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-20544/UKB-b-20544_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20544/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20544/UKB-b-20544_data.vcf.gz ...
Read summary statistics for 9066770 SNPs.
Dropped 9030 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, 1287333 SNPs remain.
After merging with regression SNP LD, 1287333 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0619 (0.0028)
Lambda GC: 1.4472
Mean Chi^2: 1.6074
Intercept: 1.0287 (0.0095)
Ratio: 0.0473 (0.0156)
Analysis finished at Thu Oct 17 14:43:51 2019
Total time elapsed: 1.0m:39.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 5.555e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 58,
    "n_p_sig": 9355,
    "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": 96532,
    "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": 1287333,
    "ldsc_nsnp_merge_regression_ld": 1287333,
    "ldsc_observed_scale_h2_beta": 0.0619,
    "ldsc_observed_scale_h2_se": 0.0028,
    "ldsc_intercept_beta": 1.0287,
    "ldsc_intercept_se": 0.0095,
    "ldsc_lambda_gc": 1.4472,
    "ldsc_mean_chisq": 1.6074,
    "ldsc_ratio": 0.0473
}

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 9057781 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 9066770 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 8.641721e+00 5.757643e+00 1.000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.879399e+07 5.633207e+07 8.280e+02 3.244647e+07 6.936300e+07 1.145325e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.600000e-06 3.190700e-03 -3.187e-02 -1.351100e-03 1.900000e-06 1.350600e-03 3.412270e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.396900e-03 1.781600e-03 8.576e-04 1.024100e-03 1.578200e-03 3.288800e-03 1.990250e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.544274e-01 3.010071e-01 0.000e+00 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.544294e-01 3.009829e-01 0.000e+00 1.820907e-01 4.379176e-01 7.150968e-01 1.000000e+00 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.188566e-01 2.584042e-01 3.283e-03 1.983100e-02 9.957900e-02 3.450060e-01 9.967170e-01 ▇▂▁▁▁
numeric AF_reference 96532 0.9893532 NA NA NA NA NA NA NA 2.192535e-01 2.502832e-01 0.000e+00 1.697280e-02 1.172120e-01 3.434500e-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 -0.0023123 0.0015779 0.1400000 0.1428100 0.623855 0.7821490 NA
1 54676 rs2462492 C T -0.0016289 0.0015630 0.2999998 0.2973367 0.400417 NA NA
1 86028 rs114608975 T C 0.0005804 0.0024995 0.8200001 0.8163697 0.103525 0.0277556 NA
1 91536 rs6702460 G T -0.0028035 0.0015387 0.0680002 0.0684599 0.456908 0.4207270 NA
1 234313 rs8179466 C T -0.0010598 0.0030364 0.7300002 0.7270705 0.074472 NA NA
1 534192 rs6680723 C T -0.0011015 0.0017576 0.5300002 0.5308687 0.240958 NA NA
1 546697 rs12025928 A G 0.0014435 0.0021920 0.5099998 0.5102010 0.913420 NA NA
1 693731 rs12238997 A G -0.0012964 0.0014729 0.3800004 0.3787694 0.116320 0.1417730 NA
1 705882 rs72631875 G A -0.0000952 0.0021587 0.9599999 0.9648313 0.067305 0.0315495 NA
1 706368 rs55727773 A G -0.0008517 0.0010911 0.4400003 0.4350077 0.515752 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0027720 0.0013173 0.0350002 0.0353499 0.137916 0.2052720 NA
22 51219387 rs9616832 T C 0.0014880 0.0017099 0.3800004 0.3841560 0.073741 0.0654952 NA
22 51219704 rs147475742 G A 0.0016673 0.0022914 0.4700002 0.4668312 0.041941 0.0473243 NA
22 51221190 rs369304721 G A 0.0030040 0.0022869 0.1900002 0.1889871 0.049746 NA NA
22 51221731 rs115055839 T C 0.0014907 0.0017110 0.3800004 0.3836125 0.073232 0.0625000 NA
22 51222100 rs114553188 G T 0.0036507 0.0020154 0.0700003 0.0700714 0.054408 0.0880591 NA
22 51223637 rs375798137 G A 0.0036571 0.0020251 0.0710003 0.0709332 0.054040 0.0788738 NA
22 51229805 rs9616985 T C 0.0013715 0.0017171 0.4199997 0.4244650 0.073066 0.0730831 NA
22 51232488 rs376461333 A G 0.0081642 0.0040490 0.0439997 0.0437621 0.020015 NA NA
22 51237063 rs3896457 T C -0.0025110 0.0010502 0.0170000 0.0168044 0.298042 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623855 ES:SE:LP:AF:ID  -0.00231228:0.00157791:0.853872:0.623855:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400417 ES:SE:LP:AF:ID  -0.00162893:0.00156303:0.522879:0.400417:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103525 ES:SE:LP:AF:ID  0.000580428:0.00249951:0.0861861:0.103525:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456908 ES:SE:LP:AF:ID  -0.00280348:0.00153871:1.16749:0.456908:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074472 ES:SE:LP:AF:ID  -0.00105979:0.00303643:0.136677:0.074472:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240958 ES:SE:LP:AF:ID  -0.00110146:0.00175761:0.275724:0.240958:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91342  ES:SE:LP:AF:ID  0.00144346:0.00219196:0.29243:0.91342:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11632  