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-5476/UKB-b-5476_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5476/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:22 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5476/UKB-b-5476_data.vcf.gz ...
Read summary statistics for 9763106 SNPs.
Dropped 13855 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, 1288937 SNPs remain.
After merging with regression SNP LD, 1288937 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0231 (0.0017)
Lambda GC: 1.3316
Mean Chi^2: 1.3604
Intercept: 1.1526 (0.0078)
Ratio: 0.4234 (0.0217)
Analysis finished at Thu Oct 17 14:46:54 2019
Total time elapsed: 1.0m:31.96s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9497,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 1.7066e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 10,
    "n_p_sig": 76,
    "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": 172268,
    "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": 1288937,
    "ldsc_nsnp_merge_regression_ld": 1288937,
    "ldsc_observed_scale_h2_beta": 0.0231,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.1526,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.3316,
    "ldsc_mean_chisq": 1.3604,
    "ldsc_ratio": 0.4234
}

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 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 9749316 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 9763106 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 8.623572e+00 5.749169e+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 7.885857e+07 5.629259e+07 828.0000000 3.257976e+07 6.947770e+07 1.145923e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.700000e-06 4.809500e-03 -0.0992725 -1.543600e-03 8.700000e-06 1.572900e-03 8.499870e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.275200e-03 3.001800e-03 0.0009472 1.155900e-03 1.919000e-03 4.380200e-03 4.979220e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.618766e-01 2.985310e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.618767e-01 2.985059e-01 0.0000000 1.934203e-01 4.481047e-01 7.204455e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.050105e-01 2.569303e-01 0.0011590 1.378700e-02 8.011700e-02 3.193278e-01 9.988410e-01 ▇▂▁▁▁
numeric AF_reference 172268 0.9823552 NA NA NA NA NA NA NA 2.079064e-01 2.484677e-01 0.0000000 1.218050e-02 1.014380e-01 3.224840e-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 0.0000385 0.0017422 0.9800000 0.9823489 0.623764 0.7821490 NA
1 54676 rs2462492 C T -0.0000568 0.0017260 0.9699999 0.9737499 0.400398 NA NA
1 86028 rs114608975 T C -0.0020083 0.0027594 0.4700002 0.4667268 0.103558 0.0277556 NA
1 91536 rs6702460 G T 0.0010847 0.0016994 0.5199996 0.5233048 0.456843 0.4207270 NA
1 234313 rs8179466 C T 0.0002946 0.0033509 0.9299999 0.9299371 0.074506 NA NA
1 534192 rs6680723 C T -0.0011607 0.0019412 0.5500004 0.5498810 0.240956 NA NA
1 546697 rs12025928 A G -0.0014183 0.0024218 0.5600000 0.5581067 0.913475 NA NA
1 693731 rs12238997 A G -0.0006957 0.0016268 0.6700003 0.6689058 0.116328 0.1417730 NA
1 705882 rs72631875 G A 0.0004558 0.0023838 0.8499999 0.8483556 0.067291 0.0315495 NA
1 706368 rs55727773 A G -0.0003481 0.0012050 0.7700005 0.7726985 0.515643 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0012272 0.0025307 0.6300007 0.6277406 0.041949 0.0473243 NA
22 51219766 rs182321900 C T -0.0006798 0.0117871 0.9500000 0.9540074 0.001938 NA NA
22 51220146 rs868950473 C T -0.0034470 0.0116759 0.7700005 0.7678218 0.001987 NA NA
22 51221190 rs369304721 G A 0.0021731 0.0025265 0.3900004 0.3897149 0.049726 NA NA
22 51221731 rs115055839 T C 0.0013016 0.0018896 0.4899999 0.4909438 0.073230 0.0625000 NA
22 51222100 rs114553188 G T 0.0004421 0.0022246 0.8400000 0.8424626 0.054460 0.0880591 NA
22 51223637 rs375798137 G A 0.0004248 0.0022354 0.8499999 0.8492916 0.054089 0.0788738 NA
22 51229805 rs9616985 T C 0.0014156 0.0018965 0.4600002 0.4554171 0.073066 0.0730831 NA
22 51232488 rs376461333 A G -0.0045903 0.0044676 0.2999998 0.3042006 0.020042 NA NA
22 51237063 rs3896457 T C 0.0017927 0.0011599 0.1199999 0.1222096 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  3.85448e-05:0.0017422:0.00877392:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400398 ES:SE:LP:AF:ID  -5.67951e-05:0.001726:0.0132283:0.400398:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103558 ES:SE:LP:AF:ID  -0.00200834:0.00275941:0.327902:0.103558:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456843 ES:SE:LP:AF:ID  0.00108469:0.00169945:0.283997:0.456843:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074506 ES:SE:LP:AF:ID  0.000294622:0.00335087:0.0315171:0.074506:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  -0.00116073:0.00194122:0.259637:0.240956:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  -0.00141833:0.00242178:0.251812:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116328 ES:SE:LP:AF:ID  -0.000695697:0.00162679:0.173925:0.116328:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067291 ES:SE:LP:AF:ID  0.000455825:0.00238381:0.0705811:0.067291:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515643 ES:SE:LP:AF:ID  -0.000348075:0.00120505:0.113509:0.515643:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03301  ES:SE:LP:AF:ID  0.00297117:0.0030378:0.481486:0.03301:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036626 ES:SE:LP:AF:ID  0.00239897:0.00275937:0.420216:0.036626:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036742 ES:SE:LP:AF:ID  0.00194315:0.00274892:0.318759:0.036742:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036441 ES:SE:LP:AF:ID  0.00212864:0.00276876:0.356547:0.036441:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01641  ES:SE:LP:AF:ID  0.00631334:0.00426302:0.853872:0.01641:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036982 ES:SE:LP:AF:ID  0.0020799:0.00273802:0.346787:0.036982:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037079 ES:SE:LP:AF:ID  0.00207776:0.00272864:0.346787:0.037079:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101201 ES:SE:LP:AF:ID  0.00126463:0.00198829:0.283997:0.101201:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959088 ES:SE:LP:AF:ID  -0.00139584:0.00263171:0.221849:0.959088:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03145  ES:SE:LP:AF:ID  0.00355844:0.00477798:0.337242:0.03145:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.0078434:0.00380079:1.40894:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036596 ES:SE:LP:AF:ID  0.00187551:0.00274635:0.309804:0.036596:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036912 ES:SE:LP:AF:ID  0.00217036:0.00272135:0.366532:0.036912:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843201 ES:SE:LP:AF:ID  -3.84619e-05:0.00140982:0.00877392:0.843201:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055912 ES:SE:LP:AF:ID  -0.00162197:0.00228271:0.318759:0.055912:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:ID  -0.000694964:0.00154318:0.187087:0.122311:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02571  ES:SE:LP:AF:ID  -0.00148896:0.00379612:0.161151:0.02571:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121553 ES:SE:LP:AF:ID  -0.000589568:0.00154383:0.154902:0.121553:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  -0.000637161:0.0015216:0.167491:0.132336:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  -0.00449921:0.00553289:0.376751:0.011132:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005698 ES:SE:LP:AF:ID  -0.00523874:0.00714315:0.337242:0.005698:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002271 ES:SE:LP:AF:ID  -0.0123149:0.0120018:0.522879:0.002271:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036827 ES:SE:LP:AF:ID  0.00291316:0.00269382:0.552842:0.036827:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838943 ES:SE:LP:AF:ID  -0.000341242:0.00136532:0.09691:0.838943:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838572 ES:SE:LP:AF:ID  -0.000385289:0.00136385:0.107905:0.838572:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  0.000548411:0.00146347:0.148742:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129875 ES:SE:LP:AF:ID  -0.000274401:0.00146646:0.0705811:0.129875:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037338 ES:SE:LP:AF:ID  0.00220618:0.00264814:0.39794:0.037338:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037582 ES:SE:LP:AF:ID  0.00242624:0.00263141:0.443698:0.037582:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  0.000540586:0.0014606:0.148742:0.869118:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  0.000474383:0.00146118:0.124939:0.869216:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  0.00216379:0.0026428:0.387216:0.03754:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  0.000542745:0.00146057:0.148742:0.869122:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  0.00627247:0.00750047:0.39794:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  0.00631827:0.00752015:0.39794:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838025 ES:SE:LP:AF:ID  -0.000275716:0.00136006:0.0757207:0.838025:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037552 ES:SE:LP:AF:ID  0.00209543:0.00264653:0.366532:0.037552:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838656 ES:SE:LP:AF:ID  -0.000250964:0.00136389:0.0705811:0.838656:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  0.00226829:0.00476103:0.200659:0.013772:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005546 ES:SE:LP:AF:ID  0.0062265:0.00734603:0.39794:0.005546:rs184270342