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.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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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_20161.vcf.gz --id UKB-b:10831 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20161.txt.gz --cohort_controls 142387 --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-10831/UKB-b-10831_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10831/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10831/UKB-b-10831_data.vcf.gz ...
Read summary statistics for 9277584 SNPs.
Dropped 10146 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, 1287885 SNPs remain.
After merging with regression SNP LD, 1287885 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0955 (0.0061)
Lambda GC: 1.254
Mean Chi^2: 1.2964
Intercept: 1.032 (0.0081)
Ratio: 0.1078 (0.0275)
Analysis finished at Thu Oct 17 14:42:00 2019
Total time elapsed: 1.0m:41.25s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9486,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 11,
    "n_p_sig": 1004,
    "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": 110116,
    "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": 1287885,
    "ldsc_nsnp_merge_regression_ld": 1287885,
    "ldsc_observed_scale_h2_beta": 0.0955,
    "ldsc_observed_scale_h2_se": 0.0061,
    "ldsc_intercept_beta": 1.032,
    "ldsc_intercept_se": 0.0081,
    "ldsc_lambda_gc": 1.254,
    "ldsc_mean_chisq": 1.2964,
    "ldsc_ratio": 0.108
}
 

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 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 1.000000 3 58 0 9267489 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9277584 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.635594e+00 5.754308e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.880595e+07 5.630781e+07 828.0000000 3.249786e+07 6.939145e+07 1.145356e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 1.350000e-05 1.305250e-02 -0.1628740 -5.030300e-03 1.070000e-05 5.024400e-03 1.803050e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 9.919200e-03 7.774000e-03 0.0033491 4.031000e-03 6.346500e-03 1.360000e-02 8.499770e-02 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.726614e-01 2.959227e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.726627e-01 2.958965e-01 0.0000000 2.097096e-01 4.628676e-01 7.289169e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.143522e-01 2.578726e-01 0.0024590 1.776300e-02 9.326400e-02 3.368800e-01 9.975410e-01 ▇▂▁▁▁
numeric AF_reference 110116 0.988131 NA NA NA NA NA NA NA 2.152675e-01 2.496829e-01 0.0000000 1.497600e-02 1.116210e-01 3.364620e-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 0.0042427 0.0061797 0.4899999 0.4923616 0.624399 0.7821490 NA
1 54676 rs2462492 C T 0.0023521 0.0061080 0.6999999 0.7001775 0.400301 NA NA
1 86028 rs114608975 T C -0.0291183 0.0097707 0.0029000 0.0028808 0.103610 0.0277556 NA
1 91536 rs6702460 G T 0.0050695 0.0060108 0.4000000 0.3990062 0.457291 0.4207270 NA
1 234313 rs8179466 C T -0.0051504 0.0118437 0.6600001 0.6636635 0.074584 NA NA
1 534192 rs6680723 C T 0.0042843 0.0068741 0.5300002 0.5331167 0.241523 NA NA
1 546697 rs12025928 A G 0.0167411 0.0086193 0.0519996 0.0521031 0.913947 NA NA
1 693731 rs12238997 A G -0.0000882 0.0057669 0.9900000 0.9877979 0.115983 0.1417730 NA
1 705882 rs72631875 G A -0.0086805 0.0084952 0.3100002 0.3068697 0.066648 0.0315495 NA
1 706368 rs55727773 A G -0.0056842 0.0042750 0.1800002 0.1836378 0.514667 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0040555 0.0051662 0.4299995 0.4324537 0.137559 0.2052720 NA
22 51219387 rs9616832 T C -0.0027997 0.0067009 0.6800001 0.6760882 0.073374 0.0654952 NA
22 51219704 rs147475742 G A -0.0066770 0.0089776 0.4600002 0.4570338 0.041777 0.0473243 NA
22 51221190 rs369304721 G A -0.0033560 0.0089789 0.7099994 0.7085749 0.049355 NA NA
22 51221731 rs115055839 T C -0.0025299 0.0067052 0.7099994 0.7059452 0.072865 0.0625000 NA
22 51222100 rs114553188 G T -0.0058715 0.0078904 0.4600002 0.4567981 0.054352 0.0880591 NA
22 51223637 rs375798137 G A -0.0064036 0.0079278 0.4199997 0.4192412 0.053978 0.0788738 NA
22 51229805 rs9616985 T C -0.0024510 0.0067269 0.7199992 0.7155941 0.072740 0.0730831 NA
22 51232488 rs376461333 A G -0.0241597 0.0159380 0.1299999 0.1295560 0.019880 NA NA
