Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std 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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1012/ieu-a-1012.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1012/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 18:52:20 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1012/ieu-a-1012.vcf.gz ...
Read summary statistics for 2576971 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1238054 SNPs remain.
After merging with regression SNP LD, 1238054 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0597 (0.0317)
Lambda GC: 1.0141
Mean Chi^2: 1.0179
Intercept: 1.0043 (0.0051)
Ratio: 0.2371 (0.282)
Analysis finished at Tue Feb  4 18:52:51 2020
Total time elapsed: 31.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9242,
    "inflation_factor": 1.0104,
    "mean_EFFECT": 0,
    "n": 12597,
    "n_snps": 2576971,
    "n_clumped_hits": 1,
    "n_p_sig": 19,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 22817,
    "n_est": 11681.7535,
    "ratio_se_n": 0.963,
    "mean_diff": -0,
    "ratio_diff": 1.0051,
    "sd_y_est1": 1.05,
    "sd_y_est2": 1.0111,
    "r2_sum1": 0.0036,
    "r2_sum2": 0.0033,
    "r2_sum3": 0.0035,
    "r2_sum4": 0.0038,
    "ldsc_nsnp_merge_refpanel_ld": 1238054,
    "ldsc_nsnp_merge_regression_ld": 1238054,
    "ldsc_observed_scale_h2_beta": 0.0597,
    "ldsc_observed_scale_h2_se": 0.0317,
    "ldsc_intercept_beta": 1.0043,
    "ldsc_intercept_se": 0.0051,
    "ldsc_lambda_gc": 1.0141,
    "ldsc_mean_chisq": 1.0179,
    "ldsc_ratio": 0.2402
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 42 0 2576971 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 8.601925e+00 5.676305e+00 1.0000000 4.000000e+00 8.000000e+00 1.200000e+01 2.30000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.879566e+07 5.582625e+07 6689.0000000 3.246815e+07 7.006629e+07 1.143752e+08 2.49219e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.520000e-05 3.327460e-02 -1.4770700 -1.229900e-02 -4.700000e-05 1.225600e-02 1.08294e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.361130e-02 2.322290e-02 0.0120450 1.345400e-02 1.602000e-02 2.345700e-02 5.71692e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.980011e-01 2.895264e-01 0.0000000 2.466999e-01 4.977703e-01 7.492064e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.980011e-01 2.895272e-01 0.0000000 2.467225e-01 4.977554e-01 7.492027e-01 1.00000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 3.615347e-01 2.705812e-01 0.0200000 1.258290e-01 2.978910e-01 5.597775e-01 9.79993e-01 ▇▅▃▂▂
numeric AF_reference 22817 0.9911458 NA NA NA NA NA 3.637514e-01 2.552413e-01 0.0001997 1.489620e-01 3.033150e-01 5.485220e-01 1.00000e+00 ▇▆▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 1.132985e+04 2.937865e+03 413.0000000 1.144100e+04 1.259100e+04 1.259200e+04 1.25970e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C -0.048645 0.060899 0.4244192 0.4244171 0.078099 0.0371406 4603
1 723819 rs11804171 T A -0.048648 0.060730 0.4230990 0.4231005 0.078099 0.1345850 4603
1 723891 rs2977670 G C 0.005131 0.044581 0.9083539 0.9083707 0.905230 0.7799520 5754
1 750235 rs12138618 G A -0.083137 0.048673 0.0876274 0.0876229 0.067001 NA 6170
1 752566 rs3094315 G A -0.013589 0.023816 0.5683214 0.5682825 0.821298 0.7182510 6222
1 752721 rs3131972 A G -0.081858 0.060525 0.1762082 0.1762263 0.806855 0.6533550 919
1 753541 rs2073813 G A 0.059746 0.042734 0.1620720 0.1620859 0.164488 0.3019170 2070
1 754192 rs3131968 A G -0.036722 0.028795 0.2021929 0.2022063 0.863968 0.6785140 6673
1 761732 rs2286139 C T -0.060356 0.043061 0.1610089 0.1610229 0.838135 0.6257990 2070
