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-17627/UKB-b-17627_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17627/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17627/UKB-b-17627_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: 0.027 (0.0016)
Lambda GC: 1.2407
Mean Chi^2: 1.2852
Intercept: 1.039 (0.0085)
Ratio: 0.1368 (0.0299)
Analysis finished at Thu Oct 17 14:42:05 2019
Total time elapsed: 1.0m:46.4s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 11,
    "n_p_sig": 929,
    "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": 0.027,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.039,
    "ldsc_intercept_se": 0.0085,
    "ldsc_lambda_gc": 1.2407,
    "ldsc_mean_chisq": 1.2852,
    "ldsc_ratio": 0.1367
}

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 2.040000e-05 7.981400e-03 -0.1156600 -2.511000e-03 -4.000000e-06 2.514100e-03 1.136220e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.587800e-03 5.289700e-03 0.0015635 1.914000e-03 3.209600e-03 7.405800e-03 8.215630e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.732039e-01 2.959570e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.732039e-01 2.959306e-01 0.0000000 2.106397e-01 4.639954e-01 7.290622e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035074e-01 2.568624e-01 0.0009870 1.316900e-02 7.791200e-02 3.164558e-01 9.990060e-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 -0.0013989 0.0028766 0.6300007 0.6267572 0.623748 0.7821490 NA
1 54676 rs2462492 C T 0.0027248 0.0028495 0.3400001 0.3389659 0.400441 NA NA
1 86028 rs114608975 T C 0.0047261 0.0045562 0.2999998 0.2996039 0.103554 0.0277556 NA
1 91536 rs6702460 G T 0.0000565 0.0028062 0.9800000 0.9839317 0.456870 0.4207270 NA
1 234313 rs8179466 C T -0.0044080 0.0055350 0.4299995 0.4258069 0.074485 NA NA
1 534192 rs6680723 C T 0.0002269 0.0032053 0.9400001 0.9435544 0.240970 NA NA
1 546697 rs12025928 A G -0.0028728 0.0039984 0.4700002 0.4724599 0.913476 NA NA
1 693731 rs12238997 A G -0.0009213 0.0026859 0.7300002 0.7315897 0.116349 0.1417730 NA
1 705882 rs72631875 G A 0.0021265 0.0039361 0.5900000 0.5890254 0.067288 0.0315495 NA
1 706368 rs55727773 A G -0.0000304 0.0019898 0.9900000 0.9878173 0.515663 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0020659 0.0041764 0.6200004 0.6208440 0.041950 0.0473243 NA
22 51219766 rs182321900 C T 0.0195930 0.0194894 0.3100002 0.3147449 0.001931 NA NA
22 51220146 rs868950473 C T 0.0189097 0.0193030 0.3300000 0.3272713 0.001980 NA NA
22 51221190 rs369304721 G A 0.0023401 0.0041701 0.5700002 0.5746816 0.049711 NA NA
22 51221731 rs115055839 T C 0.0018155 0.0031190 0.5600000 0.5605042 0.073211 0.0625000 NA
22 51222100 rs114553188 G T -0.0072423 0.0036711 0.0490004 0.0485192 0.054463 0.0880591 NA
22 51223637 rs375798137 G A -0.0068107 0.0036889 0.0649995 0.0648519 0.054092 0.0788738 NA
22 51229805 rs9616985 T C 0.0017653 0.0031302 0.5700002 0.5727808 0.073048 0.0730831 NA
22 51232488 rs376461333 A G -0.0062706 0.0073753 0.4000000 0.3951993 0.020032 NA NA
22 51237063 rs3896457 T C -0.0025534 0.0019143 0.1800002 0.1822569 0.297964 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623748 ES:SE:LP:AF:ID  -0.00139886:0.00287656:0.200659:0.623748:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400441 ES:SE:LP:AF:ID  0.00272476:0.00284954:0.468521:0.400441:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103554 ES:SE:LP:AF:ID  0.00472609:0.00455622:0.522879:0.103554:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45687  ES:SE:LP:AF:ID  5.65165e-05:0.00280619:0.00877392:0.45687:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074485 ES:SE:LP:AF:ID  -0.00440798:0.00553497:0.366532:0.074485:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24097  ES:SE:LP:AF:ID  0.000226944:0.00320528:0.0268721:0.24097:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -0.00287278:0.0039984:0.327902:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116349 ES:SE:LP:AF:ID  -0.000921295:0.0026859:0.136677:0.116349:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  0.00212649:0.00393613:0.229148:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515663 ES:SE:LP:AF:ID  -3.03826e-05:0.00198978:0.00436481:0.515663:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032993 ES:SE:LP:AF:ID  -0.00114352:0.00501724:0.0861861:0.032993:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036608 