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_3404.vcf.gz --id UKB-b:16118 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_3404.txt.gz --cohort_cases 72887 --cohort_controls 32509 --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-16118/UKB-b-16118_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16118/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:49 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16118/UKB-b-16118_data.vcf.gz ...
Read summary statistics for 8756062 SNPs.
Dropped 7742 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, 1286214 SNPs remain.
After merging with regression SNP LD, 1286214 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0275 (0.0053)
Lambda GC: 1.0611
Mean Chi^2: 1.0634
Intercept: 1.0059 (0.007)
Ratio: 0.0926 (0.1098)
Analysis finished at Thu Oct 17 14:46:12 2019
Total time elapsed: 1.0m:23.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9468,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "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": 85725,
    "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": 1286214,
    "ldsc_nsnp_merge_regression_ld": 1286214,
    "ldsc_observed_scale_h2_beta": 0.0275,
    "ldsc_observed_scale_h2_se": 0.0053,
    "ldsc_intercept_beta": 1.0059,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0611,
    "ldsc_mean_chisq": 1.0634,
    "ldsc_ratio": 0.0931
}

Flags

name value
af_correlation FALSE
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 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 8748357 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 8756062 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 8.650078e+00 5.760866e+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 7.876950e+07 5.635415e+07 828.0000000 3.239698e+07 6.931183e+07 1.145565e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.440000e-05 6.158700e-03 -0.0667219 -2.546400e-03 7.000000e-06 2.539100e-03 6.701330e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.019600e-03 3.506300e-03 0.0019336 2.288600e-03 3.417800e-03 6.826900e-03 3.503260e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.927157e-01 2.906105e-01 0.0000001 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.927163e-01 2.905843e-01 0.0000001 2.394849e-01 4.896045e-01 7.448690e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.259597e-01 2.591718e-01 0.0048020 2.350920e-02 1.095020e-01 3.571850e-01 9.951970e-01 ▇▂▁▁▁
numeric AF_reference 85725 0.9902096 NA NA NA NA NA NA NA 2.258360e-01 2.511375e-01 0.0000000 2.116610e-02 1.263980e-01 3.544330e-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 -0.0012228 0.0035524 0.7300002 0.7306859 0.622281 0.7821490 NA
1 54676 rs2462492 C T -0.0028990 0.0035191 0.4100001 0.4100497 0.400662 NA NA
1 86028 rs114608975 T C 0.0030978 0.0056016 0.5800000 0.5802476 0.104004 0.0277556 NA
1 91536 rs6702460 G T 0.0008679 0.0034710 0.8000000 0.8025538 0.456051 0.4207270 NA
1 234313 rs8179466 C T -0.0089432 0.0068064 0.1900002 0.1888697 0.074657 NA NA
1 534192 rs6680723 C T -0.0007819 0.0039654 0.8400000 0.8436817 0.240840 NA NA
1 546697 rs12025928 A G 0.0022491 0.0049869 0.6499995 0.6519895 0.913943 NA NA
1 693731 rs12238997 A G 0.0001704 0.0033355 0.9599999 0.9592627 0.115302 0.1417730 NA
1 705882 rs72631875 G A -0.0024172 0.0048771 0.6200004 0.6201616 0.067076 0.0315495 NA
1 706368 rs55727773 A G 0.0003220 0.0024550 0.9000000 0.8956513 0.515831 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0009886 0.0029637 0.7400005 0.7386938 0.138253 0.2052720 NA
22 51219387 rs9616832 T C 0.0028042 0.0038351 0.4600002 0.4646669 0.074355 0.0654952 NA
22 51219704 rs147475742 G A -0.0007187 0.0051382 0.8900000 0.8887641 0.042222 0.0473243 NA
22 51221190 rs369304721 G A 0.0030025 0.0051480 0.5600000 0.5597392 0.050024 NA NA
22 51221731 rs115055839 T C 0.0034485 0.0038366 0.3700002 0.3687382 0.073868 0.0625000 NA
22 51222100 rs114553188 G T -0.0025169 0.0045536 0.5800000 0.5804493 0.054199 0.0880591 NA
22 51223637 rs375798137 G A -0.0021120 0.0045738 0.6400000 0.6442547 0.053853 0.0788738 NA
22 51229805 rs9616985 T C 0.0031286 0.0038496 0.4199997 0.4163844 0.073739 0.0730831 NA
22 51232488 rs376461333 A G 0.0028750 0.0092595 0.7600007 0.7561896 0.019706 NA NA
22 51237063 rs3896457 T C 0.0025791 0.0023746 0.2800000 0.2774224 0.297104 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.622281 ES:SE:LP:AF:ID  -0.00122278:0.00355239:0.136677:0.622281:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400662 ES:SE:LP:AF:ID  -0.00289904:0.00351908:0.387216:0.400662:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104004 ES:SE:LP:AF:ID  0.00309782:0.00560161:0.236572:0.104004:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456051 ES:SE:LP:AF:ID  0.000867908:0.00347103:0.09691:0.456051:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074657 ES:SE:LP:AF:ID  -0.00894316:0.00680642:0.721246:0.074657:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24084  ES:SE:LP:AF:ID  -0.000781927:0.00396542:0.0757207:0.24084:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913943 