1 768448 rs12562034 G A -0.055183 0.031896 0.0836142 0.0836139 0.103797 0.1918930 5719
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51216564 rs9616970 T C 0.053072 0.030255 0.0794090 0.0794037 0.148228 0.1563500 9332
22 51217134 rs117417021 A G 0.017782 0.022258 0.4243605 0.4243462 0.430333 0.2671730 9332
22 51222100 rs114553188 G T 0.103963 0.035470 0.0033890 0.0033786 0.057088 0.0880591 11440
22 51223637 rs375798137 G A 0.104050 0.035525 0.0034130 0.0034014 0.057068 0.0788738 11440
22 51229805 rs9616985 T C 0.003658 0.042866 0.9319691 0.9319945 0.100037 0.0730831 8434
23 35921591 rs2204667 C G 0.000915 0.017446 0.9581469 0.9581721 0.158044 NA 12592
23 51666786 rs14115 A G 0.001761 0.027381 0.9486950 0.9487197 0.061255 NA 11437
23 70163799 rs1626496 A C -0.025617 0.025302 0.3113121 0.3113231 0.071022 NA 12593
23 91415872 rs6562597 G A 0.096467 0.058723 0.1004350 0.1004354 0.024141 0.0021192 6605
23 118495837 rs12882977 G A -0.005328 0.012476 0.6693373 0.6693357 0.476340 0.2307280 12592

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.078099 ES:SE:LP:AF:SS:ID   -0.048645:0.060899:0.372205:0.078099:4603:rs12565286
1   723819  rs11804171  T   A   .   PASS    AF=0.078099 ES:SE:LP:AF:SS:ID   -0.048648:0.06073:0.373558:0.078099:4603:rs11804171
1   723891  rs2977670   G   C   .   PASS    AF=0.90523  ES:SE:LP:AF:SS:ID   0.005131:0.044581:0.0417449:0.90523:5754:rs2977670
1   750235  rs12138618  G   A   .   PASS    AF=0.067001 ES:SE:LP:AF:SS:ID   -0.083137:0.048673:1.05736:0.067001:6170:rs12138618
1   752566  rs3094315   G   A   .   PASS    AF=0.821298 ES:SE:LP:AF:SS:ID   -0.013589:0.023816:0.245406:0.821298:6222:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.806855 ES:SE:LP:AF:SS:ID   -0.081858:0.060525:0.753974:0.806855:919:rs3131972
1   753541  rs2073813   G   A   .   PASS    AF=0.164488 ES:SE:LP:AF:SS:ID   0.059746:0.042734:0.790292:0.164488:2070:rs2073813
1   754192  rs3131968   A   G   .   PASS    AF=0.863968 ES:SE:LP:AF:SS:ID   -0.036722:0.028795:0.694234:0.863968:6673:rs3131968
1   761732  rs2286139   C   T   .   PASS    AF=0.838135 ES:SE:LP:AF:SS:ID   -0.060356:0.043061:0.79315:0.838135:2070:rs2286139
1   768448  rs12562034  G   A   .   PASS    AF=0.103797 ES:SE:LP:AF:SS:ID   -0.055183:0.031896:1.07772:0.103797:5719:rs12562034
1   775659  rs2905035   A   G   .   PASS    AF=0.864556 ES:SE:LP:AF:SS:ID   -0.039826:0.029764:0.742653:0.864556:6673:rs2905035
1   776546  rs12124819  A   G   .   PASS    AF=0.259004 ES:SE:LP:AF:SS:ID   0.027254:0.03238:0.397981:0.259004:2602:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.864838 ES:SE:LP:AF:SS:ID   -0.040279:0.029867:0.750924:0.864838:6673:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.130804 ES:SE:LP:AF:SS:ID   0.037304:0.034781:0.547514:0.130804:5522:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.869239 ES:SE:LP:AF:SS:ID   -0.037583:0.034889:0.550731:0.869239:5522:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.869514 ES:SE:LP:AF:SS:ID   -0.039536:0.035462:0.576943:0.869514:5522:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.86966  ES:SE:LP:AF:SS:ID   -0.039247:0.03575:0.565003:0.86966:5522:rs2980300
1   798026  rs4951864   C   T   .   PASS    AF=0.895308 ES:SE:LP:AF:SS:ID   0.063756:0.034675:1.18061:0.895308:7089:rs4951864
1   798801  rs12132517  G   A   .   PASS    AF=0.111598 ES:SE:LP:AF:SS:ID   -0.061209:0.034882:1.1007:0.111598:7089:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.200698 ES:SE:LP:AF:SS:ID   -0.032441:0.03028:0.546694:0.200698:6673:rs11240777
1   838555  rs4970383   C   A   .   PASS    AF=0.251904 ES:SE:LP:AF:SS:ID   -0.014845:0.051798:0.111021:0.251904:919:rs4970383
