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-17999/UKB-b-17999_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17999/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17999/UKB-b-17999_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: 0.0431 (0.0021)
Lambda GC: 1.3045
Mean Chi^2: 1.3616
Intercept: 1.034 (0.0075)
Ratio: 0.0941 (0.0207)
Analysis finished at Thu Oct 17 14:42:04 2019
Total time elapsed: 1.0m:46.64s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0.0004,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 12,
    "n_p_sig": 370,
    "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": 0.0431,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.034,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.3045,
    "ldsc_mean_chisq": 1.3616,
    "ldsc_ratio": 0.094
}

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 TRUE
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 3.583000e-04 1.467110e-02 -0.3076110 -4.538800e-03 7.250000e-05 4.781700e-03 2.364060e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.014190e-02 9.590400e-03 0.0028389 3.475700e-03 5.828400e-03 1.344830e-02 1.487350e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.678733e-01 2.975210e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.678746e-01 2.974974e-01 0.0000000 2.023370e-01 4.567183e-01 7.255496e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035087e-01 2.568569e-01 0.0009570 1.317200e-02 7.791700e-02 3.164648e-01 9.990230e-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 -0.0009452 0.0052200 0.8600001 0.8563101 0.623774 0.7821490 NA
1 54676 rs2462492 C T -0.0030142 0.0051761 0.5600000 0.5603460 0.400434 NA NA
1 86028 rs114608975 T C 0.0205501 0.0082564 0.0129999 0.0128111 0.103684 0.0277556 NA
1 91536 rs6702460 G T -0.0091767 0.0050971 0.0719996 0.0717999 0.456776 0.4207270 NA
1 234313 rs8179466 C T 0.0101042 0.0100799 0.3200000 0.3161453 0.074356 NA NA
1 534192 rs6680723 C T 0.0013776 0.0058191 0.8100000 0.8128556 0.241087 NA NA
1 546697 rs12025928 A G -0.0082718 0.0072624 0.2500000 0.2547089 0.913454 NA NA
1 693731 rs12238997 A G -0.0050357 0.0048807 0.2999998 0.3021838 0.116141 0.1417730 NA
1 705882 rs72631875 G A -0.0096695 0.0071620 0.1800002 0.1769836 0.067125 0.0315495 NA
1 706368 rs55727773 A G 0.0013101 0.0036140 0.7199992 0.7169810 0.515579 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0020930 0.0075842 0.7800007 0.7825683 0.041991 0.0473243 NA
22 51219766 rs182321900 C T -0.0161758 0.0353738 0.6499995 0.6474684 0.001934 NA NA
22 51220146 rs868950473 C T -0.0225285 0.0350714 0.5199996 0.5206388 0.001980 NA NA
22 51221190 rs369304721 G A -0.0056514 0.0075664 0.4600002 0.4551211 0.049838 NA NA
22 51221731 rs115055839 T C -0.0028408 0.0056620 0.6200004 0.6158593 0.073353 0.0625000 NA
22 51222100 rs114553188 G T 0.0005715 0.0066846 0.9299999 0.9318712 0.054224 0.0880591 NA
22 51223637 rs375798137 G A 0.0007758 0.0067172 0.9100000 0.9080468 0.053851 0.0788738 NA
22 51229805 rs9616985 T C -0.0024115 0.0056820 0.6700003 0.6712667 0.073191 0.0730831 NA
22 51232488 rs376461333 A G -0.0080322 0.0134042 0.5500004 0.5490210 0.019990 NA NA
22 51237063 rs3896457 T C -0.0015825 0.0034803 0.6499995 0.6493124 0.297667 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623774 ES:SE:LP:AF:ID  -0.000945204:0.00522001:0.0655015:0.623774:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400434 ES:SE:LP:AF:ID  -0.00301418:0.00517609:0.251812:0.400434:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103684 ES:SE:LP:AF:ID  0.0205501:0.00825644:1.88606:0.103684:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456776 ES:SE:LP:AF:ID  -0.00917674:0.0050971:1.14267:0.456776:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074356 ES:SE:LP:AF:ID  0.0101042:0.0100799:0.49485:0.074356:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241087 ES:SE:LP:AF:ID  0.00137764:0.00581912:0.091515:0.241087:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913454 ES:SE:LP:AF:ID  -0.00827183:0.00726245:0.60206:0.913454:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116141 ES:SE:LP:AF:ID  -0.00503574:0.00488072:0.522879:0.116141:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067125 ES:SE:LP:AF:ID  -0.00966949:0.00716205:0.744727:0.067125:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515579 ES:SE:LP:AF:ID  0.00131007:0.00361402:0.142668:0.515579:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03306  ES:SE:LP:AF:ID  