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_23125.vcf.gz --id UKB-b:19925 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_23125.txt.gz --cohort_controls 454672 --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-19925/UKB-b-19925_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19925/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:58 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19925/UKB-b-19925_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: 0.2513 (0.008)
Lambda GC: 2.4938
Mean Chi^2: 3.6395
Intercept: 1.2861 (0.0214)
Ratio: 0.1084 (0.0081)
Analysis finished at Thu Oct 17 14:43:41 2019
Total time elapsed: 1.0m:42.66s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.92,
    "mean_EFFECT": 4.0257e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 519,
    "n_p_sig": 91476,
    "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": 0.2513,
    "ldsc_observed_scale_h2_se": 0.008,
    "ldsc_intercept_beta": 1.2861,
    "ldsc_intercept_se": 0.0214,
    "ldsc_lambda_gc": 2.4938,
    "ldsc_mean_chisq": 3.6395,
    "ldsc_ratio": 0.1084
}
 

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 4.000000e-06 7.004800e-03 -0.2454380 -2.675400e-03 -3.000000e-07 2.670200e-03 1.696720e-01 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.339900e-03 4.107600e-03 0.0012126 1.486800e-03 2.493100e-03 5.752300e-03 6.368940e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.937803e-01 3.117140e-01 0.0000000 9.800090e-02 3.500000e-01 6.600001e-01 1.000000e+00 ▇▅▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.937831e-01 3.116933e-01 0.0000000 9.798570e-02 3.476115e-01 6.605416e-01 9.999997e-01 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568614e-01 0.0009840 1.316900e-02 7.791400e-02 3.164540e-01 9.990050e-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 0.0006477 0.0022277 0.7700005 0.7712418 0.623736 0.7821490 NA
1 54676 rs2462492 C T 0.0030005 0.0022074 0.1700000 0.1740509 0.400351 NA NA
1 86028 rs114608975 T C -0.0015442 0.0035287 0.6600001 0.6616817 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0050296 0.0021730 0.0210000 0.0206351 0.456854 0.4207270 NA
1 234313 rs8179466 C T -0.0093503 0.0042864 0.0290001 0.0291561 0.074494 NA NA
1 534192 rs6680723 C T -0.0038480 0.0024825 0.1199999 0.1211181 0.240937 NA NA
1 546697 rs12025928 A G 0.0060375 0.0030968 0.0510000 0.0512247 0.913461 NA NA
1 693731 rs12238997 A G -0.0033139 0.0020815 0.1100001 0.1113702 0.116209 0.1417730 NA
1 705882 rs72631875 G A -0.0053026 0.0030477 0.0819993 0.0818815 0.067325 0.0315495 NA
1 706368 rs55727773 A G -0.0011817 0.0015413 0.4400003 0.4432606 0.515773 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0056532 0.0032578 0.0830004 0.0826889 0.041968 0.0473243 NA
22 51219766 rs182321900 C T -0.0123170 0.0151605 0.4199997 0.4165391 0.001943 NA NA
22 51220146 rs868950473 C T -0.0126779 0.0150161 0.4000000 0.3985090 0.001992 NA NA
22 51221190 rs369304721 G A -0.0013211 0.0032519 0.6800001 0.6845608 0.049765 NA NA
22 51221731 rs115055839 T C 0.0000360 0.0024326 0.9900000 0.9881789 0.073282 0.0625000 NA
22 51222100 rs114553188 G T 0.0007275 0.0028640 0.8000000 0.7994897 0.054490 0.0880591 NA
22 51223637 rs375798137 G A 0.0007252 0.0028778 0.8000000 0.8010509 0.054119 0.0788738 NA
22 51229805 rs9616985 T C 0.0001978 0.0024414 0.9400001 0.9354273 0.073115 0.0730831 NA
22 51232488 rs376461333 A G 0.0027280 0.0057503 0.6400000 0.6352111 0.020056 NA NA
22 51237063 rs3896457 T C 0.0004065 0.0014939 0.7899998 0.7855225 0.297907 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623736 ES:SE:LP:AF:ID  0.000647706:0.0022277:0.113509:0.623736:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400351 ES:SE:LP:AF:ID  0.00300051:0.00220739:0.769551:0.400351:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  -0.00154415:0.00352874:0.180456:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456854 ES:SE:LP:AF:ID  0.00502964:0.00217301:1.67778:0.456854:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074494 ES:SE:LP:AF:ID  -0.00935029:0.00428643:1.5376:0.074494:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240937 ES:SE:LP:AF:ID  -0.00384804:0.00248245:0.920819:0.240937:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913461 ES:SE:LP:AF:ID  0.00603748:0.00309679:1.29243:0.913461:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116209 ES:SE:LP:AF:ID  -0.00331393:0.00208153:0.958607:0.116209:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067325 ES:SE:LP:AF:ID  -0.00530259:0.00304769:1.08619:0.067325:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515773 