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/public/UKB-b-5445/UKB-b-5445_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5445/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:20 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5445/UKB-b-5445_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0105 (0.0013)
Lambda GC: 1.1299
Mean Chi^2: 1.1365
Intercept: 1.0434 (0.0063)
Ratio: 0.3179 (0.0464)
Analysis finished at Thu Oct 17 14:46:56 2019
Total time elapsed: 1.0m:35.88s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 13,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.0105,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0434,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.1299,
    "ldsc_mean_chisq": 1.1365,
    "ldsc_ratio": 0.3179
}

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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.339000e-04 7.166600e-03 -0.1019970 -2.140200e-03 2.280000e-05 2.224400e-03 1.809550e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.072300e-03 4.801500e-03 0.0014192 1.737500e-03 2.913500e-03 6.722800e-03 7.458300e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.857253e-01 2.928341e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.857264e-01 2.928089e-01 0.0000000 2.279526e-01 4.807348e-01 7.394403e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035075e-01 2.568623e-01 0.0009880 1.317000e-02 7.791300e-02 3.164548e-01 9.990090e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 0.0004261 0.0026116 0.8700001 0.8703970 0.623779 0.7821490 NA
1 54676 rs2462492 C T 0.0006546 0.0025872 0.8000000 0.8002621 0.400422 NA NA
1 86028 rs114608975 T C -0.0011403 0.0041368 0.7800007 0.7828260 0.103533 0.0277556 NA
1 91536 rs6702460 G T 0.0027643 0.0025476 0.2800000 0.2778860 0.456907 0.4207270 NA
1 234313 rs8179466 C T 0.0092374 0.0050230 0.0659994 0.0659119 0.074501 NA NA
1 534192 rs6680723 C T -0.0027506 0.0029104 0.3400001 0.3446179 0.240941 NA NA
1 546697 rs12025928 A G -0.0007638 0.0036294 0.8300000 0.8333108 0.913459 NA NA
1 693731 rs12238997 A G -0.0015709 0.0024388 0.5199996 0.5194982 0.116303 0.1417730 NA
1 705882 rs72631875 G A -0.0033524 0.0035735 0.3500000 0.3481827 0.067279 0.0315495 NA
1 706368 rs55727773 A G 0.0021321 0.0018064 0.2399999 0.2378800 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0029214 0.0037896 0.4400003 0.4407663 0.041972 0.0473243 NA
22 51219766 rs182321900 C T -0.0056392 0.0176401 0.7499995 0.7492104 0.001941 NA NA
22 51220146 rs868950473 C T -0.0027567 0.0174734 0.8700001 0.8746398 0.001991 NA NA
22 51221190 rs369304721 G A -0.0043503 0.0037839 0.2500000 0.2502659 0.049734 NA NA
22 51221731 rs115055839 T C -0.0022450 0.0028301 0.4299995 0.4276442 0.073242 0.0625000 NA
22 51222100 rs114553188 G T 0.0072979 0.0033323 0.0290001 0.0285222 0.054455 0.0880591 NA
22 51223637 rs375798137 G A 0.0075638 0.0033484 0.0239999 0.0238904 0.054085 0.0788738 NA
22 51229805 rs9616985 T C -0.0018482 0.0028404 0.5199996 0.5152406 0.073077 0.0730831 NA
22 51232488 rs376461333 A G 0.0157952 0.0066905 0.0179999 0.0182338 0.020045 NA NA
22 51237063 rs3896457 T C -0.0041165 0.0017375 0.0179999 0.0178272 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623779 ES:SE:LP:AF:ID  0.000426087:0.00261156:0.0604807:0.623779:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400422 ES:SE:LP:AF:ID  0.000654587:0.00258722:0.09691:0.400422:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103533 ES:SE:LP:AF:ID  -0.00114026:0.0041368:0.107905:0.103533:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456907 ES:SE:LP:AF:ID  0.00276434:0.00254759:0.552842:0.456907:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074501 ES:SE:LP:AF:ID  0.00923739:0.00502299:1.18046:0.074501:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240941 ES:SE:LP:AF:ID  -0.00275059:0.00291043:0.468521:0.240941:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913459 ES:SE:LP:AF:ID  -0.000763823:0.00362935:0.0809219:0.913459:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116303 ES:SE:LP:AF:ID  -0.00157091:0.00243885:0.283997:0.116303:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067279 ES:SE:LP:AF:ID  -0.00335241:0.00357354:0.455932:0.067279:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  0.00213211:0.00180641:0.619789:0.515645:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033013 ES:SE:LP:AF:ID  -0.00202899:0.00455345:0.180456:0.033013:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036635 