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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    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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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_20087_159.vcf.gz --id UKB-b:1993 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20087_159.txt.gz --cohort_cases 15836 --cohort_controls 49113 --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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    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-1993/ukb-b-1993.vcf.gz; Date=Sun May 10 01:16:14 2020"
}

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-1993/UKB-b-1993_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1993/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:03 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1993/UKB-b-1993_data.vcf.gz ...
Read summary statistics for 6603425 SNPs.
Dropped 3690 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, 1248601 SNPs remain.
After merging with regression SNP LD, 1248601 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0209 (0.0069)
Lambda GC: 1.0438
Mean Chi^2: 1.0392
Intercept: 1.0122 (0.0067)
Ratio: 0.311 (0.1704)
Analysis finished at Thu Oct 17 14:43:27 2019
Total time elapsed: 1.0m:23.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.932,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 60597,
    "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": 1248601,
    "ldsc_nsnp_merge_regression_ld": 1248601,
    "ldsc_observed_scale_h2_beta": 0.0209,
    "ldsc_observed_scale_h2_se": 0.0069,
    "ldsc_intercept_beta": 1.0122,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0438,
    "ldsc_mean_chisq": 1.0392,
    "ldsc_ratio": 0.3112
}

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 6599757 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 6603425 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 8.665301e+00 5.763864e+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 7.858659e+07 5.648079e+07 828.0000000 3.204928e+07 6.903317e+07 1.144858e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.780000e-05 4.265600e-03 -0.0365362 -2.421200e-03 -4.670000e-05 2.333200e-03 4.004110e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.866100e-03 1.595600e-03 0.0023009 2.573200e-03 3.214800e-03 4.767400e-03 1.987250e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.937695e-01 2.902500e-01 0.0000001 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.937687e-01 2.902235e-01 0.0000001 2.408755e-01 4.913648e-01 7.450825e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.894420e-01 2.579881e-01 0.0221020 7.287300e-02 1.985960e-01 4.501540e-01 9.778980e-01 ▇▃▂▂▁
numeric AF_reference 60597 0.9908234 NA NA NA NA NA NA NA 2.871494e-01 2.502889e-01 0.0000000 8.206870e-02 2.088660e-01 4.422920e-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 -0.0062685 0.0042408 0.1400000 0.1393704 0.623812 0.7821490 NA
1 54676 rs2462492 C T -0.0047853 0.0042284 0.2599998 0.2577652 0.399144 NA NA
1 86028 rs114608975 T C 0.0077694 0.0067310 0.2500000 0.2483910 0.103536 0.0277556 NA
1 91536 rs6702460 G T -0.0057685 0.0041590 0.1700000 0.1654407 0.455916 0.4207270 NA
1 234313 rs8179466 C T -0.0087830 0.0082249 0.2900000 0.2855866 0.074455 NA NA
1 534192 rs6680723 C T -0.0007584 0.0047369 0.8700001 0.8727919 0.242057 NA NA
1 546697 rs12025928 A G 0.0004298 0.0058774 0.9400001 0.9417073 0.912862 NA NA
1 693731 rs12238997 A G 0.0002487 0.0039497 0.9500000 0.9497983 0.117313 0.1417730 NA
1 705882 rs72631875 G A 0.0094905 0.0057572 0.0990011 0.0992565 0.067698 0.0315495 NA
1 706368 rs55727773 A G -0.0002854 0.0029318 0.9199999 0.9224443 0.513304 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0085584 0.0046352 0.0649995 0.0648390 0.071792 0.0826677 NA
22 51219006 rs28729663 G A 0.0080082 0.0035658 0.0250000 0.0247156 0.136315 0.2052720 NA
22 51219387 rs9616832 T C 0.0084747 0.0046476 0.0680002 0.0682359 0.071797 0.0654952 NA
22 51219704 rs147475742 G A 0.0027290 0.0061826 0.6600001 0.6589293 0.041190 0.0473243 NA
22 51221190 rs369304721 G A 0.0102892 0.0062264 0.0980009 0.0984329 0.048372 NA NA
22 51221731 rs115055839 T C 0.0091253 0.0046487 0.0500000 0.0496469 0.071348 0.0625000 NA
22 51222100 rs114553188 G T 0.0065937 0.0053868 0.2200002 0.2209327 0.054850 0.0880591 NA
22 51223637 rs375798137 G A 0.0068122 0.0054149 0.2099999 0.2083748 0.054470 0.0788738 NA
22 51229805 rs9616985 T C 0.0086688 0.0046630 0.0629999 0.0630191 0.071253 0.0730831 NA
