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-19657/UKB-b-19657_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19657/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19657/UKB-b-19657_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: 0.1345 (0.0048)
Lambda GC: 1.8107
Mean Chi^2: 2.2716
Intercept: 1.1263 (0.0125)
Ratio: 0.0993 (0.0098)
Analysis finished at Thu Oct 17 14:43:12 2019
Total time elapsed: 1.0m:46.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.4921,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 260,
    "n_p_sig": 33126,
    "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": 0.1345,
    "ldsc_observed_scale_h2_se": 0.0048,
    "ldsc_intercept_beta": 1.1263,
    "ldsc_intercept_se": 0.0125,
    "ldsc_lambda_gc": 1.8107,
    "ldsc_mean_chisq": 2.2716,
    "ldsc_ratio": 0.0993
}

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 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 -2.960000e-05 8.985400e-03 -0.1225040 -3.195700e-03 -1.180000e-05 3.156700e-03 1.727490e-01 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.981600e-03 5.661500e-03 0.0016737 2.049100e-03 3.436100e-03 7.928200e-03 8.812450e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.314063e-01 3.065202e-01 0.0000000 1.499999e-01 4.100001e-01 6.999999e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.314066e-01 3.064975e-01 0.0000000 1.483778e-01 4.054252e-01 6.965695e-01 9.999998e-01 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035074e-01 2.568614e-01 0.0009700 1.317100e-02 7.791700e-02 3.164550e-01 9.990280e-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 -0.0002624 0.0030773 0.9299999 0.9320449 0.623818 0.7821490 NA
1 54676 rs2462492 C T 0.0037806 0.0030491 0.2200002 0.2150132 0.400348 NA NA
1 86028 rs114608975 T C -0.0064654 0.0048720 0.1800002 0.1844924 0.103530 0.0277556 NA
1 91536 rs6702460 G T -0.0011870 0.0030014 0.6899999 0.6924970 0.456816 0.4207270 NA
1 234313 rs8179466 C T -0.0031207 0.0059211 0.5999997 0.5981602 0.074514 NA NA
1 534192 rs6680723 C T -0.0049981 0.0034267 0.1400000 0.1446836 0.241002 NA NA
1 546697 rs12025928 A G 0.0023360 0.0042784 0.5900000 0.5850640 0.913453 NA NA
1 693731 rs12238997 A G -0.0052372 0.0028733 0.0680002 0.0683472 0.116293 0.1417730 NA
1 705882 rs72631875 G A 0.0004420 0.0042090 0.9199999 0.9163583 0.067315 0.0315495 NA
1 706368 rs55727773 A G 0.0023455 0.0021277 0.2700001 0.2703026 0.515391 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0050172 0.0044832 0.2599998 0.2630951 0.041858 0.0473243 NA
22 51219766 rs182321900 C T -0.0443428 0.0208638 0.0340001 0.0335577 0.001938 NA NA
22 51220146 rs868950473 C T -0.0422992 0.0206539 0.0409996 0.0405599 0.001990 NA NA
22 51221190 rs369304721 G A -0.0041800 0.0044728 0.3500000 0.3500210 0.049672 NA NA
22 51221731 rs115055839 T C -0.0022772 0.0033446 0.5000000 0.4959572 0.073178 0.0625000 NA
22 51222100 rs114553188 G T 0.0068110 0.0039366 0.0840001 0.0836037 0.054478 0.0880591 NA
22 51223637 rs375798137 G A 0.0067315 0.0039558 0.0890000 0.0888137 0.054109 0.0788738 NA
22 51229805 rs9616985 T C -0.0023205 0.0033570 0.4899999 0.4894089 0.073009 0.0730831 NA
22 51232488 rs376461333 A G 0.0140829 0.0078976 0.0749998 0.0745562 0.020066 NA NA
22 51237063 rs3896457 T C 0.0005495 0.0020539 0.7899998 0.7890566 0.297830 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623818 ES:SE:LP:AF:ID  -0.000262405:0.00307726:0.0315171:0.623818:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400348 ES:SE:LP:AF:ID  0.00378056:0.00304909:0.657577:0.400348:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10353  ES:SE:LP:AF:ID  -0.00646545:0.00487205:0.744727:0.10353:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456816 ES:SE:LP:AF:ID  -0.00118696:0.0030014:0.161151:0.456816:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074514 ES:SE:LP:AF:ID  -0.00312071:0.00592111:0.221849:0.074514:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241002 ES:SE:LP:AF:ID  -0.00499808:0.0034267:0.853872:0.241002:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913453 ES:SE:LP:AF:ID  0.00233604:0.00427844:0.229148:0.913453:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116293 ES:SE:LP:AF:ID  -0.00523725:0.00287333:1.16749:0.116293:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067315 ES:SE:LP:AF:ID  0.000442039:0.00420901:0.0362122:0.067315:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515391 ES:SE:LP:AF:ID  0.00234546:0.00212766:0.568636:0.515391:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033136 