ES:SE:LP:AF:ID  -0.000761743:0.00413578:0.0705811:0.036635:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036749 ES:SE:LP:AF:ID  -0.00132442:0.00412023:0.124939:0.036749:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03645  ES:SE:LP:AF:ID  -0.000554018:0.00414986:0.05061:0.03645:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016402 ES:SE:LP:AF:ID  -0.00300869:0.00639194:0.19382:0.016402:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036989 ES:SE:LP:AF:ID  -0.000761861:0.00410386:0.0705811:0.036989:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037088 ES:SE:LP:AF:ID  -0.000541037:0.00408971:0.05061:0.037088:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101237 ES:SE:LP:AF:ID  -0.00164695:0.00297955:0.236572:0.101237:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959087 ES:SE:LP:AF:ID  -0.000101691:0.00394512:0.00877392:0.959087:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031452 ES:SE:LP:AF:ID  0.00757857:0.00716135:0.537602:0.031452:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05326  ES:SE:LP:AF:ID  0.00577193:0.00569677:0.508638:0.05326:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036608 ES:SE:LP:AF:ID  -0.000872454:0.004116:0.0809219:0.036608:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036926 ES:SE:LP:AF:ID  -0.00126707:0.00407845:0.119186:0.036926:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843217 ES:SE:LP:AF:ID  0.00171987:0.00211357:0.376751:0.843217:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05591  ES:SE:LP:AF:ID  -0.00526116:0.00342215:0.920819:0.05591:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122287 ES:SE:LP:AF:ID  -0.00213103:0.00231352:0.443698:0.122287:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025722 ES:SE:LP:AF:ID  0.000357903:0.00568861:0.0222764:0.025722:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121529 ES:SE:LP:AF:ID  -0.0024065:0.00231451:0.522879:0.121529:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132335 ES:SE:LP:AF:ID  -0.00213521:0.0022809:0.455932:0.132335:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  0.0014177:0.00829455:0.0655015:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005705 ES:SE:LP:AF:ID  0.00807515:0.0106983:0.346787:0.005705:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00227  ES:SE:LP:AF:ID  0.017326:0.0180028:0.468521:0.00227:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001027 ES:SE:LP:AF:ID  -0.0169758:0.029537:0.244125:0.001027:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036838 ES:SE:LP:AF:ID  -0.000372706:0.00403744:0.0315171:0.036838:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838936 ES:SE:LP:AF:ID  0.00124367:0.00204676:0.267606:0.838936:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838565 ES:SE:LP:AF:ID  0.00117178:0.00204456:0.244125:0.838565:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869783 ES:SE:LP:AF:ID  0.00145675:0.00219396:0.29243:0.869783:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129863 ES:SE:LP:AF:ID  -0.00172295:0.00219845:0.366532:0.129863:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037348 ES:SE:LP:AF:ID  -0.000438003:0.00396906:0.0409586:0.037348:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037592 ES:SE:LP:AF:ID  -0.000656402:0.00394397:0.0604807:0.037592:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  0.00140075:0.00218965:0.283997:0.869126:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869222 ES:SE:LP:AF:ID  0.00148835:0.00219052:0.30103:0.869222:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  -0.000668968:0.00396101:0.0604807:0.03755:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869128 ES:SE:LP:AF:ID  0.00142217:0.00218961:0.283997:0.869128:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005128 ES:SE:LP:AF:ID  0.00916255:0.0112333:0.387216:0.005128:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005094 ES:SE:LP:AF:ID  0.00960866:0.0112627:0.408935:0.005094:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838017 ES:SE:LP:AF:ID  0.001122:0.00203887:0.236572:0.838017:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037564 ES:SE:LP:AF:ID  -0.000379897:0.00396659:0.0362122:0.037564:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838649 ES:SE:LP:AF:ID  0.00114193:0.00204461:0.236572:0.838649:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013767 ES:SE:LP:AF:ID  0.00378754:0.0071379:0.221849:0.013767:rs181660517