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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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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_20154.vcf.gz --id UKB-b:13405 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20154.txt.gz --cohort_controls 148653 --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-13405/UKB-b-13405_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13405/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13405/UKB-b-13405_data.vcf.gz ...
Read summary statistics for 9294495 SNPs.
Dropped 10292 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, 1287895 SNPs remain.
After merging with regression SNP LD, 1287895 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1867 (0.0079)
Lambda GC: 1.434
Mean Chi^2: 1.607
Intercept: 1.0521 (0.0084)
Ratio: 0.0859 (0.0138)
Analysis finished at Thu Oct 17 14:44:06 2019
Total time elapsed: 1.0m:36.88s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9484,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 88,
    "n_p_sig": 13240,
    "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": 112794,
    "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": 1287895,
    "ldsc_nsnp_merge_regression_ld": 1287895,
    "ldsc_observed_scale_h2_beta": 0.1867,
    "ldsc_observed_scale_h2_se": 0.0079,
    "ldsc_intercept_beta": 1.0521,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.434,
    "ldsc_mean_chisq": 1.607,
    "ldsc_ratio": 0.0858
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 9284254 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9294495 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 8.634415e+00 5.753956e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.881294e+07 5.630963e+07 828.0000000 3.250548e+07 6.939352e+07 1.145423e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.820000e-05 1.371990e-02 -0.1708390 -5.490900e-03 -4.170000e-05 5.407400e-03 2.509140e-01 ▁▅▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.010810e-02 7.979400e-03 0.0033947 4.084100e-03 6.445100e-03 1.384820e-02 1.169210e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.566779e-01 3.011152e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.566784e-01 3.010899e-01 0.0000000 1.846598e-01 4.417756e-01 7.178780e-01 1.000000e+00 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.139035e-01 2.577953e-01 0.0023550 1.755200e-02 9.266600e-02 3.360455e-01 9.976450e-01 ▇▂▁▁▁
numeric AF_reference 112794 0.9878644 NA NA NA NA NA NA NA 2.148413e-01 2.496088e-01 0.0000000 1.477640e-02 1.110220e-01 3.358630e-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 -0.0025796 0.0062438 0.6800001 0.6794956 0.624076 0.7821490 NA
1 54676 rs2462492 C T 0.0002524 0.0061933 0.9699999 0.9674918 0.400879 NA NA
1 86028 rs114608975 T C -0.0070644 0.0099098 0.4799997 0.4759257 0.103399 0.0277556 NA
1 91536 rs6702460 G T -0.0041593 0.0060954 0.5000000 0.4950013 0.456786 0.4207270 NA
1 234313 rs8179466 C T 0.0087729 0.0120773 0.4700002 0.4675952 0.074382 NA NA
1 534192 rs6680723 C T -0.0069963 0.0069518 0.3100002 0.3142191 0.241045 NA NA
1 546697 rs12025928 A G 0.0045827 0.0087136 0.5999997 0.5989407 0.914079 NA NA
1 693731 rs12238997 A G -0.0071692 0.0058042 0.2200002 0.2167635 0.117190 0.1417730 NA
1 705882 rs72631875 G A 0.0029804 0.0085992 0.7300002 0.7289017 0.066512 0.0315495 NA
1 706368 rs55727773 A G 0.0030731 0.0043125 0.4799997 0.4760893 0.515316 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0000300 0.0052211 1.0000000 0.9954217 0.137964 0.2052720 NA
22 51219387 rs9616832 T C -0.0073119 0.0067957 0.2800000 0.2819487 0.073364 0.0654952 NA
22 51219704 rs147475742 G A -0.0082242 0.0091374 0.3700002 0.3680844 0.041407 0.0473243 NA
22 51221190 rs369304721 G A -0.0132141 0.0091148 0.1499999 0.1471312 0.049310 NA NA
22 51221731 rs115055839 T C -0.0070867 0.0068023 0.2999998 0.2974979 0.072842 0.0625000 NA
22 51222100 rs114553188 G T 0.0124221 0.0079635 0.1199999 0.1187898 0.054804 0.0880591 NA
22 51223637 rs375798137 G A 0.0119473 0.0080014 0.1400000 0.1353961 0.054445 0.0788738 NA
22 51229805 rs9616985 T C -0.0075869 0.0068274 0.2700001 0.2664664 0.072700 0.0730831 NA
22 51232488 rs376461333 A G 0.0133092 0.0159424 0.4000000 0.4038132 0.020229 NA NA
22 51237063 rs3896457 T C 0.0004195 0.0041546 0.9199999 0.9195685 0.297765 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624076 ES:SE:LP:AF:ID  -0.00257964:0.00624381:0.167491:0.624076:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400879 ES:SE:LP:AF:ID  0.000252404:0.00619332:0.0132283:0.400879:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103399 ES:SE:LP:AF:ID  -0.0070644:0.00990979:0.318759:0.103399:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456786 ES:SE:LP:AF:ID  -0.00415934:0.00609538:0.30103:0.456786:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074382 ES:SE:LP:AF:ID  0.00877292:0.0120773:0.327902:0.074382:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241045 ES:SE:LP:AF:ID  -0.0069963:0.00695175:0.508638:0.241045:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.914079 