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/7323be05-3b58-4a7d-959f-e3740db2e1d8/call-ldsc/inputs/562856165/ieu-b-29.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-29/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Aug 21 01:23:46 2020
Reading summary statistics from /data/cromwell-executions/qc/7323be05-3b58-4a7d-959f-e3740db2e1d8/call-ldsc/inputs/562856165/ieu-b-29.vcf.gz ...
Read summary statistics for 26797652 SNPs.
Dropped 126228 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ...
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] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1220779 SNPs remain.
After merging with regression SNP LD, 1220779 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0625 (0.0052)
Lambda GC: 1.3111
Mean Chi^2: 1.7023
Intercept: 1.1008 (0.0131)
Ratio: 0.1435 (0.0187)
Analysis finished at Fri Aug 21 01:28:29 2020
Total time elapsed: 4.0m:43.68s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9663,
    "inflation_factor": 1.0804,
    "mean_EFFECT": -0.0025,
    "n": 474001,
    "n_snps": 26797883,
    "n_clumped_hits": 201,
    "n_p_sig": 27786,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 32823,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 2118258,
    "n_est": 359294.9888,
    "ratio_se_n": 0.8706,
    "mean_diff": 0.0006,
    "ratio_diff": 1.9554,
    "sd_y_est1": 1.2874,
    "sd_y_est2": 1.1209,
    "r2_sum1": 0.0387,
    "r2_sum2": 0.0234,
    "r2_sum3": 0.0308,
    "r2_sum4": 0.0377,
    "ldsc_nsnp_merge_refpanel_ld": 1220779,
    "ldsc_nsnp_merge_regression_ld": 1220779,
    "ldsc_observed_scale_h2_beta": 0.0625,
    "ldsc_observed_scale_h2_se": 0.0052,
    "ldsc_intercept_beta": 1.1008,
    "ldsc_intercept_se": 0.0131,
    "ldsc_lambda_gc": 1.3111,
    "ldsc_mean_chisq": 1.7023,
    "ldsc_ratio": 0.1435
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 47 0.9999982 3 64 0 26796084 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.655104e+00 5.783659e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.897093e+07 5.623767e+07 56.000000 3.282779e+07 6.963202e+07 1.148417e+08 2.492398e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.520400e-03 1.279777e-01 -4.615790 -2.463500e-02 -1.970000e-04 2.063500e-02 7.265790e+00 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.287500e-02 9.741390e-02 0.001997 7.373000e-03 4.939800e-02 1.238030e-01 6.890430e+00 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.865750e-01 2.932561e-01 0.000000 2.295192e-01 4.832535e-01 7.406278e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.865748e-01 2.932570e-01 0.000000 2.295382e-01 4.832397e-01 7.406194e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 7.923450e-02 1.930541e-01 0.000025 1.560000e-04 7.400000e-04 2.363000e-02 9.999750e-01 ▇▁▁▁▁