1   846808  rs4475691   C   T   .   PASS    AF=0.173931 ES:SE:LP:AF:SS:ID   0.025469:0.0402:0.278694:0.173931:2109:rs4475691
1   846864  rs950122    G   C   .   PASS    AF=0.150594 ES:SE:LP:AF:SS:ID   -0.021459:0.04937:0.177941:0.150594:3277:rs950122
1   854250  rs7537756   A   G   .   PASS    AF=0.184096 ES:SE:LP:AF:SS:ID   0.007043:0.059925:0.0426676:0.184096:919:rs7537756
1   861808  rs13302982  A   G   .   PASS    AF=0.966812 ES:SE:LP:AF:SS:ID   0.17112:0.13126:0.715962:0.966812:919:rs13302982
1   873558  rs1110052   G   T   .   PASS    AF=0.711475 ES:SE:LP:AF:SS:ID   -0.001814:0.052201:0.0122176:0.711475:919:rs1110052
1   882033  rs2272756   G   A   .   PASS    AF=0.260797 ES:SE:LP:AF:SS:ID   0.00333:0.032049:0.0375241:0.260797:3277:rs2272756
1   888659  rs3748597   T   C   .   PASS    AF=0.946681 ES:SE:LP:AF:SS:ID   0.088976:0.10242:0.414552:0.946681:919:rs3748597
1   891945  rs13303106  A   G   .   PASS    AF=0.638194 ES:SE:LP:AF:SS:ID   0.019354:0.048119:0.162698:0.638194:919:rs13303106
1   894573  rs13303010  G   A   .   PASS    AF=0.894995 ES:SE:LP:AF:SS:ID   0.18457:0.07632:1.80657:0.894995:919:rs13303010
1   900505  rs28705211  G   C   .   PASS    AF=0.259845 ES:SE:LP:AF:SS:ID   0.008159:0.046854:0.0646212:0.259845:1190:rs28705211
1   903104  rs6696281   C   T   .   PASS    AF=0.043573 ES:SE:LP:AF:SS:ID   -0.21242:0.11442:1.19795:0.043573:919:rs6696281
1   910935  rs2340592   G   A   .   PASS    AF=0.203176 ES:SE:LP:AF:SS:ID   -0.10332:0.057965:1.12678:0.203176:919:rs2340592
1   918384  rs13303118  G   T   .   PASS    AF=0.553097 ES:SE:LP:AF:SS:ID   0.001024:0.031435:0.0114397:0.553097:2109:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.566401 ES:SE:LP:AF:SS:ID   0.038905:0.039198:0.493594:0.566401:2070:rs2341354
1   924898  rs6665000   C   A   .   PASS    AF=0.970076 ES:SE:LP:AF:SS:ID   -0.02039:0.13272:0.0565639:0.970076:919:rs6665000
1   926431  rs4970403   A   T   .   PASS    AF=0.977379 ES:SE:LP:AF:SS:ID   0.080827:0.16487:0.204828:0.977379:919:rs4970403
1   927309  rs2341362   T   C   .   PASS    AF=0.970044 ES:SE:LP:AF:SS:ID   -0.020486:0.1328:0.0568098:0.970044:919:rs2341362
1   928836  rs9777703   C   T   .   PASS    AF=0.972276 ES:SE:LP:AF:SS:ID   -0.199181:0.09264:1.5007:0.972276:2109:rs9777703
1   932457  rs1891910   G   A   .   PASS    AF=0.23395  ES:SE:LP:AF:SS:ID   0.015323:0.054464:0.10877:0.23395:919:rs1891910
1   940203  rs35940137  G   A   .   PASS    AF=0.06148  ES:SE:LP:AF:SS:ID   0.005905:0.094836:0.0221246:0.06148:919:rs35940137
1   944564  rs3128117   T   C   .   PASS    AF=0.447225 ES:SE:LP:AF:SS:ID   -0.03394:0.046249:0.334373:0.447225:919:rs3128117
1   947034  rs2465126   G   A   .   PASS    AF=0.971708 ES:SE:LP:AF:SS:ID   0.057841:0.13599:0.173528:0.971708:919:rs2465126
1   948692  rs2341365   G   A   .   PASS    AF=0.968988 ES:SE:LP:AF:SS:ID   0.10724:0.13068:0.385251:0.968988:919:rs2341365
1   948921  rs15842 T   C   .   PASS    AF=0.972131 ES:SE:LP:AF:SS:ID   0.069137:0.13731:0.211388:0.972131:919:rs15842
1   959842  rs2710888   C   T   .   PASS    AF=0.401961 ES:SE:LP:AF:SS:ID   -0.073632:0.048093:0.900485:0.401961:919:rs2710888
1   962210  rs3128126   A   G   .   PASS    AF=0.442189 ES:SE:LP:AF:SS:ID   -0.011005:0.02246:0.204691:0.442189:7975:rs3128126
1   977780  rs2710875   C   T   .   PASS    AF=0.918934 ES:SE:LP:AF:SS:ID   -0.10738:0.08347:0.702752:0.918934:919:rs2710875
1   990380  rs3121561   C   T   .   PASS    AF=0.277228 ES:SE:LP:AF:SS:ID   -0.016412:0.021944:0.34243:0.277228:7975:rs3121561
1   990417  rs2465136   T   C   .   PASS    AF=0.318825 ES:SE:LP:AF:SS:ID   -0.070573:0.050794:0.783317:0.318825:919:rs2465136