ES:SE:LP:AF:ID  0.00458269:0.00871359:0.221849:0.914079:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11719  ES:SE:LP:AF:ID  -0.00716922:0.00580419:0.657577:0.11719:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066512 ES:SE:LP:AF:ID  0.00298038:0.00859923:0.136677:0.066512:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515316 ES:SE:LP:AF:ID  0.00307313:0.00431252:0.318759:0.515316:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032412 ES:SE:LP:AF:ID  0.0129935:0.0109858:0.619789:0.032412:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03601  ES:SE:LP:AF:ID  0.00990884:0.00996578:0.49485:0.03601:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036115 ES:SE:LP:AF:ID  0.0100649:0.00993227:0.508638:0.036115:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035849 ES:SE:LP:AF:ID  0.0101345:0.00999756:0.508638:0.035849:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016325 ES:SE:LP:AF:ID  0.02106:0.0152961:0.769551:0.016325:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03634  ES:SE:LP:AF:ID  0.00969276:0.0098952:0.481486:0.03634:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036458 ES:SE:LP:AF:ID  0.0100449:0.00985686:0.508638:0.036458:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101473 ES:SE:LP:AF:ID  -0.0035735:0.0071057:0.207608:0.101473:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.960027 ES:SE:LP:AF:ID  -0.00769684:0.00953809:0.376751:0.960027:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031305 ES:SE:LP:AF:ID  0.00658028:0.0171823:0.154902:0.031305:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053038 ES:SE:LP:AF:ID  -0.0127331:0.0136392:0.455932:0.053038:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036011 ES:SE:LP:AF:ID  0.00928035:0.00991682:0.455932:0.036011:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036296 ES:SE:LP:AF:ID  0.00994996:0.00982814:0.508638:0.036296:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843279 ES:SE:LP:AF:ID  0.00334993:0.0050495:0.29243:0.843279:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056515 ES:SE:LP:AF:ID  -0.0160866:0.00814369:1.31876:0.056515:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1232   ES:SE:LP:AF:ID  -0.00876248:0.00550867:0.958607:0.1232:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02605  ES:SE:LP:AF:ID  -0.00164717:0.0134759:0.0457575:0.02605:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122477 ES:SE:LP:AF:ID  -0.00876332:0.00550969:0.958607:0.122477:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132727 ES:SE:LP:AF:ID  -0.00719051:0.00543976:0.721246:0.132727:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011138 ES:SE:LP:AF:ID  -0.0467649:0.0198025:1.74473:0.011138:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005704 ES:SE:LP:AF:ID  -0.0203523:0.0256211:0.366532:0.005704:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036239 ES:SE:LP:AF:ID  0.00794423:0.00972349:0.387216:0.036239:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839121 ES:SE:LP:AF:ID  0.00389808:0.00489169:0.366532:0.839121:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838841 ES:SE:LP:AF:ID  0.00374867:0.00488751:0.356547:0.838841:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869241 ES:SE:LP:AF:ID  0.00898047:0.00523588:1.0655:0.869241:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130397 ES:SE:LP:AF:ID  -0.00770758:0.00524576:0.853872:0.130397:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036689 ES:SE:LP:AF:ID  0.0088689:0.00956456:0.455932:0.036689:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.036929 ES:SE:LP:AF:ID  0.00863834:0.00950303:0.443698:0.036929:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868651 ES:SE:LP:AF:ID  0.00852505:0.00522632:1:0.868651:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868742 ES:SE:LP:AF:ID  0.00836224:0.00522791:0.958607:0.868742:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.036886 ES:SE:LP:AF:ID  0.00831002:0.00954588:0.420216:0.036886:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868653 ES:SE:LP:AF:ID  0.00862086:0.00522603:1.00436:0.868653:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005054 ES:SE:LP:AF:ID  0.000258538:0.0271365:0.00436481:0.005054:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00502  ES:SE:LP:AF:ID  0.0017949:0.0272063:0.0222764:0.00502:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838256 ES:SE:LP:AF:ID  0.00360239:0.0048752:0.337242:0.838256:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.036917 ES:SE:LP:AF:ID  0.00778581:0.00955639:0.376751:0.036917:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838878 ES:SE:LP:AF:ID  0.00367429:0.00488851:0.346787:0.838878:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013787 ES:SE:LP:AF:ID  -0.015594:0.0170914:0.443698:0.013787:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005476 ES:SE:LP:AF:ID  0.0172792:0.0264908:0.29243:0.005476:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839787 ES:SE:LP:AF:ID  0.00425781:0.00495294:0.408935:0.839787:rs3131965