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/57e34be8-352f-4f93-9d1d-0b7a687e067e/call-ldsc/inputs/562856187/ieu-b-30.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-30/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Aug 21 01:29:43 2020
Reading summary statistics from /data/cromwell-executions/qc/57e34be8-352f-4f93-9d1d-0b7a687e067e/call-ldsc/inputs/562856187/ieu-b-30.vcf.gz ...
Read summary statistics for 27090670 SNPs.
Dropped 128540 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, 1220780 SNPs remain.
After merging with regression SNP LD, 1220780 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1774 (0.0112)
Lambda GC: 1.9241
Mean Chi^2: 3.4242
Intercept: 1.3376 (0.0289)
Ratio: 0.1392 (0.0119)
Analysis finished at Fri Aug 21 01:34:34 2020
Total time elapsed: 4.0m:51.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9668,
    "inflation_factor": 1.2184,
    "mean_EFFECT": 0.0001,
    "n": 562243,
    "n_snps": 27090906,
    "n_clumped_hits": 507,
    "n_p_sig": 117809,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 67997,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 2142622,
    "n_est": 401285.6742,
    "ratio_se_n": 0.8448,
    "mean_diff": -0.0001,
    "ratio_diff": 1.2433,
    "sd_y_est1": 1.3843,
    "sd_y_est2": 1.1695,
    "r2_sum1": 0.0967,
    "r2_sum2": 0.0505,
    "r2_sum3": 0.0707,
    "r2_sum4": 0.0991,
    "ldsc_nsnp_merge_refpanel_ld": 1220780,
    "ldsc_nsnp_merge_regression_ld": 1220780,
    "ldsc_observed_scale_h2_beta": 0.1774,
    "ldsc_observed_scale_h2_se": 0.0112,
    "ldsc_intercept_beta": 1.3376,
    "ldsc_intercept_se": 0.0289,
    "ldsc_lambda_gc": 1.9241,
    "ldsc_mean_chisq": 3.4242,
    "ldsc_ratio": 0.1393
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
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 48 0.9999982 3 64 0 27089072 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 8.652631e+00 5.781882e+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 7.898692e+07 5.625017e+07 56.000000 3.283874e+07 6.963686e+07 1.148587e+08 2.492398e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.297000e-04 1.792292e-01 -74.136800 -2.199700e-02 5.700000e-05 2.253200e-02 4.481330e+01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.649400e-02 1.642921e-01 0.001799 6.855000e-03 4.628900e-02 1.180820e-01 8.903050e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.663526e-01 3.000334e-01 0.000000 1.983741e-01 4.565728e-01 7.267098e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.663522e-01 3.000346e-01 0.000000 1.983951e-01 4.565628e-01 7.266991e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 7.845300e-02 1.921642e-01 0.000025 1.720000e-04 8.200000e-04 2.239480e-02 9.999750e-01 ▇▁▁▁▁