numeric AF_reference 2118258 0.9209543 NA NA NA NA NA 9.014430e-02 1.925894e-01 0.000000 1.397800e-03 7.388200e-03 5.391370e-02 1.000000e+00 ▇▁▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 4.206801e+05 1.107789e+05 396.000000 4.257370e+05 4.563230e+05 4.726030e+05 4.740010e+05 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 16141 rs529651976 C T -0.107128 0.211137 0.6119064 0.6118839 0.000528 0.0025958 35960
1 49298 rs200943160 T C -0.009012 0.011219 0.4218383 0.4218128 0.823488 0.7821490 35960
1 54353 rs140052487 C A -0.093822 0.099718 0.3467616 0.3467698 0.001848 0.0089856 35960
1 54564 rs558796213 G T 0.013768 0.117877 0.9069961 0.9070188 0.000143 0.0041933 404718
1 54591 rs561234294 A G 0.038867 0.118430 0.7427779 0.7427715 0.001573 0.0035942 35960
1 54712 rs552304420 T C 0.035990 0.044022 0.4136176 0.4136166 0.010376 0.0109824 35960
1 54815 rs568686875 T C 0.265242 0.185100 0.1518529 0.1518676 0.000482 0.0019968 35960
1 55326 rs3107975 T C 0.038077 0.033208 0.2515261 0.2515382 0.019507 0.0459265 35960
1 55351 rs531766459 T A -0.036419 0.062549 0.5604166 0.5604000 0.000504 0.0007987 404718
1 55405 rs372455836 C T -0.042056 0.055434 0.4480670 0.4480512 0.006921 0.0075879 35960
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51237137 rs534739169 A C -0.049554 0.089557 0.5800614 0.5800419 0.000214 0.0001997 440678
22 51237410 rs530437591 G A -0.026856 0.057906 0.6428224 0.6428010 0.000355 0.0017971 440678
22 51237486 rs149820726 G C -0.007146 0.160422 0.9644551 0.9644700 0.000528 0.0025958 35960
22 51238275 rs202031343 C T 0.038389 0.104267 0.7127496 0.7127392 0.001251 0.0009984 35960
22 51238307 rs577028785 A G 0.044573 0.232951 0.8482440 0.8482587 0.000250 0.0015974 35960
22 51238349 rs546389903 T C 0.362966 0.285239 0.2031758 0.2031963 0.000167 0.0013978 35960
22 51238660 rs569936315 A G 0.054786 0.152888 0.7201020 0.7200883 0.000066 0.0167732 440678
22 51239586 rs535432390 T G -0.048054 0.022214 0.0305429 0.0305235 0.002935 0.0001997 458825
22 51239678 rs573137567 G T 0.069831 0.084904 0.4108081 0.4108094 0.001891 0.0233626 35960
22 51244163 rs199560686 A G 0.039150 0.210964 0.8527629 0.8527767 0.000052 0.0077875 440678

bcf preview

1   16141   rs529651976 C   T   .   PASS    AF=0.000528 ES:SE:LP:AF:SS:ID   -0.107128:0.211137:0.213315:0.000528:35960:rs529651976
1   49298   rs10399793  T   C   .   PASS    AF=0.823488 ES:SE:LP:AF:SS:ID   -0.009012:0.011219:0.374854:0.823488:35960:rs10399793
1   54353   rs140052487 C   A   .   PASS    AF=0.001848 ES:SE:LP:AF:SS:ID   -0.093822:0.099718:0.459969:0.001848:35960:rs140052487
1   54564   rs558796213 G   T   .   PASS    AF=0.000143 ES:SE:LP:AF:SS:ID   0.013768:0.117877:0.0423946:0.000143:404718:rs558796213
1   54591   rs561234294 A   G   .   PASS    AF=0.001573 ES:SE:LP:AF:SS:ID   0.038867:0.11843:0.129141:0.001573:35960:rs561234294
1   54712   rs573184866 T   C   .   PASS    AF=0.010376 ES:SE:LP:AF:SS:ID   0.03599:0.044022:0.383401:0.010376:35960:rs573184866