ES:SE:LP:AF:ID  -0.00118169:0.00154127:0.356547:0.515773:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032986 ES:SE:LP:AF:ID  -0.000651488:0.00388601:0.0604807:0.032986:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036597 ES:SE:LP:AF:ID  -0.000586798:0.00353013:0.0604807:0.036597:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036716 ES:SE:LP:AF:ID  -0.000201573:0.00351652:0.0222764:0.036716:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036413 ES:SE:LP:AF:ID  -0.00100203:0.00354207:0.107905:0.036413:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016391 ES:SE:LP:AF:ID  -0.00251593:0.00545522:0.19382:0.016391:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036953 ES:SE:LP:AF:ID  -0.000831644:0.00350281:0.091515:0.036953:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037051 ES:SE:LP:AF:ID  -0.000730188:0.00349071:0.0809219:0.037051:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101247 ES:SE:LP:AF:ID  0.00162053:0.00254235:0.283997:0.101247:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959097 ES:SE:LP:AF:ID  0.00134735:0.00336584:0.161151:0.959097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031463 ES:SE:LP:AF:ID  -0.00372364:0.00610581:0.267606:0.031463:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  0.00253186:0.00485771:0.221849:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036572 ES:SE:LP:AF:ID  -0.00122456:0.00351313:0.136677:0.036572:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03689  ES:SE:LP:AF:ID  -0.00192196:0.00348115:0.236572:0.03689:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843328 ES:SE:LP:AF:ID  0.00294589:0.0018035:1:0.843328:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05586  ES:SE:LP:AF:ID  -0.00574628:0.00292058:1.3098:0.05586:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122186 ES:SE:LP:AF:ID  -0.0033531:0.0019745:1.05061:0.122186:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025733 ES:SE:LP:AF:ID  0.00346719:0.00485138:0.327902:0.025733:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121426 ES:SE:LP:AF:ID  -0.0031951:0.00197534:0.958607:0.121426:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13221  ES:SE:LP:AF:ID  -0.00299363:0.00194666:0.920819:0.13221:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011123 ES:SE:LP:AF:ID  0.00620128:0.0070813:0.420216:0.011123:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005691 ES:SE:LP:AF:ID  0.00917433:0.00913732:0.49485:0.005691:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002288 ES:SE:LP:AF:ID  0.00432943:0.0152922:0.107905:0.002288:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  0.00117408:0.0250146:0.0177288:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036804 ES:SE:LP:AF:ID  -0.00129663:0.00344597:0.148742:0.036804:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839057 ES:SE:LP:AF:ID  0.00294436:0.00174646:1.03621:0.839057:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838683 ES:SE:LP:AF:ID  0.00300622:0.00174454:1.07058:0.838683:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869876 ES:SE:LP:AF:ID  0.00317883:0.00187217:1.04576:0.869876:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129763 ES:SE:LP:AF:ID  -0.00345111:0.00187608:1.18046:0.129763:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037316 ES:SE:LP:AF:ID  -0.00281408:0.00338757:0.387216:0.037316:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  -0.00266088:0.00336612:0.366532:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86922  ES:SE:LP:AF:ID  0.00321572:0.00186848:1.07058:0.86922:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869318 ES:SE:LP:AF:ID  0.00317728:0.00186922:1.05061:0.869318:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  -0.00284338:0.00338089:0.39794:0.037514:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869223 ES:SE:LP:AF:ID  0.00324394:0.00186844:1.08092:0.869223:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005131 ES:SE:LP:AF:ID  -0.00620012:0.00958117:0.283997:0.005131:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005097 ES:SE:LP:AF:ID  -0.00657832:0.009606:0.309804:0.005097:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83814  ES:SE:LP:AF:ID  0.00306225:0.00173973:1.10791:0.83814:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  -0.00286559:0.00338567:0.39794:0.037526:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838772 ES:SE:LP:AF:ID  0.00312742:0.00174464:1.13668:0.838772:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  0.0120882:0.0060869:1.3279:0.013776:rs181660517