ES:SE:LP:AF:ID  0.00224911:0.00498694:0.187087:0.913943:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115302 ES:SE:LP:AF:ID  0.000170372:0.00333547:0.0177288:0.115302:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067076 ES:SE:LP:AF:ID  -0.0024172:0.00487711:0.207608:0.067076:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515831 ES:SE:LP:AF:ID  0.000321995:0.00245504:0.0457575:0.515831:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03248  ES:SE:LP:AF:ID  -0.00269318:0.00625331:0.173925:0.03248:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036009 ES:SE:LP:AF:ID  -0.00154227:0.00568572:0.102373:0.036009:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036093 ES:SE:LP:AF:ID  -0.00155707:0.0056671:0.107905:0.036093:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035793 ES:SE:LP:AF:ID  -0.00178508:0.00570963:0.124939:0.035793:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016117 ES:SE:LP:AF:ID  0.00332237:0.00876648:0.154902:0.016117:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036345 ES:SE:LP:AF:ID  -0.00210955:0.00564339:0.148742:0.036345:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036444 ES:SE:LP:AF:ID  -0.0021765:0.00562298:0.154902:0.036444:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100925 ES:SE:LP:AF:ID  -0.00601281:0.004065:0.853872:0.100925:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959604 ES:SE:LP:AF:ID  0.00458236:0.00541072:0.39794:0.959604:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031551 ES:SE:LP:AF:ID  -0.0106287:0.00970439:0.568636:0.031551:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053616 ES:SE:LP:AF:ID  0.0238272:0.00773095:2.67778:0.053616:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.035922 ES:SE:LP:AF:ID  -0.00215096:0.00566564:0.154902:0.035922:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036241 ES:SE:LP:AF:ID  -0.00187391:0.00561268:0.130768:0.036241:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.844811 ES:SE:LP:AF:ID  0.00122895:0.00289078:0.173925:0.844811:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055518 ES:SE:LP:AF:ID  0.00132197:0.00468026:0.107905:0.055518:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121162 ES:SE:LP:AF:ID  5.15321e-05:0.00316634:0.00436481:0.121162:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.026101 ES:SE:LP:AF:ID  0.0111327:0.00769083:0.823909:0.026101:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.120437 ES:SE:LP:AF:ID  0.000223931:0.0031669:0.0268721:0.120437:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.130939 ES:SE:LP:AF:ID  -0.000260829:0.00312229:0.0315171:0.130939:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.010889 ES:SE:LP:AF:ID  -0.00878946:0.0114063:0.356547:0.010889:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005822 ES:SE:LP:AF:ID  1.30597e-05:0.0144334:-0:0.005822:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036184 ES:SE:LP:AF:ID  -0.00172402:0.00554929:0.119186:0.036184:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.840483 ES:SE:LP:AF:ID  0.00117754:0.00279903:0.173925:0.840483:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.840109 ES:SE:LP:AF:ID  0.00123344:0.00279559:0.180456:0.840109:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.870688 ES:SE:LP:AF:ID  0.00101208:0.00300008:0.130768:0.870688:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.128935 ES:SE:LP:AF:ID  -0.00100527:0.00300728:0.130768:0.128935:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036731 ES:SE:LP:AF:ID  -0.00186679:0.0054526:0.136677:0.036731:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.036976 ES:SE:LP:AF:ID  -0.0019443:0.0054181:0.142668:0.036976:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870054 ES:SE:LP:AF:ID  0.00127744:0.00299434:0.173925:0.870054:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870154 ES:SE:LP:AF:ID  0.00119869:0.00299536:0.161151:0.870154:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.036939 ES:SE:LP:AF:ID  -0.0019553:0.00544058:0.142668:0.036939:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.87005  ES:SE:LP:AF:ID  0.00121742:0.00299427:0.167491:0.87005:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005055 ES:SE:LP:AF:ID  -0.0117706:0.015431:0.346787:0.005055:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005021 ES:SE:LP:AF:ID  -0.013179:0.0154746:0.408935:0.005021:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.839587 ES:SE:LP:AF:ID  0.00159932:0.00278891:0.244125:0.839587:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.036925 ES:SE:LP:AF:ID  -0.0018333:0.0054502:0.130768:0.036925:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.84021  ES:SE:LP:AF:ID  0.00154021:0.00279667:0.236572:0.84021:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.014084 ES:SE:LP:AF:ID  0.00533842:0.00962703:0.236572:0.014084:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.00552  ES:SE:LP:AF:ID  0.0138002:0.0150389:0.443698:0.00552:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.8412   ES:SE:LP:AF:ID  0.001226:0.00283379:0.173925:0.8412:rs3131965