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-14598/UKB-b-14598_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14598/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:44 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14598/UKB-b-14598_data.vcf.gz ...
Read summary statistics for 9554798 SNPs.
Dropped 12039 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, 1288487 SNPs remain.
After merging with regression SNP LD, 1288487 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0226 (0.0017)
Lambda GC: 1.3774
Mean Chi^2: 1.4065
Intercept: 1.2071 (0.0081)
Ratio: 0.5095 (0.0198)
Analysis finished at Thu Oct 17 14:45:30 2019
Total time elapsed: 1.0m:46.11s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9492,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 6,
    "n_p_sig": 88,
    "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": 140342,
    "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": 1288487,
    "ldsc_nsnp_merge_regression_ld": 1288487,
    "ldsc_observed_scale_h2_beta": 0.0226,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.2071,
    "ldsc_intercept_se": 0.0081,
    "ldsc_lambda_gc": 1.3774,
    "ldsc_mean_chisq": 1.4065,
    "ldsc_ratio": 0.5095
}

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 TRUE
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 9542820 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 9554798 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 8.628213e+00 5.751148e+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 7.883464e+07 5.630319e+07 828.0000000 3.254726e+07 6.942621e+07 1.145682e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.940000e-05 4.677200e-03 -0.0665798 -1.612000e-03 9.700000e-06 1.652000e-03 5.786850e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.212400e-03 2.738700e-03 0.0009982 1.210100e-03 1.963600e-03 4.359200e-03 3.661790e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.554620e-01 2.993756e-01 0.0000000 1.800002e-01 4.400003e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.554621e-01 2.993500e-01 0.0000000 1.849978e-01 4.383339e-01 7.144168e-01 9.999999e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.087799e-01 2.572213e-01 0.0016110 1.534900e-02 8.545500e-02 3.264440e-01 9.983890e-01 ▇▂▁▁▁
numeric AF_reference 140342 0.9853119 NA NA NA NA NA NA NA 2.106837e-01 2.489126e-01 0.0000000 1.317890e-02 1.054310e-01 3.280750e-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 -0.0013025 0.0018356 0.4799997 0.4779918 0.623781 0.7821490 NA
1 54676 rs2462492 C T 0.0015517 0.0018187 0.3900004 0.3935447 0.400410 NA NA
1 86028 rs114608975 T C -0.0024605 0.0029068 0.4000000 0.3972817 0.103569 0.0277556 NA
1 91536 rs6702460 G T 0.0008182 0.0017907 0.6499995 0.6477311 0.456743 0.4207270 NA
1 234313 rs8179466 C T -0.0005935 0.0035295 0.8700001 0.8664567 0.074517 NA NA
1 534192 rs6680723 C T 0.0007875 0.0020454 0.6999999 0.7002333 0.240962 NA NA
1 546697 rs12025928 A G 0.0001676 0.0025529 0.9500000 0.9476699 0.913513 NA NA
1 693731 rs12238997 A G 0.0014336 0.0017142 0.4000000 0.4029776 0.116293 0.1417730 NA
1 705882 rs72631875 G A -0.0017430 0.0025113 0.4899999 0.4876461 0.067321 0.0315495 NA
1 706368 rs55727773 A G -0.0015251 0.0012699 0.2300001 0.2297597 0.515622 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0047096 0.0026670 0.0769999 0.0774142 0.041968 0.0473243 NA
22 51219766 rs182321900 C T 0.0010372 0.0124389 0.9299999 0.9335465 0.001935 NA NA
22 51220146 rs868950473 C T -0.0012119 0.0123259 0.9199999 0.9216784 0.001982 NA NA
22 51221190 rs369304721 G A 0.0020958 0.0026628 0.4299995 0.4312627 0.049747 NA NA
22 51221731 rs115055839 T C 0.0023102 0.0019917 0.2500000 0.2460666 0.073263 0.0625000 NA
22 51222100 rs114553188 G T 0.0033880 0.0023448 0.1499999 0.1484799 0.054472 0.0880591 NA
22 51223637 rs375798137 G A 0.0033860 0.0023562 0.1499999 0.1506974 0.054097 0.0788738 NA
22 51229805 rs9616985 T C 0.0022561 0.0019988 0.2599998 0.2590121 0.073102 0.0730831 NA
22 51232488 rs376461333 A G 0.0024427 0.0047084 0.5999997 0.6038976 0.020044 NA NA
22 51237063 rs3896457 T C 0.0014197 0.0012227 0.2500000 0.2455859 0.297959 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623781 ES:SE:LP:AF:ID  -0.00130246:0.00183565:0.318759:0.623781:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40041  ES:SE:LP:AF:ID  0.00155171:0.00181868:0.408935:0.40041:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103569 ES:SE:LP:AF:ID  -0.00246054:0.00290677:0.39794:0.103569:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456743 ES:SE:LP:AF:ID  0.000818182:0.00179066:0.187087:0.456743:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074517 ES:SE:LP:AF:ID  -0.000593529:0.00352953:0.0604807:0.074517:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240962 ES:SE:LP:AF:ID  0.000787471:0.00204535:0.154902:0.240962:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913513 ES:SE:LP:AF:ID  