numeric AF_reference 2142622 0.9209099 NA NA NA NA NA 8.923040e-02 1.918093e-01 0.000000 1.397800e-03 7.188500e-03 5.211660e-02 1.000000e+00 ▇▁▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 4.582429e+05 1.388749e+05 683.000000 4.444420e+05 4.890530e+05 5.581440e+05 5.622430e+05 ▁▁▁▃▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 16141 rs529651976 C T 0.204886 0.210882 0.3312547 0.3312660 0.000523 0.0025958 36410
1 49298 rs200943160 T C 0.013640 0.011139 0.2207257 0.2207537 0.823664 0.7821490 36410
1 54353 rs140052487 C A 0.082686 0.098517 0.4012989 0.4012971 0.001861 0.0089856 36410
1 54564 rs558796213 G T 0.081243 0.114214 0.4768974 0.4768843 0.000141 0.0041933 408032
1 54591 rs561234294 A G -0.118643 0.118275 0.3157941 0.3158071 0.001561 0.0035942 36410
1 54712 rs552304420 T C 0.086113 0.043579 0.0481682 0.0481524 0.010412 0.0109824 36410
1 54815 rs568686875 T C -0.028470 0.184712 0.8774860 0.8775058 0.000480 0.0019968 36410
1 55326 rs3107975 T C -0.013205 0.032807 0.6873374 0.6873120 0.019657 0.0459265 36410
1 55351 rs531766459 T A -0.044334 0.060044 0.4603127 0.4602966 0.000503 0.0007987 408032
1 55405 rs372455836 C T 0.049440 0.055084 0.3694214 0.3694317 0.006910 0.0075879 36410
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51237137 rs534739169 A C -0.079274 0.087784 0.3664933 0.3664954 0.000215 0.0001997 444442
22 51237410 rs530437591 G A 0.013528 0.056995 0.8123689 0.8123821 0.000358 0.0017971 444442
22 51237486 rs149820726 G C 0.063270 0.157960 0.6887744 0.6887556 0.000536 0.0025958 36410
22 51238275 rs202031343 C T 0.148257 0.102879 0.1495481 0.1495617 0.001263 0.0009984 36410
22 51238307 rs577028785 A G 0.006675 0.226187 0.9764459 0.9764571 0.000261 0.0015974 36410
22 51238349 rs546389903 T C -0.193449 0.284541 0.4966072 0.4965910 0.000165 0.0013978 36410
22 51238660 rs569936315 A G -0.047204 0.151800 0.7558385 0.7558297 0.000066 0.0167732 444442
22 51239586 rs535432390 T G -0.027704 0.020913 0.1852371 0.1852620 0.002968 0.0001997 490028
22 51239678 rs573137567 G T 0.057569 0.084080 0.4935475 0.4935376 0.001895 0.0233626 36410
22 51244163 rs199560686 A G 0.008184 0.205218 0.9681751 0.9681892 0.000054 0.0077875 444442

bcf preview

1   16141   rs529651976 C   T   .   PASS    AF=0.000523 ES:SE:LP:AF:SS:ID   0.204886:0.210882:0.479838:0.000523:36410:rs529651976
1   49298   rs10399793  T   C   .   PASS    AF=0.823664 ES:SE:LP:AF:SS:ID   0.01364:0.011139:0.656147:0.823664:36410:rs10399793
1   54353   rs140052487 C   A   .   PASS    AF=0.001861 ES:SE:LP:AF:SS:ID   0.082686:0.098517:0.396532:0.001861:36410:rs140052487
1   54564   rs558796213 G   T   .   PASS    AF=0.000141 ES:SE:LP:AF:SS:ID   0.081243:0.114214:0.321575:0.000141:408032:rs558796213
1   54591   rs561234294 A   G   .   PASS    AF=0.001561 ES:SE:LP:AF:SS:ID   -0.118643:0.118275:0.500596:0.001561:36410:rs561234294
1   54712   rs573184866 T   C   .   PASS    AF=0.010412 ES:SE:LP:AF:SS:ID   0.086113:0.043579:1.31724:0.010412:36410:rs573184866
