AF:ID  0.00015842:0.000109547:0.823909:0.438502:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.38212  ES:SE:LP:AF:ID  8.91171e-05:0.000117751:0.346787:0.38212:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158828 ES:SE:LP:AF:ID  -0.000243104:0.000149932:1:0.158828:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683986 ES:SE:LP:AF:ID  0.000126824:0.000116717:0.552842:0.683986:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079628 ES:SE:LP:AF:ID  -8.60463e-05:0.000208045:0.167491:0.079628:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070757 ES:SE:LP:AF:ID  6.33873e-07:0.000210996:-0:0.070757:rs367789441
1   69761   rs200505207 A   T   .   PASS    AF=0.0739   ES:SE:LP:AF:ID  -4.17553e-05:0.000207543:0.0757207:0.0739:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751143 ES:SE:LP:AF:ID  -0.000148895:0.000132186:0.585027:0.751143:rs200676709
1   76838   rs563953605 T   G   .   PASS    AF=0.077203 ES:SE:LP:AF:ID  5.20972e-05:0.000211997:0.091515:0.077203:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077442 ES:SE:LP:AF:ID  -0.00018125:0.000204777:0.420216:0.077442:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.077007 ES:SE:LP:AF:ID  5.46101e-05:0.000212053:0.09691:0.077007:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.077007 ES:SE:LP:AF:ID  5.46101e-05:0.000212053:0.09691:0.077007:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041521 ES:SE:LP:AF:ID  -0.000158893:0.000295581:0.229148:0.041521:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060964 ES:SE:LP:AF:ID  -4.78668e-05:0.000224796:0.0809219:0.060964:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075403 ES:SE:LP:AF:ID  -0.000159897:0.000207363:0.356547:0.075403:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.07543  ES:SE:LP:AF:ID  -0.000160119:0.000207321:0.356547:0.07543:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352687 ES:SE:LP:AF:ID  -2.46237e-05:0.000118687:0.0757207:0.352687:rs201754587
1   86028   rs114608975 T   C   .   PASS    AF=0.103492 ES:SE:LP:AF:ID  -2.75327e-05:0.000201899:0.05061:0.103492:rs114608975
1   86065   rs116504101 G   C   .   PASS    AF=0.076094 ES:SE:LP:AF:ID  -0.000149028:0.000207933:0.327902:0.076094:rs116504101
1   86331   rs115209712 A   G   .   PASS    AF=0.10961  ES:SE:LP:AF:ID  -0.000142556:0.000182888:0.356547:0.10961:rs115209712