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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_6155_3.vcf.gz --id UKB-b:15175 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_6155_3.txt.gz --cohort_cases 39880 --cohort_controls 420471 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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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-15175/UKB-b-15175_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15175/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:03 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15175/UKB-b-15175_data.vcf.gz ...
Read summary statistics for 7918547 SNPs.
Dropped 5980 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, 1281573 SNPs remain.
After merging with regression SNP LD, 1281573 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0124 (0.0014)
Lambda GC: 1.1149
Mean Chi^2: 1.1291
Intercept: 1.0159 (0.0075)
Ratio: 0.1235 (0.0584)
Analysis finished at Thu Oct 17 14:45:41 2019
Total time elapsed: 1.0m:38.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9425,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 7.4932e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 73894,
    "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": 1281573,
    "ldsc_nsnp_merge_regression_ld": 1281573,
    "ldsc_observed_scale_h2_beta": 0.0124,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0159,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.1149,
    "ldsc_mean_chisq": 1.1291,
    "ldsc_ratio": 0.1232
}

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 7912594 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 7918547 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 8.660700e+00 5.763537e+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 7.869887e+07 5.641983e+07 828.0000000 3.224634e+07 6.916718e+07 1.145475e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.500000e-06 1.460700e-03 -0.0140867 -6.914000e-04 4.300000e-06 7.017000e-04 1.457470e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.223200e-03 7.229000e-04 0.0005657 6.538000e-04 9.043000e-04 1.604200e-03 6.970900e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.843855e-01 2.931894e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.843856e-01 2.931636e-01 0.0000000 2.257873e-01 4.795026e-01 7.383660e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.477902e-01 2.607722e-01 0.0087770 3.693500e-02 1.397230e-01 3.923110e-01 9.912230e-01 ▇▂▂▁▁
numeric AF_reference 73894 0.9906682 NA NA NA NA NA NA NA 2.469999e-01 2.526103e-01 0.0000000 3.933710e-02 1.549520e-01 3.873800e-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 0.0013813 0.0010411 0.1800002 0.1845849 0.623763 0.7821490 NA
1 54676 rs2462492 C T 0.0003743 0.0010314 0.7199992 0.7166780 0.400432 NA NA
1 86028 rs114608975 T C -0.0022993 0.0016492 0.1600000 0.1632530 0.103549 0.0277556 NA
1 91536 rs6702460 G T 0.0012926 0.0010156 0.2000000 0.2031269 0.456866 0.4207270 NA
1 234313 rs8179466 C T 0.0018450 0.0020022 0.3599996 0.3567994 0.074519 NA NA
1 534192 rs6680723 C T 0.0018011 0.0011602 0.1199999 0.1205567 0.240923 NA NA
1 546697 rs12025928 A G -0.0018430 0.0014470 0.2000000 0.2027879 0.913452 NA NA
1 693731 rs12238997 A G 0.0006710 0.0009720 0.4899999 0.4900143 0.116339 0.1417730 NA
1 705882 rs72631875 G A 0.0003219 0.0014245 0.8200001 0.8212119 0.067289 0.0315495 NA
1 706368 rs55727773 A G -0.0007398 0.0007201 0.2999998 0.3042582 0.515638 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0001148 0.0008687 0.8900000 0.8948552 0.137972 0.2052720 NA
22 51219387 rs9616832 T C 0.0005770 0.0011277 0.6100002 0.6088870 0.073734 0.0654952 NA
22 51219704 rs147475742 G A 0.0027630 0.0015112 0.0680002 0.0675011 0.041941 0.0473243 NA
22 51221190 rs369304721 G A 0.0013739 0.0015086 0.3599996 0.3624675 0.049723 NA NA
22 51221731 rs115055839 T C 0.0007092 0.0011284 0.5300002 0.5297082 0.073224 0.0625000 NA
22 51222100 rs114553188 G T -0.0016997 0.0013279 0.2000000 0.2005408 0.054493 0.0880591 NA
22 51223637 rs375798137 G A -0.0017271 0.0013343 0.2000000 0.1955208 0.054122 0.0788738 NA
22 51229805 rs9616985 T C 0.0006993 0.0011325 0.5400003 0.5369018 0.073060 0.0730831 NA
22 51232488 rs376461333 A G -0.0046600 0.0026664 0.0810009 0.0805166 0.020057 NA NA
