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-14746/UKB-b-14746_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14746/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14746/UKB-b-14746_data.vcf.gz ...
Read summary statistics for 8625007 SNPs.
Dropped 7372 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, 1285750 SNPs remain.
After merging with regression SNP LD, 1285750 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0092 (0.0075)
Lambda GC: 1.0088
Mean Chi^2: 1.0063
Intercept: 0.9945 (0.0064)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:45:21 2019
Total time elapsed: 1.0m:35.25s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": 7.9356e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 14,
    "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": 83095,
    "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": 1285750,
    "ldsc_nsnp_merge_regression_ld": 1285750,
    "ldsc_observed_scale_h2_beta": 0.0092,
    "ldsc_observed_scale_h2_se": 0.0075,
    "ldsc_intercept_beta": 0.9945,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0088,
    "ldsc_mean_chisq": 1.0063,
    "ldsc_ratio": -0.873
}

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 8617669 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 8625007 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 8.650339e+00 5.760985e+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 7.877012e+07 5.637161e+07 828.0000000 3.238547e+07 6.929207e+07 1.145687e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.900000e-06 1.796400e-03 -0.0151054 -7.727000e-04 -2.350000e-05 7.163000e-04 2.435010e-02 ▁▇▃▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.478800e-03 1.009400e-03 0.0005873 6.916000e-04 1.019800e-03 1.999000e-03 1.012370e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.988974e-01 2.883049e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.988985e-01 2.882795e-01 0.0000000 2.494247e-01 4.973670e-01 7.486513e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291168e-01 2.594882e-01 0.0053900 2.518900e-02 1.138960e-01 3.626200e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83095 0.9903658 NA NA NA NA NA NA NA 2.288660e-01 2.514589e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 0.0006904 0.0010824 0.5199996 0.5235915 0.623818 0.7821490 NA
1 54676 rs2462492 C T 0.0003098 0.0010792 0.7700005 0.7740318 0.399149 NA NA
1 86028 rs114608975 T C -0.0015042 0.0017180 0.3800004 0.3812695 0.103531 0.0277556 NA
1 91536 rs6702460 G T -0.0006113 0.0010615 0.5600000 0.5646991 0.455911 0.4207270 NA
1 234313 rs8179466 C T -0.0010095 0.0020994 0.6300007 0.6306184 0.074452 NA NA
1 534192 rs6680723 C T -0.0030993 0.0012090 0.0100000 0.0103620 0.242049 NA NA
1 546697 rs12025928 A G 0.0003251 0.0015001 0.8300000 0.8284269 0.912857 NA NA
1 693731 rs12238997 A G -0.0002602 0.0010081 0.8000000 0.7963208 0.117325 0.1417730 NA
1 705882 rs72631875 G A -0.0014057 0.0014694 0.3400001 0.3387442 0.067697 0.0315495 NA
1 706368 rs55727773 A G 0.0000645 0.0007483 0.9299999 0.9313365 0.513303 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0009168 0.0009101 0.3100002 0.3137646 0.136330 0.2052720 NA
22 51219387 rs9616832 T C 0.0006722 0.0011862 0.5700002 0.5709094 0.071802 0.0654952 NA
22 51219704 rs147475742 G A -0.0011889 0.0015779 0.4500005 0.4511467 0.041197 0.0473243 NA
22 51221190 rs369304721 G A 0.0003872 0.0015891 0.8100000 0.8075210 0.048376 NA NA
22 51221731 rs115055839 T C 0.0006991 0.0011864 0.5600000 0.5556747 0.071352 0.0625000 NA
22 51222100 rs114553188 G T 0.0015214 0.0013748 0.2700001 0.2684548 0.054860 0.0880591 NA
22 51223637 rs375798137 G A 0.0015557 0.0013820 0.2599998 0.2602841 0.054479 0.0788738 NA
22 51229805 rs9616985 T C 0.0006457 0.0011901 0.5900000 0.5874487 0.071257 0.0730831 NA
22 51232488 rs376461333 A G 0.0005479 0.0027409 0.8400000 0.8415710 0.020463 NA NA
22 51237063 rs3896457 T C -0.0007704 0.0007185 0.2800000 0.2835992 0.298406 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623818 ES:SE:LP:AF:ID  0.000690388:0.00108242:0.283997:0.623818:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399149 ES:SE:LP:AF:ID  0.000309841:0.00107919:0.113509:0.399149:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103531 ES:SE:LP:AF:ID  -0.00150422:0.00171801:0.420216:0.103531:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455911 ES:SE:LP:AF:ID  -0.000611275:0.00106147:0.251812:0.455911:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074452 ES:SE:LP:AF:ID  -0.00100952:0.00209942:0.200659:0.074452:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242049 ES:SE:LP:AF:ID  -0.00309931:0.00120901:2:0.242049:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912857 ES:SE:LP:AF:ID  0.000325101:0.0015001:0.0809219:0.912857:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117325 ES:SE:LP:AF:ID  -0.000260192:0.00100806:0.09691:0.117325:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067697 