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-2094/UKB-b-2094_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2094/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:15 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2094/UKB-b-2094_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: 0.0103 (0.0011)
Lambda GC: 1.1275
Mean Chi^2: 1.1282
Intercept: 1.0386 (0.0072)
Ratio: 0.3008 (0.056)
Analysis finished at Thu Oct 17 14:44:06 2019
Total time elapsed: 1.0m:50.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 27,
    "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": 0.0103,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0386,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.1275,
    "ldsc_mean_chisq": 1.1282,
    "ldsc_ratio": 0.3011
}

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 1.156000e-04 6.635500e-03 -0.1181760 -1.959700e-03 2.560000e-05 2.042400e-03 1.018940e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.662800e-03 4.414300e-03 0.0013045 1.597100e-03 2.678200e-03 6.179800e-03 6.845600e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.856603e-01 2.920953e-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 4.856606e-01 2.920685e-01 0.0000000 2.290618e-01 4.805011e-01 7.381957e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035074e-01 2.568628e-01 0.0009850 1.316800e-02 7.791400e-02 3.164540e-01 9.990130e-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 0.0049100 0.0024007 0.0409996 0.0408332 0.623738 0.7821490 NA
1 54676 rs2462492 C T -0.0003717 0.0023778 0.8800001 0.8757741 0.400479 NA NA
1 86028 rs114608975 T C -0.0006472 0.0038020 0.8600001 0.8648350 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0019064 0.0023417 0.4199997 0.4156000 0.456872 0.4207270 NA
1 234313 rs8179466 C T 0.0030987 0.0046201 0.5000000 0.5024169 0.074483 NA NA
1 534192 rs6680723 C T -0.0045539 0.0026749 0.0890000 0.0886701 0.240960 NA NA
1 546697 rs12025928 A G 0.0022864 0.0033364 0.4899999 0.4931637 0.913443 NA NA
1 693731 rs12238997 A G -0.0033712 0.0022411 0.1299999 0.1325158 0.116394 0.1417730 NA
1 705882 rs72631875 G A -0.0004239 0.0032856 0.9000000 0.8973431 0.067248 0.0315495 NA
1 706368 rs55727773 A G 0.0038330 0.0016603 0.0210000 0.0209666 0.515586 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0056764 0.0034849 0.1000000 0.1033426 0.041952 0.0473243 NA
22 51219766 rs182321900 C T 0.0000296 0.0162688 1.0000000 0.9985498 0.001932 NA NA
22 51220146 rs868950473 C T -0.0009200 0.0161094 0.9500000 0.9544563 0.001981 NA NA
22 51221190 rs369304721 G A 0.0040585 0.0034792 0.2399999 0.2434195 0.049720 NA NA
22 51221731 rs115055839 T C 0.0027742 0.0026021 0.2900000 0.2863664 0.073227 0.0625000 NA
22 51222100 rs114553188 G T 0.0031938 0.0030635 0.2999998 0.2971769 0.054460 0.0880591 NA
22 51223637 rs375798137 G A 0.0034418 0.0030784 0.2599998 0.2635462 0.054088 0.0788738 NA
22 51229805 rs9616985 T C 0.0030932 0.0026114 0.2399999 0.2362253 0.073063 0.0730831 NA
22 51232488 rs376461333 A G 0.0078817 0.0061541 0.2000000 0.2002938 0.020039 NA NA
22 51237063 rs3896457 T C 0.0017480 0.0015970 0.2700001 0.2737021 0.297981 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623738 ES:SE:LP:AF:ID  0.00491002:0.00240073:1.38722:0.623738:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400479 ES:SE:LP:AF:ID  -0.000371724:0.00237784:0.0555173:0.400479:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  -0.000647192:0.00380203:0.0655015:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456872 ES:SE:LP:AF:ID  0.00190636:0.00234174:0.376751:0.456872:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074483 ES:SE:LP:AF:ID  0.00309869:0.00462014:0.30103:0.074483:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -0.00455388:0.00267489:1.05061:0.24096:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913443 ES:SE:LP:AF:ID  0.00228638:0.00333639:0.309804:0.913443:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116394 ES:SE:LP:AF:ID  -0.00337123:0.00224113:0.886057:0.116394:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067248 ES:SE:LP:AF:ID  -0.000423899:0.00328557:0.0457575:0.067248:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515586 ES:SE:LP:AF:ID  0.00383299:0.00166032:1.67778:0.515586:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032973 ES:SE:LP:AF:ID  0.00613493:0.00418815:0.853872:0.032973:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036589 