22 51237063 rs3896457 T C -0.0041609 0.0028151 0.1400000 0.1393891 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.00626848:0.00424079:0.853872:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  -0.00478529:0.00422845:0.585027:0.399144:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  0.00776939:0.00673102:0.60206:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  -0.00576852:0.00415898:0.769551:0.455916:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074455 ES:SE:LP:AF:ID  -0.00878301:0.00822492:0.537602:0.074455:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  -0.000758434:0.00473686:0.0604807:0.242057:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912862 ES:SE:LP:AF:ID  0.000429781:0.00587741:0.0268721:0.912862:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117313 ES:SE:LP:AF:ID  0.000248676:0.00394974:0.0222764:0.117313:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067698 ES:SE:LP:AF:ID  0.0094905:0.00575716:1.00436:0.067698:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  -0.000285423:0.00293177:0.0362122:0.513304:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033677 ES:SE:LP:AF:ID  -0.00179669:0.00730756:0.091515:0.033677:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037457 ES:SE:LP:AF:ID  -0.00276876:0.0066276:0.167491:0.037457:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037644 ES:SE:LP:AF:ID  -0.00246541:0.00659292:0.148742:0.037644:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03722  ES:SE:LP:AF:ID  -0.00255857:0.00665317:0.154902:0.03722:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.03786  ES:SE:LP:AF:ID  -0.00235101:0.00657038:0.142668:0.03786:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037955 ES:SE:LP:AF:ID  -0.00196385:0.00654954:0.119186:0.037955:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102736 ES:SE:LP:AF:ID  0.000464556:0.00478428:0.0362122:0.102736:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95809  ES:SE:LP:AF:ID  0.00157983:0.00632587:0.09691:0.95809:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03169  ES:SE:LP:AF:ID  0.0105191:0.0115837:0.443698:0.03169:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052723 ES:SE:LP:AF:ID  -0.00691197:0.00933034:0.337242:0.052723:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037449 ES:SE:LP:AF:ID  -0.00141406:0.00659255:0.0809219:0.037449:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037717 ES:SE:LP:AF:ID  -0.00224863:0.00653794:0.136677:0.037717:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  0.000136034:0.00341579:0.0132283:0.841441:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056334 ES:SE:LP:AF:ID  -0.00152355:0.00554876:0.107905:0.056334:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  0.000567958:0.00375179:0.0555173:0.123078:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02513  ES:SE:LP:AF:ID  -0.00950141:0.00934323:0.508638:0.02513:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  0.000670142:0.003753:0.0655015:0.12233:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  -0.00231452:0.00368418:0.275724:0.134139:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.0376   ES:SE:LP:AF:ID  -0.00240067:0.00647735:0.148742:0.0376:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  -0.000276621:0.00330436:0.0315171:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  -0.000235722:0.00330194:0.0268721:0.836733:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  -0.0011847:0.0035481:0.130768:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131004 ES:SE:LP:AF:ID  0.000925296:0.00355722:0.102373:0.131004:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038045 ES:SE:LP:AF:ID  -0.00294868:0.00637575:0.19382:0.038045:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038292 ES:SE:LP:AF:ID  -0.00319894:0.00633624:0.21467:0.038292:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867976 ES:SE:LP:AF:ID  -0.00118307:0.0035424:0.130768:0.867976:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86805  ES:SE:LP:AF:ID  -0.00118423:0.00354385:0.130768:0.86805:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038199 ES:SE:LP:AF:ID  -0.0029879:0.00636549:0.19382:0.038199:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867987 ES:SE:LP:AF:ID  -0.00114668:0.00354231:0.124939:0.867987:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  -0.000526082:0.00329228:0.0604807:0.836159:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038203 ES:SE:LP:AF:ID  -0.00281221:0.00637479:0.180456:0.038203:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  -0.000736722:0.0033013:0.0861861:0.836793:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  -0.000584995:0.00334777:0.0655015:0.838109:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  -0.000808718:0.00353775:0.0861861:0.868228:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867742 ES:SE:LP:AF:ID  -0.00087104:0.00352838:0.091515:0.867742:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866644 ES:SE:LP:AF:ID  -0.00114641:0.00352191:0.130768:0.866644:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867911 ES:SE:LP:AF:ID  -0.000751612:0.00353196:0.0809219:0.867911:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867923 ES:SE:LP:AF:ID  -0.000760753:0.0035322:0.0809219:0.867923:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867932 ES:SE:LP:AF:ID  -0.000770499:0.00353233:0.0809219:0.867932:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868398 ES:SE:LP:AF:ID  -0.000918004:0.00354162:0.09691:0.868398:rs3131954