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-20432/UKB-b-20432_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20432/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20432/UKB-b-20432_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: 0.0259 (0.0022)
Lambda GC: 1.1728
Mean Chi^2: 1.2098
Intercept: 1.0094 (0.0089)
Ratio: 0.0449 (0.0424)
Analysis finished at Thu Oct 17 14:43:57 2019
Total time elapsed: 1.0m:45.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 119,
    "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": 0.0259,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0094,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.1728,
    "ldsc_mean_chisq": 1.2098,
    "ldsc_ratio": 0.0448
}

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 1.519000e-04 9.276400e-03 -0.1422070 -2.827400e-03 2.570000e-05 2.881400e-03 2.178790e-01 ▁▇▃▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.524200e-03 6.170500e-03 0.0018257 2.235700e-03 3.749100e-03 8.650700e-03 9.615770e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.813574e-01 2.942687e-01 0.0000000 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.813586e-01 2.942434e-01 0.0000000 2.216406e-01 4.752812e-01 7.365261e-01 1.000000e+00 ▇▇▇▇▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035086e-01 2.568579e-01 0.0009540 1.317100e-02 7.791500e-02 3.164588e-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 -0.0021445 0.0033576 0.5199996 0.5230222 0.623757 0.7821490 NA
1 54676 rs2462492 C T -0.0038768 0.0033301 0.2399999 0.2443493 0.400340 NA NA
1 86028 rs114608975 T C -0.0011704 0.0053107 0.8300000 0.8255706 0.103703 0.0277556 NA
1 91536 rs6702460 G T -0.0053980 0.0032792 0.1000000 0.0997405 0.456708 0.4207270 NA
1 234313 rs8179466 C T 0.0062301 0.0064829 0.3400001 0.3365458 0.074378 NA NA
1 534192 rs6680723 C T 0.0013239 0.0037440 0.7199992 0.7236282 0.241078 NA NA
1 546697 rs12025928 A G 0.0008680 0.0046702 0.8499999 0.8525535 0.913417 NA NA
1 693731 rs12238997 A G -0.0037307 0.0031404 0.2300001 0.2348394 0.116120 0.1417730 NA
1 705882 rs72631875 G A -0.0017423 0.0046041 0.7099994 0.7051188 0.067169 0.0315495 NA
1 706368 rs55727773 A G 0.0012334 0.0023248 0.5999997 0.5957507 0.515610 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0069628 0.0048826 0.1499999 0.1538517 0.041907 0.0473243 NA
22 51219766 rs182321900 C T 0.0275993 0.0228045 0.2300001 0.2261804 0.001925 NA NA
22 51220146 rs868950473 C T 0.0268806 0.0225931 0.2300001 0.2341367 0.001973 NA NA
22 51221190 rs369304721 G A -0.0056986 0.0048690 0.2399999 0.2418486 0.049784 NA NA
22 51221731 rs115055839 T C -0.0042645 0.0036433 0.2399999 0.2418018 0.073264 0.0625000 NA
22 51222100 rs114553188 G T -0.0028506 0.0042982 0.5099998 0.5071930 0.054240 0.0880591 NA
22 51223637 rs375798137 G A -0.0026624 0.0043191 0.5400003 0.5376140 0.053870 0.0788738 NA
22 51229805 rs9616985 T C -0.0043784 0.0036562 0.2300001 0.2311002 0.073102 0.0730831 NA
22 51232488 rs376461333 A G -0.0114352 0.0086194 0.1800002 0.1846135 0.020001 NA NA
22 51237063 rs3896457 T C 0.0054364 0.0022383 0.0150000 0.0151470 0.297687 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623757 ES:SE:LP:AF:ID  -0.00214451:0.00335765:0.283997:0.623757:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40034  ES:SE:LP:AF:ID  -0.00387685:0.0033301:0.619789:0.40034:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103703 ES:SE:LP:AF:ID  -0.00117041:0.00531073:0.0809219:0.103703:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456708 ES:SE:LP:AF:ID  -0.005398:0.00327924:1:0.456708:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074378 ES:SE:LP:AF:ID  0.00623011:0.00648286:0.468521:0.074378:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241078 ES:SE:LP:AF:ID  0.00132392:0.00374397:0.142668:0.241078:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913417 ES:SE:LP:AF:ID  0.000868006:0.00467018:0.0705811:0.913417:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11612  ES:SE:LP:AF:ID  -0.0037307:0.00314036:0.638272:0.11612:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067169 ES:SE:LP:AF:ID  -0.00174229:0.00460412:0.148742:0.067169:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51561  ES:SE:LP:AF:ID  0.00123335:0.00232479:0.221849:0.51561:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033056 ES:SE:LP:AF:ID  0.000822669:0.00585406:0.05061:0.033056:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036661 