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-13952/UKB-b-13952_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13952/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13952/UKB-b-13952_data.vcf.gz ...
Read summary statistics for 5997538 SNPs.
Dropped 2739 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, 1214505 SNPs remain.
After merging with regression SNP LD, 1214505 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.009 (0.0017)
Lambda GC: 1.0925
Mean Chi^2: 1.1008
Intercept: 1.0354 (0.0079)
Ratio: 0.3512 (0.0785)
Analysis finished at Thu Oct 17 14:44:13 2019
Total time elapsed: 1.0m:9.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9245,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -3.176e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 66,
    "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": 54228,
    "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": 1214505,
    "ldsc_nsnp_merge_regression_ld": 1214505,
    "ldsc_observed_scale_h2_beta": 0.009,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.0354,
    "ldsc_intercept_se": 0.0079,
    "ldsc_lambda_gc": 1.0925,
    "ldsc_mean_chisq": 1.1008,
    "ldsc_ratio": 0.3512
}

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 5994818 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 5997538 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 8.670870e+00 5.762115e+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 7.857630e+07 5.652191e+07 828.0000000 3.198813e+07 6.901738e+07 1.144891e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.200000e-06 6.327000e-04 -0.0057983 -3.807000e-04 -2.300000e-06 3.731000e-04 6.875000e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.762000e-04 1.932000e-04 0.0003775 4.172000e-04 5.009000e-04 6.892000e-04 1.982800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.862136e-01 2.928497e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.862125e-01 2.928232e-01 0.0000000 2.286432e-01 4.808822e-01 7.401827e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.118388e-01 2.533363e-01 0.0338990 9.701600e-02 2.297540e-01 4.771150e-01 9.661010e-01 ▇▃▂▂▁
numeric AF_reference 54228 0.9909583 NA NA NA NA NA NA NA 3.083287e-01 2.465001e-01 0.0000000 1.058310e-01 2.374200e-01 4.676520e-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 -0.0001391 0.0006949 0.8400000 0.8413941 0.623834 0.7821490 NA
1 54676 rs2462492 C T -0.0015991 0.0006877 0.0200000 0.0200633 0.400313 NA NA
1 86028 rs114608975 T C 0.0005676 0.0011004 0.6100002 0.6059824 0.103529 0.0277556 NA
1 91536 rs6702460 G T -0.0012208 0.0006778 0.0719996 0.0716827 0.456724 0.4207270 NA
1 234313 rs8179466 C T 0.0016686 0.0013337 0.2099999 0.2108999 0.074563 NA NA
1 534192 rs6680723 C T 0.0007509 0.0007743 0.3300000 0.3321503 0.240909 NA NA
1 546697 rs12025928 A G 0.0008835 0.0009668 0.3599996 0.3607751 0.913556 NA NA
1 693731 rs12238997 A G 0.0005576 0.0006490 0.3900004 0.3902307 0.116139 0.1417730 NA
1 705882 rs72631875 G A -0.0000751 0.0009533 0.9400001 0.9372160 0.067038 0.0315495 NA
1 706368 rs55727773 A G -0.0002778 0.0004806 0.5600000 0.5633463 0.515699 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0001395 0.0007500 0.8499999 0.8524551 0.073855 0.0826677 NA
22 51219006 rs28729663 G A 0.0004351 0.0005803 0.4500005 0.4533240 0.137851 0.2052720 NA
22 51219387 rs9616832 T C -0.0001156 0.0007515 0.8800001 0.8777828 0.073985 0.0654952 NA
22 51219704 rs147475742 G A 0.0002069 0.0010071 0.8400000 0.8372034 0.042096 0.0473243 NA
22 51221190 rs369304721 G A -0.0000919 0.0010056 0.9299999 0.9271826 0.049828 NA NA
22 51221731 rs115055839 T C -0.0001584 0.0007520 0.8300000 0.8331845 0.073461 0.0625000 NA
22 51222100 rs114553188 G T 0.0010640 0.0008896 0.2300001 0.2317125 0.054174 0.0880591 NA
22 51223637 rs375798137 G A 0.0010640 0.0008939 0.2300001 0.2339160 0.053807 0.0788738 NA
22 51229805 rs9616985 T C -0.0001991 0.0007546 0.7899998 0.7919026 0.073309 0.0730831 NA
22 51237063 rs3896457 T C 0.0006789 0.0004622 0.1400000 0.1418442 0.298079 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623834 ES:SE:LP:AF:ID  -0.000139057:0.000694901:0.0757207:0.623834:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400313 ES:SE:LP:AF:ID  -0.00159907:0.000687724:1.69897:0.400313:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103529 ES:SE:LP:AF:ID  0.000567615:0.00110042:0.21467:0.103529:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456724 ES:SE:LP:AF:ID  -0.00122079:0.000677792:1.14267:0.456724:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074563 ES:SE:LP:AF:ID  0.00166861:0.00133372:0.677781:0.074563:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240909 ES:SE:LP:AF:ID  0.000750871:0.00077426:0.481486:0.240909:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913556 ES:SE:LP:AF:ID  0.000883527:0.000966777:0.443698:0.913556:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116139 ES:SE:LP:AF:ID  0.000557609:0.000648987:0.408935:0.116139:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067038 ES:SE:LP:AF:ID  -7.50912e-05:0.000953304:0.0268721:0.067038:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515699 ES:SE:LP:AF:ID  -0.000277752:0.000480641:0.251812:0.515699:rs12029736
