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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_41210_J439.vcf.gz --id UKB-b:676 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41210_J439.txt.gz --cohort_cases 1029 --cohort_controls 461981 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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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/public/UKB-b-676/UKB-b-676_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-676/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-676/UKB-b-676_data.vcf.gz ...
Read summary statistics for 1425565 SNPs.
Dropped 118 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 368870 SNPs remain.
After merging with regression SNP LD, 368870 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0008 (0.0014)
Lambda GC: 1.0195
Mean Chi^2: 1.0262
Intercept: 1.0174 (0.0113)
Ratio: 0.6631 (0.4316)
Analysis finished at Thu Oct 17 14:40:38 2019
Total time elapsed: 20.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.5725,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 3.3055e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 11356,
    "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": 368870,
    "ldsc_nsnp_merge_regression_ld": 368870,
    "ldsc_observed_scale_h2_beta": 0.0008,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0174,
    "ldsc_intercept_se": 0.0113,
    "ldsc_lambda_gc": 1.0195,
    "ldsc_mean_chisq": 1.0262,
    "ldsc_ratio": 0.6641
}

Flags

name value
af_correlation TRUE
inflation_factor FALSE
n TRUE
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 TRUE
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 0 1.000000 4 58 0 1425449 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 1425565 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.676828e+00 5.768780e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.853706e+07 5.655249e+07 1.23330e+04 3.166828e+07 6.902424e+07 1.144885e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 3.000000e-07 1.017000e-04 -5.24400e-04 -6.770000e-05 8.000000e-07 6.920000e-05 4.650000e-04 ▁▁▇▃▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.001000e-04 2.600000e-06 9.44000e-05 9.850000e-05 9.960000e-05 1.013000e-04 1.867000e-04 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.949561e-01 2.901221e-01 5.00000e-07 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.949553e-01 2.901021e-01 5.00000e-07 2.415088e-01 4.941361e-01 7.461794e-01 9.999995e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 4.835153e-01 9.181650e-02 3.40137e-01 4.027060e-01 4.753180e-01 5.598280e-01 6.598630e-01 ▇▇▆▆▅
numeric AF_reference 11356 0.992034 NA NA NA NA NA NA NA 4.614914e-01 1.431917e-01 1.99700e-04 3.546330e-01 4.558710e-01 5.636980e-01 1.000000e+00 ▁▆▇▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C 0.0000276 0.0001738 0.8700001 0.8738444 0.623765 0.782149 NA
1 54676 rs2462492 C T -0.0000690 0.0001722 0.6899999 0.6887532 0.400401 NA NA
1 91536 rs6702460 G T 0.0000140 0.0001695 0.9299999 0.9339706 0.456846 0.420727 NA
1 706368 rs55727773 A G -0.0001548 0.0001202 0.2000000 0.1978719 0.515645 0.275160 NA
1 814495 rs74461805 C A -0.0001122 0.0001648 0.5000000 0.4960507 0.340396 NA NA
1 840753 rs4970382 T C -0.0000331 0.0000999 0.7400005 0.7400502 0.400124 0.468850 NA
1 843405 rs11516185 A G -0.0000667 0.0001240 0.5900000 0.5908693 0.362606 0.375399 NA
1 850218 rs6664536 T A 0.0000542 0.0000996 0.5900000 0.5865275 0.590331 0.345248 NA
1 850371 rs6679046 G T 0.0000701 0.0001002 0.4799997 0.4840795 0.603723 0.508786 NA
1 850780 rs6657440 C T 0.0000650 0.0001001 0.5199996 0.5166047 0.603942 0.560304 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51158017 rs6010065 G C -0.0003647 0.0000982 0.0002000 0.0002033 0.461411 0.547524 NA
22 51158499 rs8136930 T G -0.0003702 0.0000983 0.0001700 0.0001652 0.461636 0.544728 NA
22 51161019 rs5770994 C T 0.0002585 0.0000980 0.0083000 0.0083342 0.482204 0.425719 NA
22 51163039 rs715584 G T -0.0003665 0.0000995 0.0002300 0.0002298 0.426975 0.473642 NA
22 51164109 rs5770995 G C -0.0003644 0.0000989 0.0002300 0.0002286 0.452705 0.510982 NA
22 51164115 rs5770996 C T -0.0003731 0.0000988 0.0001600 0.0001599 0.456917 0.514776 NA
22 51174048 rs9628245 G C -0.0000971 0.0001117 0.3800004 0.3844654 0.380135 0.433107 NA
22 51186143 rs2879914 T C -0.0001596 0.0001052 0.1299999 0.1293523 0.381825 0.273363 NA
22 51186228 rs3865766 C T -0.0001967 0.0001026 0.0549997 0.0551155 0.451061 0.453275 NA
22 51197266 rs61290853 A G -0.0002237 0.0001059 0.0350002 0.0346909 0.386333 0.422923 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  2.75958e-05:0.000173802:0.0604807:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -6.89679e-05:0.000172184:0.161151:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  1.40461e-05:0.000169536:0.0315171:0.456846:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000154796:0.000120217:0.69897:0.515645:rs12029736
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  -0.000112208:0.000164838:0.30103:0.340396:rs74461805
