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-2909/UKB-b-2909_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2909/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2909/UKB-b-2909_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: 0.0422 (0.002)
Lambda GC: 1.326
Mean Chi^2: 1.3943
Intercept: 1.0168 (0.0078)
Ratio: 0.0425 (0.0197)
Analysis finished at Thu Oct 17 14:44:55 2019
Total time elapsed: 1.0m:50.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 16,
    "n_p_sig": 808,
    "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": 0.0422,
    "ldsc_observed_scale_h2_se": 0.002,
    "ldsc_intercept_beta": 1.0168,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.326,
    "ldsc_mean_chisq": 1.3943,
    "ldsc_ratio": 0.0426
}

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 TRUE
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 4.370000e-05 6.037300e-03 -0.1011330 -1.948200e-03 1.110000e-05 1.970800e-03 9.466550e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.253100e-03 4.027300e-03 0.0011898 1.456600e-03 2.442600e-03 5.636200e-03 6.251870e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.676338e-01 2.975872e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.676342e-01 2.975628e-01 0.0000000 2.020148e-01 4.561348e-01 7.252929e-01 9.999996e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035072e-01 2.568639e-01 0.0009860 1.316800e-02 7.791100e-02 3.164570e-01 9.990160e-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 -0.0003291 0.0021892 0.8800001 0.8805109 0.623768 0.7821490 NA
1 54676 rs2462492 C T 0.0026472 0.0021688 0.2200002 0.2222394 0.400421 NA NA
1 86028 rs114608975 T C 0.0041810 0.0034674 0.2300001 0.2278876 0.103561 0.0277556 NA
1 91536 rs6702460 G T -0.0002981 0.0021354 0.8900000 0.8889852 0.456863 0.4207270 NA
1 234313 rs8179466 C T -0.0027032 0.0042104 0.5199996 0.5208638 0.074512 NA NA
1 534192 rs6680723 C T -0.0001974 0.0024393 0.9400001 0.9355044 0.240950 NA NA
1 546697 rs12025928 A G -0.0027942 0.0030433 0.3599996 0.3585418 0.913485 NA NA
1 693731 rs12238997 A G 0.0045147 0.0020441 0.0269998 0.0272012 0.116297 0.1417730 NA
1 705882 rs72631875 G A 0.0024149 0.0029959 0.4199997 0.4201984 0.067265 0.0315495 NA
1 706368 rs55727773 A G 0.0004031 0.0015142 0.7899998 0.7900760 0.515642 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0046205 0.0031792 0.1499999 0.1461291 0.041935 0.0473243 NA
22 51219766 rs182321900 C T -0.0105660 0.0148478 0.4799997 0.4766998 0.001930 NA NA
22 51220146 rs868950473 C T -0.0142391 0.0147048 0.3300000 0.3328796 0.001979 NA NA
22 51221190 rs369304721 G A 0.0012555 0.0031738 0.6899999 0.6924028 0.049718 NA NA
22 51221731 rs115055839 T C 0.0003928 0.0023736 0.8700001 0.8685589 0.073223 0.0625000 NA
22 51222100 rs114553188 G T -0.0039248 0.0027936 0.1600000 0.1600515 0.054475 0.0880591 NA
22 51223637 rs375798137 G A -0.0038132 0.0028072 0.1700000 0.1743538 0.054103 0.0788738 NA
22 51229805 rs9616985 T C 0.0001713 0.0023822 0.9400001 0.9426641 0.073058 0.0730831 NA
22 51232488 rs376461333 A G -0.0062135 0.0056121 0.2700001 0.2682208 0.020045 NA NA
22 51237063 rs3896457 T C -0.0005277 0.0014568 0.7199992 0.7171661 0.297952 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623768 ES:SE:LP:AF:ID  -0.000329087:0.00218922:0.0555173:0.623768:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400421 ES:SE:LP:AF:ID  0.00264719:0.00216877:0.657577:0.400421:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103561 ES:SE:LP:AF:ID  0.00418103:0.00346738:0.638272:0.103561:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  -0.00029808:0.00213542:0.05061:0.456863:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074512 ES:SE:LP:AF:ID  -0.00270317:0.00421045:0.283997:0.074512:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24095  ES:SE:LP:AF:ID  -0.000197391:0.00243929:0.0268721:0.24095:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913485 ES:SE:LP:AF:ID  -0.00279417:0.00304327:0.443698:0.913485:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116297 ES:SE:LP:AF:ID  0.00451466:0.00204411:1.56864:0.116297:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067265 ES:SE:LP:AF:ID  0.00241491:0.00299588:0.376751:0.067265:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515642 ES:SE:LP:AF:ID  0.000403106:0.00151423:0.102373:0.515642:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032976 ES:SE:LP:AF:ID  -0.000401511:0.003819:0.0362122:0.032976:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036593 