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-2393/UKB-b-2393_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2393/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:37 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2393/UKB-b-2393_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: 0.0432 (0.0019)
Lambda GC: 1.3427
Mean Chi^2: 1.4215
Intercept: 1.0302 (0.0085)
Ratio: 0.0715 (0.0201)
Analysis finished at Thu Oct 17 14:44:28 2019
Total time elapsed: 1.0m:50.87s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 28,
    "n_p_sig": 2753,
    "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": 0.0432,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.0302,
    "ldsc_intercept_se": 0.0085,
    "ldsc_lambda_gc": 1.3427,
    "ldsc_mean_chisq": 1.4215,
    "ldsc_ratio": 0.0716
}

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 1.530000e-05 4.273400e-03 -0.0770435 -1.400400e-03 5.100000e-06 1.406400e-03 7.085560e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.007900e-03 2.847300e-03 0.0008417 1.030300e-03 1.727700e-03 3.986600e-03 4.421580e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.653813e-01 2.987075e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.653824e-01 2.986837e-01 0.0000000 1.976437e-01 4.535696e-01 7.248681e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035076e-01 2.568623e-01 0.0009860 1.316900e-02 7.791400e-02 3.164538e-01 9.990080e-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 -0.0025039 0.0015483 0.1100001 0.1058431 0.623754 0.7821490 NA
1 54676 rs2462492 C T -0.0014940 0.0015339 0.3300000 0.3300622 0.400423 NA NA
1 86028 rs114608975 T C 0.0027240 0.0024517 0.2700001 0.2665408 0.103567 0.0277556 NA
1 91536 rs6702460 G T -0.0014533 0.0015104 0.3400001 0.3359253 0.456847 0.4207270 NA
1 234313 rs8179466 C T 0.0045197 0.0029775 0.1299999 0.1290284 0.074513 NA NA
1 534192 rs6680723 C T -0.0018684 0.0017254 0.2800000 0.2788669 0.240946 NA NA
1 546697 rs12025928 A G 0.0007405 0.0021522 0.7300002 0.7307786 0.913464 NA NA
1 693731 rs12238997 A G 0.0018411 0.0014457 0.2000000 0.2028342 0.116324 0.1417730 NA
1 705882 rs72631875 G A -0.0033899 0.0021188 0.1100001 0.1096147 0.067282 0.0315495 NA
1 706368 rs55727773 A G -0.0016026 0.0010710 0.1299999 0.1345578 0.515607 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0027838 0.0022492 0.2200002 0.2158335 0.041919 0.0473243 NA
22 51219766 rs182321900 C T -0.0042288 0.0105081 0.6899999 0.6873693 0.001927 NA NA
22 51220146 rs868950473 C T -0.0029366 0.0104083 0.7800007 0.7778353 0.001976 NA NA
22 51221190 rs369304721 G A -0.0039692 0.0022455 0.0769999 0.0771170 0.049696 NA NA
22 51221731 rs115055839 T C -0.0030244 0.0016793 0.0719996 0.0717075 0.073194 0.0625000 NA
22 51222100 rs114553188 G T 0.0030280 0.0019765 0.1299999 0.1255286 0.054459 0.0880591 NA
22 51223637 rs375798137 G A 0.0029901 0.0019861 0.1299999 0.1321947 0.054088 0.0788738 NA
22 51229805 rs9616985 T C -0.0031654 0.0016854 0.0599998 0.0603587 0.073030 0.0730831 NA
22 51232488 rs376461333 A G 0.0031691 0.0039679 0.4199997 0.4244755 0.020053 NA NA
22 51237063 rs3896457 T C -0.0008478 0.0010305 0.4100001 0.4106929 0.297994 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623754 ES:SE:LP:AF:ID  -0.00250387:0.00154831:0.958607:0.623754:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400423 ES:SE:LP:AF:ID  -0.00149404:0.00153394:0.481486:0.400423:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103567 ES:SE:LP:AF:ID  0.00272404:0.00245174:0.568636:0.103567:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456847 ES:SE:LP:AF:ID  -0.00145334:0.00151036:0.468521:0.456847:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074513 ES:SE:LP:AF:ID  0.00451968:0.0029775:0.886057:0.074513:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240946 ES:SE:LP:AF:ID  -0.00186837:0.00172539:0.552842:0.240946:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913464 ES:SE:LP:AF:ID  0.000740547:0.00215219:0.136677:0.913464:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116324 ES:SE:LP:AF:ID  0.0018411:0.00144568:0.69897:0.116324:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067282 ES:SE:LP:AF:ID  -0.00338991:0.00211879:0.958607:0.067282:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515607 ES:SE:LP:AF:ID  -0.00160261:0.001071:0.886057:0.515607:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033001 ES:SE:LP:AF:ID  -0.000612874:0.00270003:0.0861861:0.033001:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036615 