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-7432/UKB-b-7432_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7432/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7432/UKB-b-7432_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: 0.0076 (0.0012)
Lambda GC: 1.0874
Mean Chi^2: 1.0855
Intercept: 1.0169 (0.006)
Ratio: 0.1977 (0.0703)
Analysis finished at Thu Oct 17 14:42:52 2019
Total time elapsed: 2.0m:35.06s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "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": 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": 0.0076,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0169,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0874,
    "ldsc_mean_chisq": 1.0855,
    "ldsc_ratio": 0.1977
}

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 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 -3.110000e-05 3.368800e-03 -0.0758480 -1.037000e-03 -1.030000e-05 1.000900e-03 5.081940e-02 ▁▁▇▆▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.416200e-03 2.287200e-03 0.0006760 8.276000e-04 1.387900e-03 3.202400e-03 3.552690e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.907116e-01 2.910695e-01 0.0000002 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.907113e-01 2.910424e-01 0.0000002 2.361628e-01 4.871985e-01 7.428660e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035076e-01 2.568623e-01 0.0009900 1.316800e-02 7.791300e-02 3.164508e-01 9.990070e-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 0.0010293 0.0012441 0.4100001 0.4080522 0.623745 0.7821490 NA
1 54676 rs2462492 C T -0.0007921 0.0012325 0.5199996 0.5204517 0.400397 NA NA
1 86028 rs114608975 T C 0.0030272 0.0019705 0.1199999 0.1244646 0.103557 0.0277556 NA
1 91536 rs6702460 G T -0.0005673 0.0012136 0.6400000 0.6401831 0.456832 0.4207270 NA
1 234313 rs8179466 C T 0.0003273 0.0023917 0.8900000 0.8911398 0.074534 NA NA
1 534192 rs6680723 C T 0.0033332 0.0013863 0.0160000 0.0162022 0.240965 NA NA
1 546697 rs12025928 A G -0.0020557 0.0017292 0.2300001 0.2345132 0.913466 NA NA
1 693731 rs12238997 A G -0.0001187 0.0011614 0.9199999 0.9186247 0.116356 0.1417730 NA
1 705882 rs72631875 G A 0.0018411 0.0017020 0.2800000 0.2793817 0.067295 0.0315495 NA
1 706368 rs55727773 A G 0.0010337 0.0008605 0.2300001 0.2296553 0.515617 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0007454 0.0018055 0.6800001 0.6797281 0.041955 0.0473243 NA
22 51219766 rs182321900 C T 0.0084909 0.0084248 0.3100002 0.3135308 0.001932 NA NA
22 51220146 rs868950473 C T 0.0103039 0.0083440 0.2200002 0.2168746 0.001981 NA NA
22 51221190 rs369304721 G A -0.0007340 0.0018029 0.6800001 0.6839250 0.049724 NA NA
22 51221731 rs115055839 T C 0.0000240 0.0013483 0.9900000 0.9857814 0.073237 0.0625000 NA
22 51222100 rs114553188 G T -0.0009669 0.0015868 0.5400003 0.5423067 0.054485 0.0880591 NA
22 51223637 rs375798137 G A -0.0009905 0.0015945 0.5300002 0.5344623 0.054114 0.0788738 NA
22 51229805 rs9616985 T C -0.0000977 0.0013532 0.9400001 0.9424566 0.073071 0.0730831 NA
22 51232488 rs376461333 A G -0.0045636 0.0031868 0.1499999 0.1521255 0.020053 NA NA
22 51237063 rs3896457 T C -0.0000077 0.0008276 0.9900000 0.9925409 0.297979 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623745 ES:SE:LP:AF:ID  0.00102926:0.00124408:0.387216:0.623745:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400397 ES:SE:LP:AF:ID  -0.000792091:0.00123254:0.283997:0.400397:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  0.00302725:0.00197048:0.920819:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456832 ES:SE:LP:AF:ID  -0.000567312:0.00121365:0.19382:0.456832:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074534 ES:SE:LP:AF:ID  0.000327333:0.0023917:0.05061:0.074534:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  0.00333317:0.00138632:1.79588:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913466 ES:SE:LP:AF:ID  -0.00205566:0.00172917:0.638272:0.913466:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116356 ES:SE:LP:AF:ID  -0.000118661:0.00116145:0.0362122:0.116356:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067295 ES:SE:LP:AF:ID  0.00184108:0.00170201:0.552842:0.067295:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515617 ES:SE:LP:AF:ID  0.00103369:0.000860514:0.638272:0.515617:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032986 ES:SE:LP:AF:ID  -0.00555795:0.0021701:2:0.032986:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036604 