22 51237063 rs3896457 T C -0.0005551 0.0006926 0.4199997 0.4228522 0.297978 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.0013813:0.0010411:0.744727:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400432 ES:SE:LP:AF:ID  0.00037429:0.00103138:0.142668:0.400432:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -0.00229931:0.00164918:0.79588:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456866 ES:SE:LP:AF:ID  0.00129256:0.00101561:0.69897:0.456866:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  0.00184498:0.00200219:0.443698:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240923 ES:SE:LP:AF:ID  0.00180108:0.00116016:0.920819:0.240923:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913452 ES:SE:LP:AF:ID  -0.00184297:0.001447:0.69897:0.913452:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116339 ES:SE:LP:AF:ID  0.000670967:0.000972013:0.309804:0.116339:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067289 ES:SE:LP:AF:ID  0.000321911:0.00142447:0.0861861:0.067289:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515638 ES:SE:LP:AF:ID  -0.000739835:0.000720143:0.522879:0.515638:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032999 ES:SE:LP:AF:ID  0.00217599:0.00181558:0.638272:0.032999:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036615 ES:SE:LP:AF:ID  0.00197332:0.00164911:0.638272:0.036615:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036732 ES:SE:LP:AF:ID  0.00205499:0.00164288:0.677781:0.036732:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036432 ES:SE:LP:AF:ID  0.00180494:0.00165468:0.552842:0.036432:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016403 ES:SE:LP:AF:ID  -0.00190083:0.00254811:0.337242:0.016403:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036971 ES:SE:LP:AF:ID  0.00189649:0.00163637:0.60206:0.036971:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037068 ES:SE:LP:AF:ID  0.00194601:0.00163075:0.638272:0.037068:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10121  ES:SE:LP:AF:ID  0.000248802:0.00118791:0.0809219:0.10121:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959108 ES:SE:LP:AF:ID  -0.00199187:0.00157294:0.677781:0.959108:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  -0.00130544:0.00285516:0.187087:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  -0.00317439:0.00227103:0.79588:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036587 ES:SE:LP:AF:ID  0.00183564:0.00164127:0.585027:0.036587:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036902 ES:SE:LP:AF:ID  0.00193191:0.00162633:0.638272:0.036902:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843209 ES:SE:LP:AF:ID  -0.000974569:0.000842428:0.60206:0.843209:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055938 ES:SE:LP:AF:ID  0.00104574:0.00136374:0.356547:0.055938:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122328 ES:SE:LP:AF:ID  0.000719264:0.000922014:0.356547:0.122328:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025708 ES:SE:LP:AF:ID  0.00195517:0.00226819:0.408935:0.025708:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121572 ES:SE:LP:AF:ID  0.000634309:0.000922398:0.309804:0.121572:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132346 ES:SE:LP:AF:ID  0.00126417:0.000909172:0.79588:0.132346:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011141 ES:SE:LP:AF:ID  0.00270133:0.00330443:0.387216:0.011141:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036817 ES:SE:LP:AF:ID  0.00177874:0.00160992:0.568636:0.036817:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838925 ES:SE:LP:AF:ID  -0.000723825:0.000815817:0.431798:0.838925:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838557 ES:SE:LP:AF:ID  -0.000863016:0.000814945:0.537602:0.838557:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869744 ES:SE:LP:AF:ID  -0.000440777:0.00087443:0.21467:0.869744:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129904 ES:SE:LP:AF:ID  0.000694261:0.000876214:0.366532:0.129904:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037328 ES:SE:LP:AF:ID  0.0018769:0.00158264:0.619789:0.037328:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037572 ES:SE:LP:AF:ID  0.00181449:0.00157262:0.60206:0.037572:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  -0.000634758:0.000872729:0.327902:0.869089:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869185 ES:SE:LP:AF:ID  -0.000632911:0.000873073:0.327902:0.869185:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.00180613:0.00157943:0.60206:0.03753:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869092 ES:SE:LP:AF:ID  -0.0006516:0.000872711:0.337242:0.869092:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838009 ES:SE:LP:AF:ID  -0.000953074:0.000812675:0.619789:0.838009:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037543 ES:SE:LP:AF:ID  0.00183048:0.00158166:0.60206:0.037543:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83864  ES:SE:LP:AF:ID  -0.000995371:0.000814962:0.657577:0.83864:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013783 ES:SE:LP:AF:ID  -0.00518769:0.0028438:1.16749:0.013783:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.83975  ES:SE:LP:AF:ID  -0.000656376:0.000825979:0.366532:0.83975:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869368 ES:SE:LP:AF:ID  -0.000466239:0.000871688:0.229148:0.869368:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868914 ES:SE:LP:AF:ID  -0.000532449:0.000869492:0.267606:0.868914:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867871 ES:SE:LP:AF:ID  -0.000517079:0.000867836:0.259637:0.867871:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869058 ES:SE:LP:AF:ID  -0.000509573:0.000870207:0.251812:0.869058:rs4951929