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-5379/UKB-b-5379_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5379/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5379/UKB-b-5379_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: 0.0374 (0.002)
Lambda GC: 1.3503
Mean Chi^2: 1.4126
Intercept: 1.0747 (0.0085)
Ratio: 0.181 (0.0205)
Analysis finished at Thu Oct 17 14:46:54 2019
Total time elapsed: 1.0m:38.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 23,
    "n_p_sig": 1410,
    "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": 0.0374,
    "ldsc_observed_scale_h2_se": 0.002,
    "ldsc_intercept_beta": 1.0747,
    "ldsc_intercept_se": 0.0085,
    "ldsc_lambda_gc": 1.3503,
    "ldsc_mean_chisq": 1.4126,
    "ldsc_ratio": 0.181
}

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 2.206000e-04 1.170400e-02 -0.2080350 -3.635200e-03 5.340000e-05 3.818700e-03 1.641250e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.979700e-03 7.554200e-03 0.0022328 2.733300e-03 4.583400e-03 1.057580e-02 1.174630e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.627195e-01 2.984067e-01 0.0000000 1.900002e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.627206e-01 2.983815e-01 0.0000000 1.945409e-01 4.492963e-01 7.208536e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035075e-01 2.568626e-01 0.0009870 1.316900e-02 7.791400e-02 3.164580e-01 9.990090e-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 0.0012260 0.0041071 0.7700005 0.7653144 0.623762 0.7821490 NA
1 54676 rs2462492 C T -0.0021414 0.0040690 0.5999997 0.5986977 0.400434 NA NA
1 86028 rs114608975 T C 0.0010168 0.0065059 0.8800001 0.8758049 0.103552 0.0277556 NA
1 91536 rs6702460 G T 0.0008927 0.0040063 0.8200001 0.8236769 0.456848 0.4207270 NA
1 234313 rs8179466 C T 0.0069095 0.0078994 0.3800004 0.3817458 0.074510 NA NA
1 534192 rs6680723 C T 0.0011081 0.0045761 0.8100000 0.8086619 0.240978 NA NA
1 546697 rs12025928 A G 0.0015266 0.0057093 0.7899998 0.7891728 0.913470 NA NA
1 693731 rs12238997 A G -0.0000316 0.0038349 0.9900000 0.9934312 0.116346 0.1417730 NA
1 705882 rs72631875 G A 0.0028208 0.0056211 0.6200004 0.6157879 0.067265 0.0315495 NA
1 706368 rs55727773 A G -0.0054720 0.0028412 0.0539995 0.0541115 0.515660 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0089469 0.0059657 0.1299999 0.1336856 0.041939 0.0473243 NA
22 51219766 rs182321900 C T -0.0061250 0.0277991 0.8300000 0.8256135 0.001936 NA NA
22 51220146 rs868950473 C T 0.0036183 0.0275319 0.9000000 0.8954403 0.001985 NA NA
22 51221190 rs369304721 G A 0.0076936 0.0059556 0.2000000 0.1964168 0.049724 NA NA
22 51221731 rs115055839 T C 0.0041719 0.0044544 0.3500000 0.3489805 0.073222 0.0625000 NA
22 51222100 rs114553188 G T -0.0002633 0.0052454 0.9599999 0.9599633 0.054421 0.0880591 NA
22 51223637 rs375798137 G A -0.0004816 0.0052708 0.9299999 0.9272047 0.054051 0.0788738 NA
22 51229805 rs9616985 T C 0.0039071 0.0044706 0.3800004 0.3821415 0.073058 0.0730831 NA
22 51232488 rs376461333 A G 0.0004614 0.0105388 0.9699999 0.9650779 0.020021 NA NA
22 51237063 rs3896457 T C 0.0012735 0.0027340 0.6400000 0.6413513 0.297972 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  0.00122602:0.00410714:0.113509:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400434 ES:SE:LP:AF:ID  -0.00214142:0.00406902:0.221849:0.400434:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103552 ES:SE:LP:AF:ID  0.0010168:0.00650588:0.0555173:0.103552:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456848 ES:SE:LP:AF:ID  0.000892677:0.0040063:0.0861861:0.456848:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07451  ES:SE:LP:AF:ID  0.00690948:0.0078994:0.420216:0.07451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240978 ES:SE:LP:AF:ID  0.00110811:0.00457608:0.091515:0.240978:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91347  ES:SE:LP:AF:ID  0.00152657:0.00570926:0.102373:0.91347:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116346 ES:SE:LP:AF:ID  -3.15721e-05:0.0038349:0.00436481:0.116346:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067265 ES:SE:LP:AF:ID  0.00282084:0.00562112:0.207608:0.067265:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51566  ES:SE:LP:AF:ID  -0.00547197:0.00284119:1.26761:0.51566:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033002 ES:SE:LP:AF:ID  -0.000586062:0.00716283:0.0315171:0.033002:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03662  