0.000167553:0.00255287:0.0222764:0.913513:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116293 ES:SE:LP:AF:ID  0.00143362:0.00171421:0.39794:0.116293:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067321 ES:SE:LP:AF:ID  -0.00174298:0.00251129:0.309804:0.067321:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515622 ES:SE:LP:AF:ID  -0.00152511:0.00126989:0.638272:0.515622:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032979 ES:SE:LP:AF:ID  -0.0020944:0.00320265:0.29243:0.032979:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  -0.001688:0.0029089:0.251812:0.036594:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036711 ES:SE:LP:AF:ID  -0.00197947:0.00289788:0.309804:0.036711:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036412 ES:SE:LP:AF:ID  -0.00177732:0.00291865:0.267606:0.036412:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016423 ES:SE:LP:AF:ID  0.0104826:0.00448919:1.69897:0.016423:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036952 ES:SE:LP:AF:ID  -0.00167976:0.00288633:0.251812:0.036952:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037051 ES:SE:LP:AF:ID  -0.00146895:0.0028763:0.21467:0.037051:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101222 ES:SE:LP:AF:ID  0.00275198:0.00209498:0.721246:0.101222:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959131 ES:SE:LP:AF:ID  0.00231367:0.00277454:0.39794:0.959131:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031455 ES:SE:LP:AF:ID  0.000206479:0.00503458:0.0132283:0.031455:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053273 ES:SE:LP:AF:ID  -0.0116496:0.00400382:2.4437:0.053273:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036568 ES:SE:LP:AF:ID  -0.00151332:0.002895:0.221849:0.036568:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036882 ES:SE:LP:AF:ID  -0.00119006:0.00286871:0.167491:0.036882:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843263 ES:SE:LP:AF:ID  -0.000507907:0.00148566:0.136677:0.843263:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055867 ES:SE:LP:AF:ID  -0.000719274:0.00240635:0.113509:0.055867:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122285 ES:SE:LP:AF:ID  0.0011308:0.00162599:0.309804:0.122285:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025726 ES:SE:LP:AF:ID  0.00407405:0.00399876:0.508638:0.025726:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121531 ES:SE:LP:AF:ID  0.00120552:0.00162665:0.337242:0.121531:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132265 ES:SE:LP:AF:ID  -0.00106958:0.00160368:0.30103:0.132265:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  -0.00393985:0.00583005:0.30103:0.011135:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  0.00206045:0.00753092:0.107905:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002266 ES:SE:LP:AF:ID  -0.017049:0.0126677:0.744727:0.002266:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036797 ES:SE:LP:AF:ID  -0.00112566:0.00283968:0.161151:0.036797:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838977 ES:SE:LP:AF:ID  -0.00093073:0.00143865:0.283997:0.838977:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838606 ES:SE:LP:AF:ID  -0.000921504:0.00143708:0.283997:0.838606:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869789 ES:SE:LP:AF:ID  -0.00129807:0.00154193:0.39794:0.869789:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129868 ES:SE:LP:AF:ID  0.00155855:0.00154504:0.508638:0.129868:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037307 ES:SE:LP:AF:ID  -0.00139777:0.00279149:0.207608:0.037307:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037552 ES:SE:LP:AF:ID  -0.0012171:0.00277378:0.180456:0.037552:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86913  ES:SE:LP:AF:ID  -0.00131138:0.00153888:0.408935:0.86913:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86923  ES:SE:LP:AF:ID  -0.00134043:0.0015395:0.420216:0.86923:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037507 ES:SE:LP:AF:ID  -0.00141189:0.00278586:0.21467:0.037507:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869134 ES:SE:LP:AF:ID  -0.00131892:0.00153885:0.408935:0.869134:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005127 ES:SE:LP:AF:ID  0.0169849:0.00789752:1.49485:0.005127:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005093 ES:SE:LP:AF:ID  0.0171385:0.00791841:1.52288:0.005093:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838063 ES:SE:LP:AF:ID  -0.000850896:0.00143315:0.259637:0.838063:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03752  ES:SE:LP:AF:ID  -0.00144882:0.00278978:0.221849:0.03752:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838695 ES:SE:LP:AF:ID  -0.000859066:0.00143718:0.259637:0.838695:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013779 ES:SE:LP:AF:ID  -0.00144941:0.00501557:0.113509:0.013779:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005544 ES:SE:LP:AF:ID  0.00874052:0.00774152:0.585027:0.005544:rs184270342