ES:SE:LP:AF:ID  -0.000188224:0.0034687:0.0177288:0.036593:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036706 ES:SE:LP:AF:ID  -0.000221196:0.00345574:0.0222764:0.036706:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036408 ES:SE:LP:AF:ID  0.000217863:0.0034805:0.0222764:0.036408:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016394 ES:SE:LP:AF:ID  0.000521934:0.00535929:0.0362122:0.016394:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036947 ES:SE:LP:AF:ID  -0.000151166:0.00344197:0.0177288:0.036947:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037042 ES:SE:LP:AF:ID  0.00032383:0.00343028:0.0362122:0.037042:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101247 ES:SE:LP:AF:ID  -0.00066578:0.00249756:0.102373:0.101247:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959135 ES:SE:LP:AF:ID  0.000508728:0.0033088:0.0555173:0.959135:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031451 ES:SE:LP:AF:ID  -0.00742508:0.00600291:0.657577:0.031451:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053284 ES:SE:LP:AF:ID  0.00389992:0.00477327:0.387216:0.053284:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036561 ES:SE:LP:AF:ID  -0.000105606:0.00345243:0.00877392:0.036561:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036879 ES:SE:LP:AF:ID  -0.000673258:0.00342093:0.0757207:0.036879:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843284 ES:SE:LP:AF:ID  -0.00276112:0.00177172:0.920819:0.843284:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055905 ES:SE:LP:AF:ID  0.00714882:0.00286831:1.88606:0.055905:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122272 ES:SE:LP:AF:ID  0.00424518:0.0019391:1.5376:0.122272:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025722 ES:SE:LP:AF:ID  0.00811228:0.00476822:1.05061:0.025722:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121517 ES:SE:LP:AF:ID  0.0043469:0.00193991:1.60206:0.121517:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132288 ES:SE:LP:AF:ID  0.00293709:0.00191211:0.920819:0.132288:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  -0.00165011:0.00695199:0.091515:0.011135:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005707 ES:SE:LP:AF:ID  -0.00975287:0.00896745:0.552842:0.005707:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002262 ES:SE:LP:AF:ID  -0.00284695:0.0151209:0.0705811:0.002262:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001027 ES:SE:LP:AF:ID  0.0271973:0.0247299:0.568636:0.001027:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036792 ES:SE:LP:AF:ID  -0.000113076:0.00338638:0.0132283:0.036792:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839033 ES:SE:LP:AF:ID  -0.00312124:0.00171585:1.16115:0.839033:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838662 ES:SE:LP:AF:ID  -0.0030878:0.00171402:1.14267:0.838662:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869832 ES:SE:LP:AF:ID  -0.00408875:0.00183918:1.58503:0.869832:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129819 ES:SE:LP:AF:ID  0.00410681:0.00184291:1.58503:0.129819:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037302 ES:SE:LP:AF:ID  -0.000108601:0.00332902:0.0132283:0.037302:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037546 ES:SE:LP:AF:ID  -7.18073e-07:0.00330797:-0:0.037546:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869175 ES:SE:LP:AF:ID  -0.00411738:0.00183558:1.60206:0.869175:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869272 ES:SE:LP:AF:ID  -0.00413991:0.00183631:1.61979:0.869272:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037504 ES:SE:LP:AF:ID  -0.000240667:0.00332229:0.0268721:0.037504:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869177 ES:SE:LP:AF:ID  -0.00410714:0.00183554:1.60206:0.869177:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005122 ES:SE:LP:AF:ID  -0.00167594:0.00942329:0.0655015:0.005122:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  -0.0022126:0.00944803:0.091515:0.005088:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838113 ES:SE:LP:AF:ID  -0.00296514:0.00170926:1.08092:0.838113:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037517 ES:SE:LP:AF:ID  -0.000216625:0.00332696:0.0222764:0.037517:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838744 ES:SE:LP:AF:ID  -0.0030127:0.00171406:1.10237:0.838744:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013783 ES:SE:LP:AF:ID  -0.00196528:0.00598017:0.130768:0.013783:rs181660517