ES:SE:LP:AF:ID  0.00110493:0.00650599:0.0604807:0.03662:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036737 ES:SE:LP:AF:ID  0.000986512:0.00648132:0.0555173:0.036737:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036435 ES:SE:LP:AF:ID  0.00202993:0.00652818:0.119186:0.036435:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016401 ES:SE:LP:AF:ID  -0.00480469:0.0100543:0.200659:0.016401:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036973 ES:SE:LP:AF:ID  0.00190505:0.00645592:0.113509:0.036973:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03707  ES:SE:LP:AF:ID  0.00194276:0.00643379:0.119186:0.03707:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101187 ES:SE:LP:AF:ID  0.00901795:0.00468756:1.26761:0.101187:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959104 ES:SE:LP:AF:ID  -0.00119769:0.00620562:0.0705811:0.959104:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  -0.0167155:0.0112644:0.853872:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05325  ES:SE:LP:AF:ID  -0.003508:0.00896069:0.154902:0.05325:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036588 ES:SE:LP:AF:ID  0.00156122:0.0064754:0.091515:0.036588:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036903 ES:SE:LP:AF:ID  0.00087615:0.00641653:0.05061:0.036903:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.8432   ES:SE:LP:AF:ID  -0.000324882:0.00332362:0.0362122:0.8432:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05593  ES:SE:LP:AF:ID  0.000132718:0.00538117:0.00877392:0.05593:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122335 ES:SE:LP:AF:ID  0.0016825:0.0036376:0.19382:0.122335:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025697 ES:SE:LP:AF:ID  -0.00336249:0.00895161:0.148742:0.025697:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121578 ES:SE:LP:AF:ID  0.00138164:0.00363914:0.154902:0.121578:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132353 ES:SE:LP:AF:ID  0.00108086:0.00358721:0.119186:0.132353:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01114  ES:SE:LP:AF:ID  0.0117889:0.0130364:0.431798:0.01114:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005705 ES:SE:LP:AF:ID  -0.0048849:0.0168282:0.113509:0.005705:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002266 ES:SE:LP:AF:ID  -0.0453575:0.0283264:0.958607:0.002266:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001027 ES:SE:LP:AF:ID  -0.0234094:0.0464453:0.21467:0.001027:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036819 ES:SE:LP:AF:ID  0.00136334:0.0063515:0.0809219:0.036819:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838936 ES:SE:LP:AF:ID  0.0024129:0.00321875:0.346787:0.838936:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838567 ES:SE:LP:AF:ID  0.0023364:0.00321531:0.327902:0.838567:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86976  ES:SE:LP:AF:ID  0.00174791:0.00345005:0.21467:0.86976:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129887 ES:SE:LP:AF:ID  -0.000844272:0.00345711:0.091515:0.129887:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03733  ES:SE:LP:AF:ID  0.00128022:0.00624385:0.0757207:0.03733:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037574 ES:SE:LP:AF:ID  0.00159657:0.00620437:0.09691:0.037574:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869105 ES:SE:LP:AF:ID  0.00158293:0.00344333:0.187087:0.869105:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869202 ES:SE:LP:AF:ID  0.00173519:0.0034447:0.21467:0.869202:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037532 ES:SE:LP:AF:ID  0.00136956:0.00623121:0.0809219:0.037532:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869107 ES:SE:LP:AF:ID  0.00160354:0.00344327:0.19382:0.869107:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005123 ES:SE:LP:AF:ID  -0.019478:0.0176799:0.568636:0.005123:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  -0.0198709:0.0177264:0.585027:0.005088:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83802  ES:SE:LP:AF:ID  0.00206983:0.00320641:0.283997:0.83802:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  0.00181325:0.00623999:0.113509:0.037545:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838651 ES:SE:LP:AF:ID  0.00209566:0.00321543:0.29243:0.838651:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  0.00124521:0.0112222:0.0409586:0.013776:rs181660517