1   54815   rs568686875 T   C   .   PASS    AF=0.000482 ES:SE:LP:AF:SS:ID   0.265242:0.1851:0.818577:0.000482:35960:rs568686875
1   55326   rs3107975   T   C   .   PASS    AF=0.019507 ES:SE:LP:AF:SS:ID   0.038077:0.033208:0.599417:0.019507:35960:rs3107975
1   55351   rs531766459 T   A   .   PASS    AF=0.000504 ES:SE:LP:AF:SS:ID   -0.036419:0.062549:0.251489:0.000504:404718:rs531766459
1   55405   rs372455836 C   T   .   PASS    AF=0.006921 ES:SE:LP:AF:SS:ID   -0.042056:0.055434:0.348657:0.006921:35960:rs372455836
1   55416   rs193242050 G   A   .   PASS    AF=9.4e-05  ES:SE:LP:AF:SS:ID   -0.102384:0.163775:0.274176:9.4e-05:440678:rs193242050
1   55427   rs183189405 T   C   .   PASS    AF=0.002363 ES:SE:LP:AF:SS:ID   -0.161991:0.10939:0.858133:0.002363:35960:rs183189405
1   56586   rs541979596 G   A   .   PASS    AF=0.001511 ES:SE:LP:AF:SS:ID   0.020798:0.130259:0.0589221:0.001511:35960:rs541979596
1   57095   rs553759011 T   C   .   PASS    AF=3.7e-05  ES:SE:LP:AF:SS:ID   0.133374:0.232792:0.246637:3.7e-05:404718:rs553759011
1   57183   rs368339209 A   G   .   PASS    AF=2.8e-05  ES:SE:LP:AF:SS:ID   -0.008223:0.382447:0.0075185:2.8e-05:404718:rs368339209
1   61804   rs567421057 G   A   .   PASS    AF=7.4e-05  ES:SE:LP:AF:SS:ID   0.17678:0.170874:0.52164:7.4e-05:404718:rs567421057
1   61993   rs190553843 C   T   .   PASS    AF=9.5e-05  ES:SE:LP:AF:SS:ID   0.049549:0.159332:0.121582:9.5e-05:440678:rs190553843
1   62124   rs528478839 G   A   .   PASS    AF=0.000178 ES:SE:LP:AF:SS:ID   -0.180634:0.394616:0.188991:0.000178:35960:rs528478839
1   62157   rs10399597  G   A   .   PASS    AF=0.000139 ES:SE:LP:AF:SS:ID   -0.002667:0.100378:0.00930915:0.000139:440678:rs10399597
1   62509   rs534313866 T   C   .   PASS    AF=0.000549 ES:SE:LP:AF:SS:ID   -0.10157:0.213131:0.198118:0.000549:35960:rs534313866
1   62617   rs543126209 T   G   .   PASS    AF=9.3e-05  ES:SE:LP:AF:SS:ID   -0.072458:0.163048:0.182581:9.3e-05:440678:rs543126209
1   64670   rs545257650 A   G   .   PASS    AF=0.000145 ES:SE:LP:AF:SS:ID   -0.008953:0.120412:0.0265438:0.000145:440678:rs545257650
1   64908   rs540391097 A   G   .   PASS    AF=0.000638 ES:SE:LP:AF:SS:ID   0.007206:0.056373:0.046595:0.000638:440678:rs540391097
1   65009   rs563233355 G   A   .   PASS    AF=0.000293 ES:SE:LP:AF:SS:ID   0.10516:0.075421:0.787251:0.000293:440678:rs563233355
1   65974   rs531923826 A   G   .   PASS    AF=0.004664 ES:SE:LP:AF:SS:ID   -0.006318:0.068182:0.0333173:0.004664:35960:rs531923826
1   67179   rs149952626 C   G   .   PASS    AF=0.000127 ES:SE:LP:AF:SS:ID   -0.396008:0.368283:0.549395:0.000127:35960:rs149952626
1   67223   rs78676975  C   T   .   PASS    AF=0.000485 ES:SE:LP:AF:SS:ID   0.097616:0.245816:0.160331:0.000485:35960:rs78676975
1   67224   rs566526215 G   A   .   PASS    AF=0.000161 ES:SE:LP:AF:SS:ID   0.042546:0.127783:0.131252:0.000161:440678:rs566526215