ES:SE:LP:AF:ID  0.00205972:0.00531966:0.154902:0.036661:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036777 ES:SE:LP:AF:ID  0.00197858:0.00529974:0.148742:0.036777:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036477 ES:SE:LP:AF:ID  0.00148293:0.00533796:0.107905:0.036477:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016419 ES:SE:LP:AF:ID  0.00232146:0.00821816:0.107905:0.016419:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037031 ES:SE:LP:AF:ID  0.00215202:0.00527748:0.167491:0.037031:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037128 ES:SE:LP:AF:ID  0.00197831:0.00525969:0.148742:0.037128:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  6.04147e-05:0.00383492:0.00436481:0.101206:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958984 ES:SE:LP:AF:ID  -0.00376925:0.00507095:0.337242:0.958984:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031498 ES:SE:LP:AF:ID  -0.00924066:0.00918731:0.508638:0.031498:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053171 ES:SE:LP:AF:ID  -0.00211328:0.00734851:0.113509:0.053171:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036641 ES:SE:LP:AF:ID  0.00219783:0.00529447:0.167491:0.036641:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036955 ES:SE:LP:AF:ID  0.000716876:0.00524621:0.05061:0.036955:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84333  ES:SE:LP:AF:ID  0.00134079:0.00272004:0.207608:0.84333:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055761 ES:SE:LP:AF:ID  -0.000283798:0.00440979:0.0222764:0.055761:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122155 ES:SE:LP:AF:ID  -0.00207245:0.00297827:0.309804:0.122155:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025687 ES:SE:LP:AF:ID  0.00496963:0.0073302:0.30103:0.025687:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.1214   ES:SE:LP:AF:ID  -0.0024135:0.00297932:0.376751:0.1214:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132156 ES:SE:LP:AF:ID  -0.00368597:0.00293631:0.677781:0.132156:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011098 ES:SE:LP:AF:ID  0.0072959:0.0106878:0.309804:0.011098:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005724 ES:SE:LP:AF:ID  -0.00344118:0.01374:0.09691:0.005724:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002304 ES:SE:LP:AF:ID  0.0172571:0.0229506:0.346787:0.002304:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001056 ES:SE:LP:AF:ID  -0.00630576:0.0372789:0.0604807:0.001056:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036882 ES:SE:LP:AF:ID  0.00173271:0.00519206:0.130768:0.036882:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838998 ES:SE:LP:AF:ID  0.0021385:0.00263287:0.376751:0.838998:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838626 ES:SE:LP:AF:ID  0.00183222:0.00263014:0.309804:0.838626:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869811 ES:SE:LP:AF:ID  0.00222327:0.00282267:0.366532:0.869811:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129839 ES:SE:LP:AF:ID  -0.00234677:0.00282858:0.387216:0.129839:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037372 ES:SE:LP:AF:ID  0.000743974:0.00510582:0.0555173:0.037372:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037624 ES:SE:LP:AF:ID  0.000311496:0.00507278:0.0222764:0.037624:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869139 ES:SE:LP:AF:ID  0.00188838:0.00281703:0.30103:0.869139:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869233 ES:SE:LP:AF:ID  0.00197116:0.0028181:0.318759:0.869233:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037578 ES:SE:LP:AF:ID  0.000333904:0.00509527:0.0222764:0.037578:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869143 ES:SE:LP:AF:ID  0.00182417:0.00281699:0.283997:0.869143:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005146 ES:SE:LP:AF:ID  -0.00604067:0.0144459:0.167491:0.005146:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00511  ES:SE:LP:AF:ID  -0.00602106:0.0144856:0.167491:0.00511:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838074 ES:SE:LP:AF:ID  0.00160524:0.00262281:0.267606:0.838074:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037595 ES:SE:LP:AF:ID  0.0004039:0.00510195:0.0268721:0.037595:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838701 ES:SE:LP:AF:ID  0.00150077:0.00263008:0.244125:0.838701:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013723 ES:SE:LP:AF:ID  0.00394288:0.00920108:0.173925:0.013723:rs181660517