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-14180/UKB-b-14180_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14180/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14180/UKB-b-14180_data.vcf.gz ...
Read summary statistics for 9515294 SNPs.
Dropped 11746 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, 1288398 SNPs remain.
After merging with regression SNP LD, 1288398 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.068 (0.0027)
Lambda GC: 1.4806
Mean Chi^2: 1.6448
Intercept: 1.0319 (0.0094)
Ratio: 0.0494 (0.0145)
Analysis finished at Thu Oct 17 14:45:09 2019
Total time elapsed: 1.0m:49.71s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9491,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 57,
    "n_p_sig": 6655,
    "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": 135054,
    "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": 1288398,
    "ldsc_nsnp_merge_regression_ld": 1288398,
    "ldsc_observed_scale_h2_beta": 0.068,
    "ldsc_observed_scale_h2_se": 0.0027,
    "ldsc_intercept_beta": 1.0319,
    "ldsc_intercept_se": 0.0094,
    "ldsc_lambda_gc": 1.4806,
    "ldsc_mean_chisq": 1.6448,
    "ldsc_ratio": 0.0495
}

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 9503608 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 9515294 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 8.629072e+00 5.751619e+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 7.883405e+07 5.630757e+07 828.0000000 3.254007e+07 6.941997e+07 1.145674e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.780000e-05 4.429300e-03 -0.0573836 -1.659000e-03 2.310000e-05 1.704400e-03 6.990590e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.195100e-03 2.689500e-03 0.0010056 1.217300e-03 1.967100e-03 4.344100e-03 3.502920e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.527762e-01 3.017153e-01 0.0000000 1.800002e-01 4.400003e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.527758e-01 3.016905e-01 0.0000000 1.788911e-01 4.362213e-01 7.140461e-01 9.999994e-01 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.095309e-01 2.572952e-01 0.0017130 1.566200e-02 8.651800e-02 3.278760e-01 9.982870e-01 ▇▂▁▁▁
numeric AF_reference 135054 0.9858066 NA NA NA NA NA NA NA 2.112688e-01 2.490077e-01 0.0000000 1.337860e-02 1.062300e-01 3.292730e-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 0.0010918 0.0018492 0.5500004 0.5549027 0.623726 0.7821490 NA
1 54676 rs2462492 C T -0.0028913 0.0018315 0.1100001 0.1144265 0.400485 NA NA
1 86028 rs114608975 T C -0.0007125 0.0029288 0.8100000 0.8078041 0.103554 0.0277556 NA
1 91536 rs6702460 G T -0.0013240 0.0018040 0.4600002 0.4630017 0.456835 0.4207270 NA
1 234313 rs8179466 C T -0.0023690 0.0035576 0.5099998 0.5054839 0.074491 NA NA
1 534192 rs6680723 C T -0.0001958 0.0020606 0.9199999 0.9243063 0.240985 NA NA
1 546697 rs12025928 A G 0.0012731 0.0025695 0.6200004 0.6202740 0.913405 NA NA
1 693731 rs12238997 A G -0.0001290 0.0017267 0.9400001 0.9404273 0.116304 0.1417730 NA
1 705882 rs72631875 G A 0.0016424 0.0025306 0.5199996 0.5163069 0.067310 0.0315495 NA
1 706368 rs55727773 A G -0.0004957 0.0012791 0.6999999 0.6983769 0.515772 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0030831 0.0026870 0.2500000 0.2512128 0.041941 0.0473243 NA
22 51219766 rs182321900 C T -0.0091744 0.0125914 0.4700002 0.4662301 0.001919 NA NA
22 51220146 rs868950473 C T -0.0046464 0.0124800 0.7099994 0.7096632 0.001965 NA NA
22 51221190 rs369304721 G A 0.0015227 0.0026827 0.5700002 0.5702966 0.049713 NA NA
22 51221731 rs115055839 T C -0.0000571 0.0020063 0.9800000 0.9772868 0.073225 0.0625000 NA
22 51222100 rs114553188 G T 0.0024852 0.0023621 0.2900000 0.2927526 0.054430 0.0880591 NA
22 51223637 rs375798137 G A 0.0023588 0.0023736 0.3200000 0.3203395 0.054057 0.0788738 NA
22 51229805 rs9616985 T C -0.0000296 0.0020135 0.9900000 0.9882715 0.073061 0.0730831 NA
22 51232488 rs376461333 A G 0.0057656 0.0047474 0.2200002 0.2245659 0.020019 NA NA
22 51237063 rs3896457 T C -0.0008447 0.0012313 0.4899999 0.4926946 0.297946 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623726 ES:SE:LP:AF:ID  0.00109184:0.00184923:0.259637:0.623726:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400485 ES:SE:LP:AF:ID  -0.00289128:0.00183154:0.958607:0.400485:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103554 ES:SE:LP:AF:ID  -0.000712452:0.00292877:0.091515:0.103554:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456835 ES:SE:LP:AF:ID  -0.00132395:0.00180396:0.337242:0.456835:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074491 ES:SE:LP:AF:ID  -0.00236897:0.00355762:0.29243:0.074491:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240985 ES:SE:LP:AF:ID  -0.000195781:0.00206062:0.0362122:0.240985:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913405 ES:SE:LP:AF:ID  0.00127308:0.00256948:0.207608:0.913405:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116304 