1   715265  rs12184267  C   T   .   PASS    AF=0.036647 ES:SE:LP:AF:ID  -0.000861509:0.00110002:0.366532:0.036647:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036762 ES:SE:LP:AF:ID  -0.000947017:0.0010959:0.408935:0.036762:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036471 ES:SE:LP:AF:ID  -0.000932639:0.00110366:0.39794:0.036471:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.037002 ES:SE:LP:AF:ID  -0.000848199:0.00109158:0.356547:0.037002:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037105 ES:SE:LP:AF:ID  -0.000868021:0.00108775:0.376751:0.037105:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101216 ES:SE:LP:AF:ID  0.000310708:0.000793107:0.154902:0.101216:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959072 ES:SE:LP:AF:ID  0.000654193:0.001049:0.275724:0.959072:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053298 ES:SE:LP:AF:ID  -0.000531168:0.0015141:0.136677:0.053298:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036625 ES:SE:LP:AF:ID  -0.000704713:0.00109468:0.283997:0.036625:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036951 ES:SE:LP:AF:ID  -0.000814217:0.00108458:0.346787:0.036951:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843329 ES:SE:LP:AF:ID  -8.014e-05:0.000562385:0.05061:0.843329:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05566  ES:SE:LP:AF:ID  0.000572965:0.000912146:0.275724:0.05566:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122112 ES:SE:LP:AF:ID  0.000426814:0.000615675:0.309804:0.122112:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12135  ES:SE:LP:AF:ID  0.000401195:0.000615929:0.29243:0.12135:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132152 ES:SE:LP:AF:ID  8.37438e-05:0.000607095:0.05061:0.132152:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036857 ES:SE:LP:AF:ID  -0.000798:0.00107378:0.337242:0.036857:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838962 ES:SE:LP:AF:ID  -0.00012606:0.000544429:0.0861861:0.838962:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838601 ES:SE:LP:AF:ID  -0.000167125:0.000543862:0.119186:0.838601:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869864 ES:SE:LP:AF:ID  -0.000418111:0.000583629:0.327902:0.869864:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129781 ES:SE:LP:AF:ID  0.00044986:0.0005848:0.356547:0.129781:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037369 ES:SE:LP:AF:ID  -0.00102489:0.00105557:0.481486:0.037369:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.0376   ES:SE:LP:AF:ID  -0.000993082:0.00104911:0.468521:0.0376:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  -0.000441461:0.000582512:0.346787:0.869215:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869316 ES:SE:LP:AF:ID  -0.000429927:0.000582755:0.337242:0.869316:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037581 ES:SE:LP:AF:ID  -0.00100892:0.00105333:0.468521:0.037581:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869219 ES:SE:LP:AF:ID  -0.000456396:0.000582508:0.366532:0.869219:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838049 ES:SE:LP:AF:ID  -0.000106107:0.000542353:0.0757207:0.838049:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037589 ES:SE:LP:AF:ID  -0.001009:0.00105494:0.468521:0.037589:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838675 ES:SE:LP:AF:ID  -0.000141967:0.000543889:0.102373:0.838675:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839773 ES:SE:LP:AF:ID  -0.000204822:0.000551176:0.148742:0.839773:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869494 ES:SE:LP:AF:ID  -0.000402183:0.000581813:0.309804:0.869494:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869021 ES:SE:LP:AF:ID  -0.000406989:0.000580306:0.318759:0.869021:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867994 ES:SE:LP:AF:ID  -0.000535624:0.000579239:0.443698:0.867994:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869179 ES:SE:LP:AF:ID  -0.000383193:0.000580806:0.29243:0.869179:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869188 ES:SE:LP:AF:ID  -0.000383621:0.000580851:0.29243:0.869188:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869196 ES:SE:LP:AF:ID  -0.000385568:0.000580863:0.29243:0.869196:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86968  ES:SE:LP:AF:ID  -0.000398642:0.000582479:0.309804:0.86968:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037646 ES:SE:LP:AF:ID  -0.000907667:0.00104861:0.408935:0.037646:rs114525117
1   760912  rs1048488   C   T   .   PASS    AF=0.838304 ES:SE:LP:AF:ID  -5.16652e-05:0.000541294:0.0362122:0.838304:rs1048488
1   760998  rs148828841 C   A   .   PASS    AF=0.037074 ES:SE:LP:AF:ID  -0.000897623:0.00106843:0.39794:0.037074:rs148828841