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-1666/UKB-b-1666_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1666/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1666/UKB-b-1666_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: 0.0128 (0.0021)
Lambda GC: 1.6838
Mean Chi^2: 1.6926
Intercept: 1.5781 (0.0096)
Ratio: 0.8347 (0.0139)
Analysis finished at Thu Oct 17 14:46:46 2019
Total time elapsed: 1.0m:32.93s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.6243,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 29,
    "n_p_sig": 144,
    "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": 0.0128,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.5781,
    "ldsc_intercept_se": 0.0096,
    "ldsc_lambda_gc": 1.6838,
    "ldsc_mean_chisq": 1.6926,
    "ldsc_ratio": 0.8347
}

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 FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio TRUE
ldsc_intercept_beta TRUE
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 7.090000e-05 1.130910e-02 -0.1885090 -3.417900e-03 3.850000e-05 3.535100e-03 1.719200e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.615700e-03 6.262200e-03 0.0018506 2.266300e-03 3.800300e-03 8.768500e-03 9.736510e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.220472e-01 3.045097e-01 0.0000000 1.400000e-01 3.900004e-01 6.800001e-01 1.000000e+00 ▇▅▅▃▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.220497e-01 3.044870e-01 0.0000000 1.407807e-01 3.880034e-01 6.832222e-01 9.999997e-01 ▇▅▅▅▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035076e-01 2.568619e-01 0.0009850 1.316900e-02 7.791400e-02 3.164540e-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 0.0056409 0.0033999 0.0969996 0.0970886 0.623759 0.7821490 NA
1 54676 rs2462492 C T 0.0021962 0.0033683 0.5099998 0.5143887 0.400399 NA NA
1 86028 rs114608975 T C -0.0029532 0.0053838 0.5800000 0.5833217 0.103585 0.0277556 NA
1 91536 rs6702460 G T 0.0010724 0.0033166 0.7499995 0.7464376 0.456799 0.4207270 NA
1 234313 rs8179466 C T 0.0018187 0.0065383 0.7800007 0.7808870 0.074519 NA NA
1 534192 rs6680723 C T 0.0060679 0.0037883 0.1100001 0.1092148 0.240981 NA NA
1 546697 rs12025928 A G -0.0042002 0.0047278 0.3700002 0.3743286 0.913515 NA NA
1 693731 rs12238997 A G 0.0004661 0.0031747 0.8800001 0.8832700 0.116373 0.1417730 NA
1 705882 rs72631875 G A 0.0004688 0.0046540 0.9199999 0.9197650 0.067245 0.0315495 NA
1 706368 rs55727773 A G -0.0061498 0.0023519 0.0089000 0.0089262 0.515554 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0030012 0.0049535 0.5400003 0.5445961 0.041987 0.0473243 NA
22 51219766 rs182321900 C T -0.0153803 0.0230068 0.5000000 0.5038074 0.001950 NA NA
22 51220146 rs868950473 C T -0.0183390 0.0227893 0.4199997 0.4209814 0.001999 NA NA
22 51221190 rs369304721 G A 0.0039172 0.0049449 0.4299995 0.4282692 0.049771 NA NA
22 51221731 rs115055839 T C 0.0038834 0.0036988 0.2900000 0.2937668 0.073287 0.0625000 NA
22 51222100 rs114553188 G T 0.0120246 0.0043567 0.0058000 0.0057797 0.054450 0.0880591 NA
22 51223637 rs375798137 G A 0.0120299 0.0043778 0.0060000 0.0059970 0.054078 0.0788738 NA
22 51229805 rs9616985 T C 0.0037330 0.0037122 0.3100002 0.3146143 0.073121 0.0730831 NA
22 51232488 rs376461333 A G 0.0232722 0.0087460 0.0077999 0.0077934 0.020047 NA NA
22 51237063 rs3896457 T C -0.0044297 0.0022712 0.0510000 0.0511289 0.297930 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623759 ES:SE:LP:AF:ID  0.00564086:0.00339988:1.01323:0.623759:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400399 ES:SE:LP:AF:ID  0.00219621:0.00336832:0.29243:0.400399:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103585 ES:SE:LP:AF:ID  -0.00295322:0.00538379:0.236572:0.103585:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456799 ES:SE:LP:AF:ID  0.00107239:0.0033166:0.124939:0.456799:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  0.00181871:0.00653828:0.107905:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240981 ES:SE:LP:AF:ID  0.00606789:0.00378833:0.958607:0.240981:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913515 ES:SE:LP:AF:ID  -0.00420016:0.00472781:0.431798:0.913515:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116373 ES:SE:LP:AF:ID  0.000466126:0.0031747:0.0555173:0.116373:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067245 ES:SE:LP:AF:ID  0.000468801:0.00465405:0.0362122:0.067245:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515554 ES:SE:LP:AF:ID  -0.00614983:0.00235187:2.05061:0.515554:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032989 