ES:SE:LP:AF:ID  -0.000129039:0.00172667:0.0268721:0.116304:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06731  ES:SE:LP:AF:ID  0.00164245:0.00253055:0.283997:0.06731:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515772 ES:SE:LP:AF:ID  -0.000495671:0.00127911:0.154902:0.515772:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033027 ES:SE:LP:AF:ID  0.0021675:0.00322342:0.30103:0.033027:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036638 ES:SE:LP:AF:ID  0.00211631:0.00292847:0.327902:0.036638:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036748 ES:SE:LP:AF:ID  0.00225237:0.00291767:0.356547:0.036748:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036449 ES:SE:LP:AF:ID  0.00240036:0.00293858:0.387216:0.036449:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016408 ES:SE:LP:AF:ID  0.00252904:0.00452554:0.236572:0.016408:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036989 ES:SE:LP:AF:ID  0.0021708:0.00290606:0.337242:0.036989:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037083 ES:SE:LP:AF:ID  0.00225168:0.0028962:0.356547:0.037083:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101222 ES:SE:LP:AF:ID  0.001214:0.00211003:0.244125:0.101222:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959096 ES:SE:LP:AF:ID  -0.000761708:0.00279382:0.102373:0.959096:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031457 ES:SE:LP:AF:ID  0.00723506:0.00506822:0.823909:0.031457:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  0.00317897:0.00403323:0.366532:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036602 ES:SE:LP:AF:ID  0.00225278:0.00291487:0.356547:0.036602:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036919 ES:SE:LP:AF:ID  0.00199718:0.00288834:0.309804:0.036919:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843263 ES:SE:LP:AF:ID  0.000118955:0.00149671:0.0268721:0.843263:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055912 ES:SE:LP:AF:ID  0.000279254:0.00242272:0.0409586:0.055912:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122273 ES:SE:LP:AF:ID  -0.000512487:0.00163803:0.124939:0.122273:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025729 ES:SE:LP:AF:ID  0.00326291:0.00402742:0.376751:0.025729:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121514 ES:SE:LP:AF:ID  -0.000329179:0.00163874:0.0757207:0.121514:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132293 ES:SE:LP:AF:ID  -0.000502854:0.00161523:0.119186:0.132293:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011134 ES:SE:LP:AF:ID  0.00122449:0.00586992:0.0809219:0.011134:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005696 ES:SE:LP:AF:ID  -0.0124166:0.0075831:1:0.005696:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002261 ES:SE:LP:AF:ID  -0.00128411:0.0127796:0.0362122:0.002261:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036835 ES:SE:LP:AF:ID  0.00240737:0.002859:0.39794:0.036835:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838979 ES:SE:LP:AF:ID  -0.000575186:0.00144937:0.161151:0.838979:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838607 ES:SE:LP:AF:ID  -0.000284586:0.00144779:0.0757207:0.838607:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869795 ES:SE:LP:AF:ID  -8.85085e-05:0.00155338:0.0222764:0.869795:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129857 ES:SE:LP:AF:ID  -0.000175223:0.00155654:0.0409586:0.129857:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037348 ES:SE:LP:AF:ID  0.00217277:0.00281053:0.356547:0.037348:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037591 ES:SE:LP:AF:ID  0.00220561:0.00279276:0.366532:0.037591:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86914  ES:SE:LP:AF:ID  0.000112407:0.00155035:0.0268721:0.86914:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869241 ES:SE:LP:AF:ID  0.00010957:0.00155097:0.0268721:0.869241:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037551 ES:SE:LP:AF:ID  0.00235515:0.00280478:0.39794:0.037551:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869143 ES:SE:LP:AF:ID  0.000116614:0.00155032:0.0268721:0.869143:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005139 ES:SE:LP:AF:ID  -0.000234265:0.0079455:0.00877392:0.005139:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005105 ES:SE:LP:AF:ID  0.000420229:0.0079662:0.0177288:0.005105:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838062 ES:SE:LP:AF:ID  -0.000480651:0.00144381:0.130768:0.838062:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037566 ES:SE:LP:AF:ID  0.00228153:0.0028087:0.376751:0.037566:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838695 ES:SE:LP:AF:ID  -0.000519624:0.00144787:0.142668:0.838695:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.0138   ES:SE:LP:AF:ID  0.00768048:0.00504808:0.886057:0.0138:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005548 ES:SE:LP:AF:ID  -4.56006e-05:0.00779282:-0:0.005548:rs184270342