1   54815   rs568686875 T   C   .   PASS    AF=0.00048  ES:SE:LP:AF:SS:ID   -0.02847:0.184712:0.0567598:0.00048:36410:rs568686875
1   55326   rs3107975   T   C   .   PASS    AF=0.019657 ES:SE:LP:AF:SS:ID   -0.013205:0.032807:0.16283:0.019657:36410:rs3107975
1   55351   rs531766459 T   A   .   PASS    AF=0.000503 ES:SE:LP:AF:SS:ID   -0.044334:0.060044:0.336947:0.000503:408032:rs531766459
1   55405   rs372455836 C   T   .   PASS    AF=0.00691  ES:SE:LP:AF:SS:ID   0.04944:0.055084:0.432478:0.00691:36410:rs372455836
1   55416   rs193242050 G   A   .   PASS    AF=9.4e-05  ES:SE:LP:AF:SS:ID   0.024508:0.162627:0.0554226:9.4e-05:444442:rs193242050
1   55427   rs183189405 T   C   .   PASS    AF=0.002378 ES:SE:LP:AF:SS:ID   -0.029572:0.10776:0.105819:0.002378:36410:rs183189405
1   56586   rs541979596 G   A   .   PASS    AF=0.001497 ES:SE:LP:AF:SS:ID   -0.087601:0.130091:0.300406:0.001497:36410:rs541979596
1   57095   rs553759011 T   C   .   PASS    AF=3.6e-05  ES:SE:LP:AF:SS:ID   0.222206:0.223963:0.493348:3.6e-05:408032:rs553759011
1   57183   rs368339209 A   G   .   PASS    AF=2.8e-05  ES:SE:LP:AF:SS:ID   0.27325:0.367894:0.339467:2.8e-05:408032:rs368339209
1   61804   rs567421057 G   A   .   PASS    AF=7.4e-05  ES:SE:LP:AF:SS:ID   0.239626:0.164391:0.838866:7.4e-05:408032:rs567421057
1   61993   rs190553843 C   T   .   PASS    AF=9.5e-05  ES:SE:LP:AF:SS:ID   0.192671:0.157861:0.65316:9.5e-05:444442:rs190553843
1   62124   rs528478839 G   A   .   PASS    AF=0.00018  ES:SE:LP:AF:SS:ID   0.397854:0.393755:0.505449:0.00018:36410:rs528478839
1   62157   rs10399597  G   A   .   PASS    AF=0.00014  ES:SE:LP:AF:SS:ID   0.151662:0.096676:0.932951:0.00014:444442:rs10399597
1   62509   rs534313866 T   C   .   PASS    AF=0.000544 ES:SE:LP:AF:SS:ID   0.198491:0.212872:0.454569:0.000544:36410:rs534313866
1   62617   rs543126209 T   G   .   PASS    AF=9.3e-05  ES:SE:LP:AF:SS:ID   0.036725:0.16193:0.0858817:9.3e-05:444442:rs543126209
1   64670   rs545257650 A   G   .   PASS    AF=0.000147 ES:SE:LP:AF:SS:ID   -0.104839:0.117257:0.430315:0.000147:444442:rs545257650
1   64908   rs540391097 A   G   .   PASS    AF=0.000642 ES:SE:LP:AF:SS:ID   -0.034953:0.053777:0.28758:0.000642:444442:rs540391097
1   65009   rs563233355 G   A   .   PASS    AF=0.000292 ES:SE:LP:AF:SS:ID   0.091127:0.07334:0.669542:0.000292:444442:rs563233355
1   65974   rs531923826 A   G   .   PASS    AF=0.004619 ES:SE:LP:AF:SS:ID   -0.085504:0.068244:0.677332:0.004619:36410:rs531923826
1   67179   rs149952626 C   G   .   PASS    AF=0.00014  ES:SE:LP:AF:SS:ID   -0.108757:0.344577:0.123612:0.00014:36410:rs149952626
1   67223   rs78676975  C   T   .   PASS    AF=0.000484 ES:SE:LP:AF:SS:ID   0.071448:0.245207:0.113077:0.000484:36410:rs78676975
1   67224   rs566526215 G   A   .   PASS    AF=0.000161 ES:SE:LP:AF:SS:ID   0.004988:0.124951:0.0140609:0.000161:444442:rs566526215