ES:SE:LP:AF:ID  -0.000874233:0.00245263:0.142668:0.036615:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036732 ES:SE:LP:AF:ID  -0.000926373:0.00244331:0.154902:0.036732:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036432 ES:SE:LP:AF:ID  -0.000247293:0.00246091:0.0362122:0.036432:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016392 ES:SE:LP:AF:ID  0.000539142:0.00379097:0.05061:0.016392:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036971 ES:SE:LP:AF:ID  -0.000862448:0.00243367:0.142668:0.036971:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037068 ES:SE:LP:AF:ID  -0.000784361:0.00242531:0.124939:0.037068:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101233 ES:SE:LP:AF:ID  0.00215072:0.00176647:0.657577:0.101233:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959111 ES:SE:LP:AF:ID  -0.00018929:0.00233941:0.0268721:0.959111:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031453 ES:SE:LP:AF:ID  -0.00137039:0.00424551:0.124939:0.031453:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05326  ES:SE:LP:AF:ID  0.00211335:0.00337666:0.275724:0.05326:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036584 ES:SE:LP:AF:ID  -0.000595426:0.00244108:0.091515:0.036584:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.0369   ES:SE:LP:AF:ID  -0.000870155:0.00241883:0.142668:0.0369:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84323  ES:SE:LP:AF:ID  -0.00153732:0.00125298:0.657577:0.84323:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055925 ES:SE:LP:AF:ID  0.00475103:0.00202844:1.72125:0.055925:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122303 ES:SE:LP:AF:ID  0.00178422:0.00137137:0.721246:0.122303:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025694 ES:SE:LP:AF:ID  -0.00458274:0.00337464:0.769551:0.025694:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121548 ES:SE:LP:AF:ID  0.00167023:0.00137194:0.657577:0.121548:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132339 ES:SE:LP:AF:ID  0.00108682:0.00135221:0.376751:0.132339:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011141 ES:SE:LP:AF:ID  0.000568295:0.00491513:0.0409586:0.011141:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005709 ES:SE:LP:AF:ID  -0.00653559:0.00634169:0.522879:0.005709:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002267 ES:SE:LP:AF:ID  0.00975023:0.0106758:0.443698:0.002267:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001028 ES:SE:LP:AF:ID  -0.0197159:0.0174863:0.585027:0.001028:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036813 ES:SE:LP:AF:ID  -0.00114084:0.00239448:0.200659:0.036813:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838968 ES:SE:LP:AF:ID  -0.00143793:0.00121344:0.619789:0.838968:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838599 ES:SE:LP:AF:ID  -0.00135944:0.00121216:0.585027:0.838599:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869791 ES:SE:LP:AF:ID  -0.00209978:0.00130068:0.958607:0.869791:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129856 ES:SE:LP:AF:ID  0.00192851:0.00130335:0.853872:0.129856:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037324 ES:SE:LP:AF:ID  -0.00124893:0.00235391:0.221849:0.037324:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037566 ES:SE:LP:AF:ID  -0.00131254:0.00233908:0.244125:0.037566:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869137 ES:SE:LP:AF:ID  -0.0020913:0.00129817:0.958607:0.869137:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869234 ES:SE:LP:AF:ID  -0.00213163:0.00129869:1:0.869234:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037524 ES:SE:LP:AF:ID  -0.00102204:0.0023492:0.180456:0.037524:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869139 ES:SE:LP:AF:ID  -0.00209481:0.00129815:0.958607:0.869139:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  0.00781342:0.0066648:0.619789:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  0.00786957:0.00668225:0.619789:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838051 ES:SE:LP:AF:ID  -0.00151545:0.00120878:0.677781:0.838051:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037537 ES:SE:LP:AF:ID  -0.000964409:0.0023525:0.167491:0.037537:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838681 ES:SE:LP:AF:ID  -0.00154972:0.00121218:0.69897:0.838681:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013777 ES:SE:LP:AF:ID  -0.000811443:0.00423024:0.0705811:0.013777:rs181660517