ES:SE:LP:AF:ID  -0.00129637:0.00147287:0.420216:0.11632:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067305 ES:SE:LP:AF:ID  -9.51812e-05:0.00215871:0.0177288:0.067305:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515752 ES:SE:LP:AF:ID  -0.000851745:0.00109107:0.356547:0.515752:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032976 ES:SE:LP:AF:ID  0.00202763:0.00275217:0.337242:0.032976:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036592 ES:SE:LP:AF:ID  0.00253772:0.0024998:0.508638:0.036592:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036707 ES:SE:LP:AF:ID  0.0026723:0.00249036:0.552842:0.036707:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036405 ES:SE:LP:AF:ID  0.00311981:0.0025084:0.677781:0.036405:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016376 ES:SE:LP:AF:ID  -0.000281316:0.00386423:0.0268721:0.016376:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036944 ES:SE:LP:AF:ID  0.00275115:0.00248064:0.568636:0.036944:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037043 ES:SE:LP:AF:ID  0.00267782:0.00247197:0.552842:0.037043:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101237 ES:SE:LP:AF:ID  0.000161297:0.0017998:0.0315171:0.101237:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959137 ES:SE:LP:AF:ID  -0.00233793:0.0023844:0.481486:0.959137:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031436 ES:SE:LP:AF:ID  -0.00637646:0.00432896:0.853872:0.031436:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053283 ES:SE:LP:AF:ID  0.00334082:0.00343911:0.481486:0.053283:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036563 ES:SE:LP:AF:ID  0.0030572:0.00248788:0.657577:0.036563:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03688  ES:SE:LP:AF:ID  0.00303808:0.0024652:0.657577:0.03688:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843279 ES:SE:LP:AF:ID  0.000442671:0.00127681:0.136677:0.843279:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055899 ES:SE:LP:AF:ID  -0.00064987:0.00206705:0.124939:0.055899:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122279 ES:SE:LP:AF:ID  -0.000975163:0.00139732:0.309804:0.122279:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  0.00260451:0.00343569:0.346787:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121525 ES:SE:LP:AF:ID  -0.0010184:0.00139789:0.327902:0.121525:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13232  ES:SE:LP:AF:ID  -0.000301153:0.00137788:0.0809219:0.13232:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011123 ES:SE:LP:AF:ID  -0.00212831:0.00501051:0.173925:0.011123:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005702 ES:SE:LP:AF:ID  -0.0100076:0.00646666:0.920819:0.005702:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036795 ES:SE:LP:AF:ID  0.00323301:0.00244031:0.721246:0.036795:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838987 ES:SE:LP:AF:ID  -0.000151176:0.00123633:0.0457575:0.838987:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838621 ES:SE:LP:AF:ID  -8.52314e-05:0.00123501:0.0268721:0.838621:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869791 ES:SE:LP:AF:ID  0.000570886:0.00132507:0.173925:0.869791:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129856 ES:SE:LP:AF:ID  -0.00063178:0.00132776:0.200659:0.129856:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037302 ES:SE:LP:AF:ID  0.00320088:0.00239904:0.744727:0.037302:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037547 ES:SE:LP:AF:ID  0.00312953:0.00238384:0.721246:0.037547:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869141 ES:SE:LP:AF:ID  0.00063948:0.0013225:0.200659:0.869141:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869241 ES:SE:LP:AF:ID  0.000682651:0.00132304:0.21467:0.869241:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037504 ES:SE:LP:AF:ID  0.00314562:0.00239417:0.721246:0.037504:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869143 ES:SE:LP:AF:ID  0.000600083:0.00132247:0.187087:0.869143:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005122 ES:SE:LP:AF:ID  0.00395905:0.00679202:0.251812:0.005122:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  0.00376425:0.00680997:0.236572:0.005088:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838076 ES:SE:LP:AF:ID  -2.8907e-05:0.0012316:0.00877392:0.838076:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037516 ES:SE:LP:AF:ID  0.00314567:0.00239752:0.721246:0.037516:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838702 ES:SE:LP:AF:ID  -4.2378e-06:0.00123505:-0:0.838702:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013815 ES:SE:LP:AF:ID  -0.000168572:0.00430425:0.0132283:0.013815:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005533 ES:SE:LP:AF:ID  0.0029219:0.00666004:0.180456:0.005533:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839811 ES:SE:LP:AF:ID  -0.000192326:0.00125175:0.0555173:0.839811:rs3131965