1   67631   rs533896527 G   C   .   PASS    AF=0.0002   ES:SE:LP:AF:SS:ID   -0.059728:0.095267:0.27514:0.0002:444442:rs533896527
1   69594   rs144967600 T   C   .   PASS    AF=0.00074  ES:SE:LP:AF:SS:ID   -0.10272:0.185953:0.236049:0.00074:36410:rs144967600
1   69610   rs376022826 C   T   .   PASS    AF=0.000218 ES:SE:LP:AF:SS:ID   0.103237:0.378603:0.105075:0.000218:36410:rs376022826
1   70317   rs570011908 G   A   .   PASS    AF=0.000635 ES:SE:LP:AF:SS:ID   -0.006827:0.2034:0.011793:0.000635:36410:rs570011908
1   72526   rs547237130 A   G   .   PASS    AF=0.038254 ES:SE:LP:AF:SS:ID   0.004603:0.022997:0.0750269:0.038254:36410:rs547237130
1   73093   rs535508237 G   A   .   PASS    AF=0.004009 ES:SE:LP:AF:SS:ID   -0.015467:0.068491:0.0854855:0.004009:36410:rs535508237
1   77763   rs557457745 G   A   .   PASS    AF=0.005348 ES:SE:LP:AF:SS:ID   -0.06144:0.062396:0.488425:0.005348:36410:rs557457745
1   78942   rs372315362 C   G   .   PASS    AF=0.00803  ES:SE:LP:AF:SS:ID   0.008269:0.048369:0.0633656:0.00803:36410:rs372315362
1   79033   rs2462495   A   G   .   PASS    AF=0.998702 ES:SE:LP:AF:SS:ID   -0.011079:0.047298:0.0889538:0.998702:408032:rs2462495
1   79137   rs143777184 A   T   .   PASS    AF=0.001023 ES:SE:LP:AF:SS:ID   -0.023925:0.043042:0.237819:0.001023:444442:rs143777184
1   79188   rs534350410 G   T   .   PASS    AF=0.001123 ES:SE:LP:AF:SS:ID   -0.123423:0.145978:0.400295:0.001123:36410:rs534350410
1   82957   rs189774606 C   T   .   PASS    AF=0.000468 ES:SE:LP:AF:SS:ID   0.019902:0.056268:0.140519:0.000468:444442:rs189774606
1   82961   rs537801787 C   T   .   PASS    AF=0.000513 ES:SE:LP:AF:SS:ID   0.059909:0.211141:0.109796:0.000513:36410:rs537801787
1   82994   rs574556077 A   G   .   PASS    AF=0.000185 ES:SE:LP:AF:SS:ID   0.107309:0.316355:0.134028:0.000185:36410:rs574556077
1   83170   rs562997564 G   T   .   PASS    AF=0.001239 ES:SE:LP:AF:SS:ID   0.176298:0.138248:0.694202:0.001239:36410:rs562997564
1   83771   rs189906733 T   G   .   PASS    AF=0.000664 ES:SE:LP:AF:SS:ID   -0.012065:0.049139:0.0936407:0.000664:444442:rs189906733
1   84139   rs183605470 A   T   .   PASS    AF=0.020806 ES:SE:LP:AF:SS:ID   -0.005258:0.031329:0.0621337:0.020806:36410:rs183605470
1   84618   rs576633512 C   T   .   PASS    AF=0.000712 ES:SE:LP:AF:SS:ID   -0.035167:0.184108:0.0713466:0.000712:36410:rs576633512
1   85622   rs185273034 A   T   .   PASS    AF=0.001245 ES:SE:LP:AF:SS:ID   0.131455:0.137799:0.468402:0.001245:36410:rs185273034
1   85892   rs147185795 A   G   .   PASS    AF=0.000455 ES:SE:LP:AF:SS:ID   -0.066499:0.064435:0.519928:0.000455:444442:rs147185795
1   86028   rs114608975 T   C   .   PASS    AF=0.061235 ES:SE:LP:AF:SS:ID   -0.015394:0.018023:0.40559:0.061235:36410:rs114608975
1   86192   rs548281277 G   A   .   PASS    AF=0.03455  ES:SE:LP:AF:SS:ID   0.005175:0.024172:0.0806719:0.03455:36410:rs548281277