0.0145099:0.0091001:0.958607:0.03306:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036667 ES:SE:LP:AF:ID  0.0161082:0.00826873:1.29243:0.036667:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036785 ES:SE:LP:AF:ID  0.0155628:0.00823743:1.22915:0.036785:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036483 ES:SE:LP:AF:ID  0.0146177:0.0082971:1.10791:0.036483:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016425 ES:SE:LP:AF:ID  0.00510246:0.012773:0.161151:0.016425:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037034 ES:SE:LP:AF:ID  0.0153059:0.00820336:1.20761:0.037034:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037131 ES:SE:LP:AF:ID  0.0148709:0.00817574:1.16115:0.037131:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101204 ES:SE:LP:AF:ID  -0.00177267:0.00596062:0.113509:0.101204:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958969 ES:SE:LP:AF:ID  -0.0145973:0.00788164:1.19382:0.958969:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03151  ES:SE:LP:AF:ID  0.0117657:0.014274:0.387216:0.03151:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053153 ES:SE:LP:AF:ID  -0.00143521:0.0114321:0.0457575:0.053153:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036654 ES:SE:LP:AF:ID  0.0152016:0.00822821:1.18709:0.036654:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036964 ES:SE:LP:AF:ID  0.0143199:0.008154:1.10237:0.036964:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84326  ES:SE:LP:AF:ID  7.23215e-05:0.00422731:0.00436481:0.84326:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055758 ES:SE:LP:AF:ID  -0.0087005:0.0068551:0.69897:0.055758:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122201 ES:SE:LP:AF:ID  -0.003274:0.00462824:0.318759:0.122201:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025695 ES:SE:LP:AF:ID  0.0138575:0.0113967:0.657577:0.025695:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121449 ES:SE:LP:AF:ID  -0.00317064:0.0046298:0.309804:0.121449:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132222 ES:SE:LP:AF:ID  -0.0013409:0.00456353:0.113509:0.132222:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011122 ES:SE:LP:AF:ID  0.0192915:0.0165926:0.619789:0.011122:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.00573  ES:SE:LP:AF:ID  0.00248514:0.0213422:0.0409586:0.00573:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002314 ES:SE:LP:AF:ID  0.00153417:0.0356021:0.0132283:0.002314:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001059 ES:SE:LP:AF:ID  0.0733206:0.0578271:0.69897:0.001059:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036888 ES:SE:LP:AF:ID  0.0139232:0.00807025:1.07572:0.036888:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838952 ES:SE:LP:AF:ID  0.000315716:0.00409201:0.0268721:0.838952:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838576 ES:SE:LP:AF:ID  0.000380708:0.00408761:0.0315171:0.838576:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869778 ES:SE:LP:AF:ID  0.00201749:0.00438661:0.187087:0.869778:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12987  ES:SE:LP:AF:ID  -0.00211719:0.00439567:0.200659:0.12987:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037375 ES:SE:LP:AF:ID  0.0120716:0.00793646:0.886057:0.037375:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037629 ES:SE:LP:AF:ID  0.0114796:0.00788483:0.823909:0.037629:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  0.00203683:0.00437773:0.19382:0.869104:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869197 ES:SE:LP:AF:ID  0.00206291:0.00437939:0.19382:0.869197:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037581 ES:SE:LP:AF:ID  0.0122419:0.00792016:0.920819:0.037581:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  0.00201836:0.00437766:0.19382:0.869106:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005134 ES:SE:LP:AF:ID  -0.0298429:0.0224811:0.744727:0.005134:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005099 ES:SE:LP:AF:ID  -0.0304422:0.0225429:0.744727:0.005099:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838026 ES:SE:LP:AF:ID  0.000304937:0.00407637:0.0268721:0.838026:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037598 ES:SE:LP:AF:ID  0.012181:0.00793059:0.920819:0.037598:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838658 ES:SE:LP:AF:ID  0.000134427:0.0040877:0.0132283:0.838658:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013735 ES:SE:LP:AF:ID  -0.00698162:0.0142953:0.200659:0.013735:rs181660517