22 51237063 rs3896457 T C -0.0009328 0.0041055 0.8200001 0.8202558 0.298766 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624399 ES:SE:LP:AF:ID  0.00424274:0.00617973:0.309804:0.624399:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400301 ES:SE:LP:AF:ID  0.00235207:0.00610799:0.154902:0.400301:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10361  ES:SE:LP:AF:ID  -0.0291183:0.00977066:2.5376:0.10361:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457291 ES:SE:LP:AF:ID  0.00506946:0.00601076:0.39794:0.457291:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074584 ES:SE:LP:AF:ID  -0.00515036:0.0118437:0.180456:0.074584:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241523 ES:SE:LP:AF:ID  0.00428432:0.0068741:0.275724:0.241523:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913947 ES:SE:LP:AF:ID  0.0167411:0.0086193:1.284:0.913947:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115983 ES:SE:LP:AF:ID  -8.81963e-05:0.00576686:0.00436481:0.115983:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066648 ES:SE:LP:AF:ID  -0.00868046:0.00849516:0.508638:0.066648:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514667 ES:SE:LP:AF:ID  -0.00568416:0.00427497:0.744727:0.514667:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03322  ES:SE:LP:AF:ID  -0.00893386:0.0107228:0.39794:0.03322:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03685  ES:SE:LP:AF:ID  -0.00892705:0.00974274:0.443698:0.03685:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036958 ES:SE:LP:AF:ID  -0.0093612:0.00970774:0.481486:0.036958:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036653 ES:SE:LP:AF:ID  -0.00914405:0.00977692:0.455932:0.036653:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016524 ES:SE:LP:AF:ID  -0.0179439:0.0149886:0.638272:0.016524:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037207 ES:SE:LP:AF:ID  -0.00953707:0.00966577:0.49485:0.037207:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037311 ES:SE:LP:AF:ID  -0.00875618:0.00963178:0.443698:0.037311:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100835 ES:SE:LP:AF:ID  -0.00517404:0.00705375:0.337242:0.100835:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958734 ES:SE:LP:AF:ID  0.011698:0.00927918:0.677781:0.958734:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031399 ES:SE:LP:AF:ID  -0.0154516:0.0169176:0.443698:0.031399:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053241 ES:SE:LP:AF:ID  0.0166024:0.0134992:0.657577:0.053241:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036859 ES:SE:LP:AF:ID  -0.00981418:0.00969271:0.508638:0.036859:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037096 ES:SE:LP:AF:ID  -0.00989333:0.0096156:0.522879:0.037096:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843007 ES:SE:LP:AF:ID  0.00398821:0.00498324:0.376751:0.843007:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055806 ES:SE:LP:AF:ID  -0.000510236:0.0081057:0.0222764:0.055806:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122404 ES:SE:LP:AF:ID  0.000183773:0.00545531:0.0132283:0.122404:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025743 ES:SE:LP:AF:ID  0.00770734:0.013449:0.244125:0.025743:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121637 ES:SE:LP:AF:ID  0.000491231:0.00545741:0.0315171:0.121637:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132333 ES:SE:LP:AF:ID  -0.00255238:0.00539058:0.19382:0.132333:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011071 ES:SE:LP:AF:ID  0.00161994:0.0197106:0.0315171:0.011071:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005717 ES:SE:LP:AF:ID  3.70877e-05:0.0253392:-0:0.005717:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037106 ES:SE:LP:AF:ID  -0.00795304:0.00950414:0.39794:0.037106:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838928 ES:SE:LP:AF:ID  0.00400397:0.00483305:0.387216:0.838928:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838561 ES:SE:LP:AF:ID  0.0042458:0.00482727:0.420216:0.838561:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869728 ES:SE:LP:AF:ID  0.00127408:0.0051783:0.091515:0.869728:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129988 ES:SE:LP:AF:ID  -0.00146464:0.00518729:0.107905:0.129988:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037578 ES:SE:LP:AF:ID  -0.00918152:0.00934855:0.481486:0.037578:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037841 ES:SE:LP:AF:ID  -0.00878255:0.00928692:0.468521:0.037841:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869064 ES:SE:LP:AF:ID  0.00175295:0.00516755:0.136677:0.869064:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86916  ES:SE:LP:AF:ID  0.00169472:0.00516927:0.130768:0.86916:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037791 ES:SE:LP:AF:ID  -0.0082468:0.00932729:0.420216:0.037791:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869071 ES:SE:LP:AF:ID  0.00175166:0.00516763:0.136677:0.869071:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.004885 ES:SE:LP:AF:ID  0.0261926:0.0272327:0.468521:0.004885:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.004847 ES:SE:LP:AF:ID  0.0247651:0.0273025:0.443698:0.004847:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837999 ES:SE:LP:AF:ID  0.00460026:0.00481432:0.468521:0.837999:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037809 ES:SE:LP:AF:ID  -0.0080993:0.00934045:0.408935:0.037809:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838613 ES:SE:LP:AF:ID  0.00442045:0.00482763:0.443698:0.838613:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013929 ES:SE:LP:AF:ID  -0.0134392:0.0167676:0.376751:0.013929:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.00551  ES:SE:LP:AF:ID  0.0308513:0.0261516:0.619789:0.00551:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839774 ES:SE:LP:AF:ID  0.00363035:0.00489296:0.337242:0.839774:rs3131965