ES:SE:LP:AF:ID  0.000513739:0.00455739:0.0409586:0.036608:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  0.000582617:0.00454018:0.0457575:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036424 ES:SE:LP:AF:ID  0.000907967:0.00457277:0.0757207:0.036424:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016402 ES:SE:LP:AF:ID  0.00683338:0.00704095:0.481486:0.016402:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036963 ES:SE:LP:AF:ID  0.000970169:0.00452215:0.0809219:0.036963:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03706  ES:SE:LP:AF:ID  0.000706532:0.00450664:0.0555173:0.03706:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101204 ES:SE:LP:AF:ID  0.00085901:0.00328274:0.102373:0.101204:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959118 ES:SE:LP:AF:ID  -0.00149332:0.0043471:0.136677:0.959118:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031454 ES:SE:LP:AF:ID  0.00325366:0.0078888:0.167491:0.031454:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053264 ES:SE:LP:AF:ID  0.000664113:0.00627445:0.0362122:0.053264:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036577 ES:SE:LP:AF:ID  0.000265545:0.00453585:0.0222764:0.036577:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036892 ES:SE:LP:AF:ID  -0.000314699:0.0044946:0.0268721:0.036892:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843215 ES:SE:LP:AF:ID  7.33437e-05:0.00232798:0.0132283:0.843215:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055932 ES:SE:LP:AF:ID  -0.0055298:0.00376854:0.853872:0.055932:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  -0.00130056:0.00254794:0.21467:0.12233:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025709 ES:SE:LP:AF:ID  -0.0127506:0.00626854:1.37675:0.025709:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121573 ES:SE:LP:AF:ID  -0.00113899:0.00254902:0.187087:0.121573:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132339 ES:SE:LP:AF:ID  -0.00125663:0.00251224:0.207608:0.132339:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  -0.00423218:0.00913372:0.19382:0.011135:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005708 ES:SE:LP:AF:ID  -0.00144374:0.0117833:0.0457575:0.005708:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002262 ES:SE:LP:AF:ID  0.00915587:0.0198749:0.187087:0.002262:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001028 ES:SE:LP:AF:ID  -0.0259847:0.0325087:0.376751:0.001028:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036807 ES:SE:LP:AF:ID  0.00147699:0.00444917:0.130768:0.036807:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838959 ES:SE:LP:AF:ID  0.000699803:0.0022545:0.119186:0.838959:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83859  ES:SE:LP:AF:ID  0.000506808:0.00225209:0.0861861:0.83859:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869774 ES:SE:LP:AF:ID  0.00112335:0.00241656:0.19382:0.869774:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  -0.000831284:0.00242151:0.136677:0.129876:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037318 ES:SE:LP:AF:ID  0.000633847:0.00437372:0.0555173:0.037318:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  0.000247446:0.00434607:0.0222764:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  0.000841271:0.00241186:0.136677:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869217 ES:SE:LP:AF:ID  0.00077466:0.00241282:0.124939:0.869217:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037519 ES:SE:LP:AF:ID  0.000285397:0.00436493:0.0222764:0.037519:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869121 ES:SE:LP:AF:ID  0.00083936:0.00241181:0.136677:0.869121:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005122 ES:SE:LP:AF:ID  -0.00327128:0.012382:0.102373:0.005122:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  -0.00348716:0.0124144:0.107905:0.005088:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838044 ES:SE:LP:AF:ID  0.000612324:0.00224586:0.102373:0.838044:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037531 ES:SE:LP:AF:ID  0.000159307:0.00437114:0.0132283:0.037531:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838674 ES:SE:LP:AF:ID  0.000608501:0.00225217:0.102373:0.838674:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013764 ES:SE:LP:AF:ID  -0.00175789:0.00786438:0.0861861:0.013764:rs181660517