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  -3.31415e-05:9.98879e-05:0.130768:0.400124:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362606 ES:SE:LP:AF:ID  -6.66579e-05:0.000123997:0.229148:0.362606:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590331 ES:SE:LP:AF:ID  5.41681e-05:9.95966e-05:0.229148:0.590331:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603723 ES:SE:LP:AF:ID  7.00841e-05:0.000100155:0.318759:0.603723:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603942 ES:SE:LP:AF:ID  6.49509e-05:0.000100142:0.283997:0.603942:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589686 ES:SE:LP:AF:ID  5.65092e-05:9.97585e-05:0.244125:0.589686:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589665 ES:SE:LP:AF:ID  5.54561e-05:9.97137e-05:0.236572:0.589665:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607671 ES:SE:LP:AF:ID  5.38704e-05:0.000100365:0.229148:0.607671:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607829 ES:SE:LP:AF:ID  5.42696e-05:0.000100379:0.229148:0.607829:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610316 ES:SE:LP:AF:ID  6.48281e-05:0.000100478:0.283997:0.610316:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603283 ES:SE:LP:AF:ID  7.37263e-05:0.00010018:0.337242:0.603283:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610337 ES:SE:LP:AF:ID  6.44849e-05:0.000100479:0.283997:0.610337:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389936 ES:SE:LP:AF:ID  -6.03763e-05:0.000100499:0.259637:0.389936:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.38992  ES:SE:LP:AF:ID  -6.03867e-05:0.000100504:0.259637:0.38992:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350356 ES:SE:LP:AF:ID  -1.08691e-05:0.000103246:0.0362122:0.350356:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.610552 ES:SE:LP:AF:ID  5.35331e-05:0.000101043:0.221849:0.610552:rs2880024
1   875770  rs4970379   A   G   .   PASS    AF=0.600085 ES:SE:LP:AF:ID  0.000138947:0.000101883:0.769551:0.600085:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.652393 ES:SE:LP:AF:ID  4.72155e-05:0.00010292:0.187087:0.652393:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.652432 ES:SE:LP:AF:ID  5.1788e-05:0.000102904:0.21467:0.652432:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.652494 ES:SE:LP:AF:ID  5.08656e-05:0.000103024:0.207608:0.652494:rs13303106
1   903245  rs28690976  A   G   .   PASS    AF=0.566938 ES:SE:LP:AF:ID  0.00017082:0.000102325:1.02228:0.566938:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386681 ES:SE:LP:AF:ID  0.000160632:0.000102047:0.920819:0.386681:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.571408 ES:SE:LP:AF:ID  0.000126593:9.88295e-05:0.69897:0.571408:rs3829740
1   912049  rs7367995   T   C   .   PASS    AF=0.585249 ES:SE:LP:AF:ID  0.000118633:9.98313e-05:0.638272:0.585249:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.59921  ES:SE:LP:AF:ID  8.94892e-05:9.99935e-05:0.431798:0.59921:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.602516 ES:SE:LP:AF:ID  7.01877e-05:0.000100296:0.318759:0.602516:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.600074 ES:SE:LP:AF:ID  7.96922e-05:0.000100104:0.366532:0.600074:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.584289 ES:SE:LP:AF:ID  0.000117839:9.95428e-05:0.619789:0.584289:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.589102 ES:SE:LP:AF:ID  0.0001038:9.96948e-05:0.522879:0.589102:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.584202 ES:SE:LP:AF:ID  0.00011959:9.9496e-05:0.638272:0.584202:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.589327 ES:SE:LP:AF:ID  0.000104111:9.96183e-05:0.522879:0.589327:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.583926 ES:SE:LP:AF:ID  0.00010582:0.000103022:0.522879:0.583926:rs4970414
1   921716  rs13303278  C   A   .   PASS    AF=0.567888 ES:SE:LP:AF:ID  0.000169686:9.94127e-05:1.05552:0.567888:rs13303278
1   924528  rs34712273  C   A   .   PASS    AF=0.578491 ES:SE:LP:AF:ID  0.000172939:9.96979e-05:1.08092:0.578491:rs34712273
1   930533  rs3128110   C   G   .   PASS    AF=0.386082 ES:SE:LP:AF:ID  -0.000168734:0.000100971:1.02228:0.386082:rs3128110
1   930567  rs3121574   A   G   .   PASS    AF=0.386124 ES:SE:LP:AF:ID  -0.000169194:0.000100973:1.02687:0.386124:rs3121574
1   930751  rs3128111   C   G   .   PASS    AF=0.385079 ES:SE:LP:AF:ID  -0.000169127:0.000101035:1.02687:0.385079:rs3128111
1   931166  rs2710880   A   G   .   PASS    AF=0.386765 ES:SE:LP:AF:ID  -0.000161244:0.00010099:0.958607:0.386765:rs2710880
1   931362  rs2799060   G   A   .   PASS    AF=0.385571 ES:SE:LP:AF:ID  -0.000163848:0.000101039:1:0.385571:rs2799060
1   933790  rs9442392   G   A   .   PASS    AF=0.578604 ES:SE:LP:AF:ID  0.000194408:9.96639e-05:1.29243:0.578604:rs9442392
1   936111  rs1936360   C   T   .   PASS    AF=0.573545 ES:SE:LP:AF:ID  0.000211276:9.964e-05:1.46852:0.573545:rs1936360
1   940005  rs2799056   A   G   .   PASS    AF=0.399264 ES:SE:LP:AF:ID  -0.000190371:0.000100621:1.23657:0.399264:rs2799056
1   940096  rs4503294   C   T   .   PASS    AF=0.565308 ES:SE:LP:AF:ID  0.000229593:9.9355e-05:1.67778:0.565308:rs4503294
1   941284  rs3128116   C   T   .   PASS    AF=0.397398 ES:SE:LP:AF:ID  -0.00019717:0.000100643:1.30103:0.397398:rs3128116
1   941334  rs57683598  G   A   .   PASS    AF=0.397402 ES:SE:LP:AF:ID  -0.000196706:0.000100649:1.29243:0.397402:rs57683598