ES:SE:LP:AF:ID  0.00525835:0.00593096:0.420216:0.032989:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036607 ES:SE:LP:AF:ID  0.00429131:0.00538701:0.366532:0.036607:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  0.00407407:0.00536661:0.346787:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036424 ES:SE:LP:AF:ID  0.00476011:0.00540516:0.420216:0.036424:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016399 ES:SE:LP:AF:ID  -0.00149821:0.00832523:0.0655015:0.016399:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036962 ES:SE:LP:AF:ID  0.00408606:0.00534541:0.356547:0.036962:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037057 ES:SE:LP:AF:ID  0.00431271:0.00532715:0.376751:0.037057:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101199 ES:SE:LP:AF:ID  0.000574391:0.00388003:0.0555173:0.101199:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959115 ES:SE:LP:AF:ID  -0.00510263:0.00513802:0.49485:0.959115:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031433 ES:SE:LP:AF:ID  0.0055188:0.00933339:0.259637:0.031433:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053249 ES:SE:LP:AF:ID  -0.0099588:0.00741735:0.744727:0.053249:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03658  ES:SE:LP:AF:ID  0.00467742:0.00536124:0.420216:0.03658:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036894 ES:SE:LP:AF:ID  0.00353026:0.00531267:0.29243:0.036894:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843194 ES:SE:LP:AF:ID  -0.00210665:0.00275166:0.356547:0.843194:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055942 ES:SE:LP:AF:ID  0.00286727:0.00445395:0.283997:0.055942:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122349 ES:SE:LP:AF:ID  0.0008837:0.00301161:0.113509:0.122349:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025704 ES:SE:LP:AF:ID  0.00029274:0.00740915:0.0132283:0.025704:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121593 ES:SE:LP:AF:ID  0.000896035:0.0030129:0.113509:0.121593:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132358 ES:SE:LP:AF:ID  0.00170991:0.00296947:0.251812:0.132358:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011133 ES:SE:LP:AF:ID  0.0177085:0.0107992:1:0.011133:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005718 ES:SE:LP:AF:ID  -0.00967058:0.0139137:0.309804:0.005718:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00227  ES:SE:LP:AF:ID  0.0362397:0.0234279:0.920819:0.00227:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001029 ES:SE:LP:AF:ID  0.00504685:0.0383863:0.0457575:0.001029:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036807 ES:SE:LP:AF:ID  0.00439762:0.00525897:0.39794:0.036807:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838909 ES:SE:LP:AF:ID  -0.00239852:0.00266477:0.431798:0.838909:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838539 ES:SE:LP:AF:ID  -0.00239743:0.00266191:0.431798:0.838539:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869719 ES:SE:LP:AF:ID  -0.00180154:0.00285606:0.275724:0.869719:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129931 ES:SE:LP:AF:ID  0.00154336:0.00286188:0.229148:0.129931:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037315 ES:SE:LP:AF:ID  0.00436061:0.00517003:0.39794:0.037315:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037557 ES:SE:LP:AF:ID  0.0042994:0.00513739:0.39794:0.037557:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869065 ES:SE:LP:AF:ID  -0.00179088:0.00285051:0.275724:0.869065:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869164 ES:SE:LP:AF:ID  -0.00183416:0.00285165:0.283997:0.869164:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037516 ES:SE:LP:AF:ID  0.00428971:0.00515964:0.387216:0.037516:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869069 ES:SE:LP:AF:ID  -0.00182101:0.00285046:0.283997:0.869069:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005125 ES:SE:LP:AF:ID  0.0251818:0.0146327:1.07058:0.005125:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005091 ES:SE:LP:AF:ID  0.025174:0.0146711:1.0655:0.005091:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837995 ES:SE:LP:AF:ID  -0.00224646:0.00265459:0.39794:0.837995:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037529 ES:SE:LP:AF:ID  0.00421591:0.00516691:0.387216:0.037529:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838626 ES:SE:LP:AF:ID  -0.00228405:0.00266205:0.408935:0.838626:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013769 ES:SE:LP:AF:ID  -0.00443499:0.00929324:0.200659:0.013769:rs181660517