1   67631   rs533896527 G   C   .   PASS    AF=0.000201 ES:SE:LP:AF:SS:ID   0.050413:0.097004:0.219468:0.000201:440678:rs533896527
1   69594   rs144967600 T   C   .   PASS    AF=0.000733 ES:SE:LP:AF:SS:ID   -0.064611:0.189702:0.134646:0.000733:35960:rs144967600
1   69610   rs376022826 C   T   .   PASS    AF=0.000204 ES:SE:LP:AF:SS:ID   -0.262:0.410801:0.28097:0.000204:35960:rs376022826
1   70317   rs570011908 G   A   .   PASS    AF=0.000633 ES:SE:LP:AF:SS:ID   0.361457:0.204284:1.11444:0.000633:35960:rs570011908
1   72526   rs547237130 A   G   .   PASS    AF=0.038306 ES:SE:LP:AF:SS:ID   0.030873:0.023138:0.73969:0.038306:35960:rs547237130
1   73093   rs535508237 G   A   .   PASS    AF=0.004017 ES:SE:LP:AF:SS:ID   -0.033046:0.069255:0.198415:0.004017:35960:rs535508237
1   77763   rs557457745 G   A   .   PASS    AF=0.00542  ES:SE:LP:AF:SS:ID   0.036987:0.061916:0.259421:0.00542:35960:rs557457745
1   78942   rs372315362 C   G   .   PASS    AF=0.008046 ES:SE:LP:AF:SS:ID   -0.033876:0.048748:0.312362:0.008046:35960:rs372315362
1   79033   rs2462495   A   G   .   PASS    AF=0.998704 ES:SE:LP:AF:SS:ID   -0.0083:0.049504:0.0620631:0.998704:404718:rs2462495
1   79137   rs143777184 A   T   .   PASS    AF=0.001029 ES:SE:LP:AF:SS:ID   0.035553:0.043521:0.383025:0.001029:440678:rs143777184
1   79188   rs534350410 G   T   .   PASS    AF=0.001127 ES:SE:LP:AF:SS:ID   0.005724:0.146375:0.0137699:0.001127:35960:rs534350410
1   82957   rs189774606 C   T   .   PASS    AF=0.00047  ES:SE:LP:AF:SS:ID   -0.010183:0.056942:0.0664808:0.00047:440678:rs189774606
1   82961   rs537801787 C   T   .   PASS    AF=0.000515 ES:SE:LP:AF:SS:ID   -0.032688:0.211498:0.0569242:0.000515:35960:rs537801787
1   82994   rs574556077 A   G   .   PASS    AF=0.000187 ES:SE:LP:AF:SS:ID   0.033813:0.316675:0.0386045:0.000187:35960:rs574556077
1   83170   rs562997564 G   T   .   PASS    AF=0.001249 ES:SE:LP:AF:SS:ID   -0.084923:0.138439:0.267921:0.001249:35960:rs562997564
1   83771   rs189906733 T   G   .   PASS    AF=0.000667 ES:SE:LP:AF:SS:ID   -0.016979:0.049905:0.134486:0.000667:440678:rs189906733
1   84139   rs183605470 A   T   .   PASS    AF=0.020838 ES:SE:LP:AF:SS:ID   0.024519:0.031534:0.35968:0.020838:35960:rs183605470
1   84618   rs576633512 C   T   .   PASS    AF=0.000696 ES:SE:LP:AF:SS:ID   0.38052:0.188135:1.36518:0.000696:35960:rs576633512
1   85622   rs185273034 A   T   .   PASS    AF=0.001253 ES:SE:LP:AF:SS:ID   -0.067565:0.138013:0.204486:0.001253:35960:rs185273034
1   85892   rs147185795 A   G   .   PASS    AF=0.000457 ES:SE:LP:AF:SS:ID   0.027874:0.06494:0.175368:0.000457:440678:rs147185795
1   86028   rs114608975 T   C   .   PASS    AF=0.061018 ES:SE:LP:AF:SS:ID   -0.033409:0.018207:1.17703:0.061018:35960:rs114608975
1   86192   rs548281277 G   A   .   PASS    AF=0.034611 ES:SE:LP:AF:SS:ID   0.045482:0.024311:1.21197:0.034611:35960:rs548281277