ES:SE:LP:AF:ID  0.00535836:0.00380398:0.79588:0.036589:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036706 ES:SE:LP:AF:ID  0.00527651:0.0037895:0.79588:0.036706:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036403 ES:SE:LP:AF:ID  0.00537427:0.00381693:0.79588:0.036403:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016422 ES:SE:LP:AF:ID  -2.20179e-05:0.00587267:-0:0.016422:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036941 ES:SE:LP:AF:ID  0.00548037:0.00377466:0.823909:0.036941:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037036 ES:SE:LP:AF:ID  0.00549867:0.00376179:0.853872:0.037036:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101205 ES:SE:LP:AF:ID  -0.000722032:0.0027394:0.102373:0.101205:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959128 ES:SE:LP:AF:ID  -0.00324339:0.00362803:0.431798:0.959128:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03145  ES:SE:LP:AF:ID  0.00688753:0.0065857:0.522879:0.03145:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053244 ES:SE:LP:AF:ID  0.002852:0.00523674:0.229148:0.053244:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036556 ES:SE:LP:AF:ID  0.0050249:0.0037861:0.744727:0.036556:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03687  ES:SE:LP:AF:ID  0.0048478:0.0037517:0.69897:0.03687:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843185 ES:SE:LP:AF:ID  0.00121385:0.00194269:0.275724:0.843185:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055962 ES:SE:LP:AF:ID  -0.00355779:0.00314371:0.585027:0.055962:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122368 ES:SE:LP:AF:ID  -0.0028303:0.00212611:0.744727:0.122368:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025715 ES:SE:LP:AF:ID  -0.00227878:0.00522977:0.180456:0.025715:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121611 ES:SE:LP:AF:ID  -0.00281237:0.00212699:0.721246:0.121611:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132347 ES:SE:LP:AF:ID  -0.00070377:0.00209649:0.130768:0.132347:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011124 ES:SE:LP:AF:ID  0.00182549:0.00762692:0.091515:0.011124:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005711 ES:SE:LP:AF:ID  -0.0216574:0.00983008:1.55284:0.005711:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002267 ES:SE:LP:AF:ID  -0.00298812:0.0165521:0.0655015:0.002267:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001025 ES:SE:LP:AF:ID  -0.0365669:0.0271725:0.744727:0.001025:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036786 ES:SE:LP:AF:ID  0.00518283:0.00371375:0.79588:0.036786:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838901 ES:SE:LP:AF:ID  0.00160403:0.00188136:0.408935:0.838901:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83853  ES:SE:LP:AF:ID  0.0016887:0.00187935:0.431798:0.83853:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869693 ES:SE:LP:AF:ID  0.00380222:0.00201634:1.22915:0.869693:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129954 ES:SE:LP:AF:ID  -0.00387309:0.00202045:1.25964:0.129954:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.0373   ES:SE:LP:AF:ID  0.00413427:0.00365062:0.585027:0.0373:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037543 ES:SE:LP:AF:ID  0.00420165:0.00362758:0.60206:0.037543:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869038 ES:SE:LP:AF:ID  0.00390466:0.0020124:1.284:0.869038:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869136 ES:SE:LP:AF:ID  0.00390176:0.00201318:1.27572:0.869136:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037503 ES:SE:LP:AF:ID  0.00426783:0.00364317:0.619789:0.037503:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86904  ES:SE:LP:AF:ID  0.00390916:0.00201235:1.284:0.86904:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005132 ES:SE:LP:AF:ID  -0.00137642:0.010325:0.05061:0.005132:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005098 ES:SE:LP:AF:ID  -0.00162694:0.0103522:0.0555173:0.005098:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837984 ES:SE:LP:AF:ID  0.00189868:0.00187413:0.508638:0.837984:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  0.00401808:0.00364838:0.568636:0.037514:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838615 ES:SE:LP:AF:ID  0.00194385:0.00187941:0.522879:0.838615:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013763 ES:SE:LP:AF:ID  -0.00909986:0.00656451:0.769551:0.013763:rs181660517