ES:SE:LP:AF:ID  -0.00517178:0.001971:2.06048:0.036604:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03672  ES:SE:LP:AF:ID  -0.00515008:0.00196354:2.06048:0.03672:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03642  ES:SE:LP:AF:ID  -0.00522132:0.00197769:2.08092:0.03642:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016408 ES:SE:LP:AF:ID  -0.0044952:0.00304435:0.853872:0.016408:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036959 ES:SE:LP:AF:ID  -0.00520347:0.00195576:2.10791:0.036959:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037055 ES:SE:LP:AF:ID  -0.00534316:0.0019491:2.21467:0.037055:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101227 ES:SE:LP:AF:ID  -0.00275227:0.00141943:1.27572:0.101227:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959115 ES:SE:LP:AF:ID  0.00509621:0.00187997:2.17393:0.959115:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  0.00375215:0.00341167:0.568636:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053279 ES:SE:LP:AF:ID  -0.000458002:0.00271241:0.0604807:0.053279:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036573 ES:SE:LP:AF:ID  -0.00530992:0.00196169:2.16749:0.036573:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03689  ES:SE:LP:AF:ID  -0.0048726:0.0019438:1.92082:0.03689:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843203 ES:SE:LP:AF:ID  0.00160771:0.0010067:0.958607:0.843203:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055932 ES:SE:LP:AF:ID  0.000327983:0.00162973:0.0757207:0.055932:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122335 ES:SE:LP:AF:ID  -0.000185182:0.00110179:0.0604807:0.122335:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025702 ES:SE:LP:AF:ID  -0.000603838:0.00271087:0.0861861:0.025702:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121579 ES:SE:LP:AF:ID  -0.000160365:0.00110225:0.0555173:0.121579:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132339 ES:SE:LP:AF:ID  -0.000949684:0.00108647:0.420216:0.132339:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011128 ES:SE:LP:AF:ID  0.00229217:0.00395233:0.251812:0.011128:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005707 ES:SE:LP:AF:ID  0.000310959:0.00509738:0.0222764:0.005707:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002266 ES:SE:LP:AF:ID  0.00875857:0.00858242:0.508638:0.002266:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.00103  ES:SE:LP:AF:ID  -0.0205724:0.0140386:0.853872:0.00103:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036804 ES:SE:LP:AF:ID  -0.00548709:0.00192419:2.36653:0.036804:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838937 ES:SE:LP:AF:ID  0.00118301:0.0009749:0.657577:0.838937:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838565 ES:SE:LP:AF:ID  0.00125765:0.00097385:0.69897:0.838565:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869747 ES:SE:LP:AF:ID  -0.000189615:0.00104491:0.0655015:0.869747:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129907 ES:SE:LP:AF:ID  4.06137e-05:0.00104702:0.0132283:0.129907:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037315 ES:SE:LP:AF:ID  -0.00497289:0.00189154:2.0655:0.037315:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037559 ES:SE:LP:AF:ID  -0.00493587:0.00187957:2.0655:0.037559:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869088 ES:SE:LP:AF:ID  -0.000115236:0.00104285:0.0409586:0.869088:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869182 ES:SE:LP:AF:ID  -0.000115036:0.00104326:0.0409586:0.869182:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037517 ES:SE:LP:AF:ID  -0.00512954:0.00188771:2.18046:0.037517:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869091 ES:SE:LP:AF:ID  -0.000110085:0.00104283:0.0362122:0.869091:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005127 ES:SE:LP:AF:ID  0.000765362:0.00535214:0.05061:0.005127:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005093 ES:SE:LP:AF:ID  0.000962584:0.00536618:0.0655015:0.005093:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838016 ES:SE:LP:AF:ID  0.00120116:0.000971135:0.657577:0.838016:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037529 ES:SE:LP:AF:ID  -0.00519409:0.00189037:2.22185:0.037529:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838647 ES:SE:LP:AF:ID  0.00115498:0.000973866:0.619789:0.838647:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013784 ES:SE:LP:AF:ID  -0.0011959:0.00339813:0.142668:0.013784:rs181660517