ES:SE:LP:AF:ID  -0.00140572:0.00146942:0.468521:0.067697:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513303 ES:SE:LP:AF:ID  6.44744e-05:0.00074828:0.0315171:0.513303:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033683 ES:SE:LP:AF:ID  -0.000462836:0.00186498:0.09691:0.033683:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037464 ES:SE:LP:AF:ID  -0.00032504:0.00169144:0.0705811:0.037464:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03765  ES:SE:LP:AF:ID  -0.000304444:0.00168259:0.0655015:0.03765:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037227 ES:SE:LP:AF:ID  -0.00042985:0.00169797:0.09691:0.037227:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016277 ES:SE:LP:AF:ID  0.000531762:0.00266409:0.0757207:0.016277:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037867 ES:SE:LP:AF:ID  -0.000267485:0.00167684:0.0604807:0.037867:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037961 ES:SE:LP:AF:ID  -0.000259005:0.00167152:0.0555173:0.037961:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102729 ES:SE:LP:AF:ID  -0.000301027:0.0012211:0.091515:0.102729:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958083 ES:SE:LP:AF:ID  -0.00034225:0.00161444:0.0809219:0.958083:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031693 ES:SE:LP:AF:ID  -0.00140085:0.0029563:0.19382:0.031693:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052723 ES:SE:LP:AF:ID  -0.00188514:0.00238129:0.366532:0.052723:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037455 ES:SE:LP:AF:ID  -0.00032353:0.0016825:0.0705811:0.037455:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037724 ES:SE:LP:AF:ID  -0.000885005:0.00166856:0.221849:0.037724:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84143  ES:SE:LP:AF:ID  0.00034483:0.000871795:0.161151:0.84143:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056343 ES:SE:LP:AF:ID  0.000249574:0.00141611:0.0655015:0.056343:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123083 ES:SE:LP:AF:ID  -0.000399103:0.000957557:0.167491:0.123083:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025115 ES:SE:LP:AF:ID  -0.00570304:0.00238561:1.76955:0.025115:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122335 ES:SE:LP:AF:ID  -0.000382843:0.000957866:0.161151:0.122335:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134154 ES:SE:LP:AF:ID  -0.000623389:0.000940284:0.29243:0.134154:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011559 ES:SE:LP:AF:ID  0.000656969:0.00335106:0.0757207:0.011559:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006101 ES:SE:LP:AF:ID  -0.00221316:0.00425544:0.221849:0.006101:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037606 ES:SE:LP:AF:ID  -0.000633974:0.0016531:0.154902:0.037606:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837017 ES:SE:LP:AF:ID  0.000465884:0.000843353:0.236572:0.837017:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836721 ES:SE:LP:AF:ID  0.000490427:0.000842734:0.251812:0.836721:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868556 ES:SE:LP:AF:ID  0.000235666:0.000905564:0.102373:0.868556:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131011 ES:SE:LP:AF:ID  -0.000271877:0.00090789:0.119186:0.131011:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038052 ES:SE:LP:AF:ID  -0.000653733:0.00162717:0.161151:0.038052:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038298 ES:SE:LP:AF:ID  -0.000660465:0.00161708:0.167491:0.038298:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867969 ES:SE:LP:AF:ID  0.000336506:0.000904108:0.148742:0.867969:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868043 ES:SE:LP:AF:ID  0.000468585:0.000904478:0.221849:0.868043:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038206 ES:SE:LP:AF:ID  -0.000585253:0.00162455:0.142668:0.038206:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86798  ES:SE:LP:AF:ID  0.000338271:0.000904085:0.148742:0.86798:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  0.00120398:0.00453098:0.102373:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836147 ES:SE:LP:AF:ID  0.000500855:0.000840268:0.259637:0.836147:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038209 ES:SE:LP:AF:ID  -0.000694871:0.00162692:0.173925:0.038209:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836781 ES:SE:LP:AF:ID  0.000485932:0.00084257:0.251812:0.836781:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013032 ES:SE:LP:AF:ID  -0.00313327:0.00304817:0.522879:0.013032:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005663 ES:SE:LP:AF:ID  0.00513782:0.00452504:0.585027:0.005663:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838098 ES:SE:LP:AF:ID  0.000426582:0.000854432:0.207608:0.838098:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868221 ES:SE:LP:AF:ID  0.00030731:0.000902921:0.136677:0.868221:rs3115858