ES:SE:LP:AF:ID  0.00324861:0.00535658:0.267606:0.033136:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036768 ES:SE:LP:AF:ID  0.00249258:0.00486432:0.21467:0.036768:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03688  ES:SE:LP:AF:ID  0.00275665:0.00484612:0.244125:0.03688:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036579 ES:SE:LP:AF:ID  0.00278097:0.00488113:0.244125:0.036579:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016425 ES:SE:LP:AF:ID  0.00428174:0.00752446:0.244125:0.016425:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03712  ES:SE:LP:AF:ID  0.00277141:0.00482703:0.244125:0.03712:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037218 ES:SE:LP:AF:ID  0.00301887:0.00481045:0.275724:0.037218:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101307 ES:SE:LP:AF:ID  0.00369534:0.00350776:0.537602:0.101307:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958943 ES:SE:LP:AF:ID  -0.00259422:0.00463995:0.236572:0.958943:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031454 ES:SE:LP:AF:ID  0.0068469:0.00843542:0.376751:0.031454:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053203 ES:SE:LP:AF:ID  -0.00779456:0.00671548:0.60206:0.053203:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036742 ES:SE:LP:AF:ID  0.00305611:0.00484068:0.275724:0.036742:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  0.00356532:0.00479692:0.337242:0.037052:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843051 ES:SE:LP:AF:ID  0.00387959:0.00248869:0.920819:0.843051:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055965 ES:SE:LP:AF:ID  -0.00406858:0.00403028:0.508638:0.055965:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122305 ES:SE:LP:AF:ID  -0.005535:0.00272499:1.37675:0.122305:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025625 ES:SE:LP:AF:ID  0.00885934:0.0067177:0.721246:0.025625:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  -0.00564058:0.00272612:1.40894:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132464 ES:SE:LP:AF:ID  -0.00524594:0.00268562:1.29243:0.132464:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011121 ES:SE:LP:AF:ID  -0.00978573:0.00977865:0.49485:0.011121:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005657 ES:SE:LP:AF:ID  -0.0178183:0.0126612:0.79588:0.005657:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002294 ES:SE:LP:AF:ID  -0.0327588:0.0210555:0.920819:0.002294:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001028 ES:SE:LP:AF:ID  0.044047:0.0347931:0.677781:0.001028:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036972 ES:SE:LP:AF:ID  0.0025061:0.00474827:0.221849:0.036972:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838765 ES:SE:LP:AF:ID  0.00400825:0.00240974:1.01773:0.838765:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838403 ES:SE:LP:AF:ID  0.00397367:0.00240717:1.00436:0.838403:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869739 ES:SE:LP:AF:ID  0.00564768:0.00258392:1.5376:0.869739:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129875 ES:SE:LP:AF:ID  -0.0049436:0.00258938:1.25181:0.129875:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037489 ES:SE:LP:AF:ID  0.00139214:0.00466759:0.113509:0.037489:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037732 ES:SE:LP:AF:ID  0.00122609:0.00463818:0.102373:0.037732:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869094 ES:SE:LP:AF:ID  0.00530509:0.00257896:1.39794:0.869094:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869196 ES:SE:LP:AF:ID  0.00531102:0.00257998:1.39794:0.869196:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03769  ES:SE:LP:AF:ID  0.00132007:0.00465841:0.107905:0.03769:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869097 ES:SE:LP:AF:ID  0.00537135:0.00257888:1.4318:0.869097:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005137 ES:SE:LP:AF:ID  -0.00277275:0.013228:0.0809219:0.005137:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005104 ES:SE:LP:AF:ID  -0.00235738:0.0132615:0.0655015:0.005104:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837852 ES:SE:LP:AF:ID  0.00387139:0.00240042:0.958607:0.837852:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037707 ES:SE:LP:AF:ID  0.00132352:0.00466486:0.107905:0.037707:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838485 ES:SE:LP:AF:ID  0.00393424:0.00240718:1:0.838485:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013773 ES:SE:LP:AF:ID  0.0236534:0.00840854:2.3098:0.013773:rs181660517