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-7137/UKB-b-7137_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7137/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-7137/UKB-b-7137_data.vcf.gz ...
Read summary statistics for 8613181 SNPs.
Dropped 7361 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, 1285689 SNPs remain.
After merging with regression SNP LD, 1285689 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0212 (0.0015)
Lambda GC: 1.1846
Mean Chi^2: 1.2128
Intercept: 1.0206 (0.0069)
Ratio: 0.0966 (0.0322)
Analysis finished at Thu Oct 17 14:42:47 2019
Total time elapsed: 2.0m:30.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9461,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 5.6372e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 13,
    "n_p_sig": 506,
    "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": 82939,
    "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": 1285689,
    "ldsc_nsnp_merge_regression_ld": 1285689,
    "ldsc_observed_scale_h2_beta": 0.0212,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0206,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.1846,
    "ldsc_mean_chisq": 1.2128,
    "ldsc_ratio": 0.0968
}

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 8605854 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 8613181 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 8.651185e+00 5.761120e+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 7.876232e+07 5.637043e+07 828.0000000 3.237875e+07 6.927948e+07 1.145588e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.600000e-06 2.172700e-03 -0.0217250 -9.474000e-04 -1.400000e-06 9.482000e-04 2.413000e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.749000e-03 1.191600e-03 0.0006957 8.197000e-04 1.207500e-03 2.363000e-03 1.236660e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.791673e-01 2.945043e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.791677e-01 2.944784e-01 0.0000000 2.193690e-01 4.716405e-01 7.343976e-01 9.999998e-01 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.293918e-01 2.595248e-01 0.0054240 2.534700e-02 1.142450e-01 3.629810e-01 9.945760e-01 ▇▂▁▁▁
numeric AF_reference 82939 0.9903707 NA NA NA NA NA NA NA 2.291171e-01 2.514909e-01 0.0000000 2.336260e-02 1.307910e-01 3.600240e-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 0.0017437 0.0012806 0.1700000 0.1733072 0.623783 0.7821490 NA
1 54676 rs2462492 C T 0.0009792 0.0012686 0.4400003 0.4401845 0.400457 NA NA
1 86028 rs114608975 T C -0.0013516 0.0020284 0.5099998 0.5052182 0.103543 0.0277556 NA
1 91536 rs6702460 G T 0.0015318 0.0012490 0.2200002 0.2200430 0.456874 0.4207270 NA
1 234313 rs8179466 C T -0.0027004 0.0024625 0.2700001 0.2728144 0.074519 NA NA
1 534192 rs6680723 C T 0.0010406 0.0014266 0.4700002 0.4657404 0.240975 NA NA
1 546697 rs12025928 A G 0.0014356 0.0017797 0.4199997 0.4198626 0.913488 NA NA
1 693731 rs12238997 A G -0.0002716 0.0011952 0.8200001 0.8202302 0.116354 0.1417730 NA
1 705882 rs72631875 G A -0.0033010 0.0017517 0.0599998 0.0595044 0.067296 0.0315495 NA
1 706368 rs55727773 A G -0.0019706 0.0008857 0.0259998 0.0260851 0.515658 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0011083 0.0010686 0.2999998 0.2997054 0.137921 0.2052720 NA
22 51219387 rs9616832 T C -0.0012980 0.0013872 0.3500000 0.3494293 0.073721 0.0654952 NA
22 51219704 rs147475742 G A -0.0010302 0.0018588 0.5800000 0.5794159 0.041945 0.0473243 NA
22 51221190 rs369304721 G A -0.0007867 0.0018555 0.6700003 0.6715865 0.049724 NA NA
22 51221731 rs115055839 T C -0.0013549 0.0013880 0.3300000 0.3290028 0.073211 0.0625000 NA
22 51222100 rs114553188 G T -0.0003357 0.0016341 0.8400000 0.8372287 0.054450 0.0880591 NA
22 51223637 rs375798137 G A -0.0004107 0.0016420 0.8000000 0.8025092 0.054078 0.0788738 NA
22 51229805 rs9616985 T C -0.0011735 0.0013930 0.4000000 0.3995702 0.073046 0.0730831 NA
22 51232488 rs376461333 A G -0.0001920 0.0032795 0.9500000 0.9533038 0.020055 NA NA
22 51237063 rs3896457 T C 0.0016177 0.0008519 0.0580003 0.0575655 0.297942 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623783 ES:SE:LP:AF:ID  0.00174372:0.00128059:0.769551:0.623783:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400457 ES:SE:LP:AF:ID  0.000979186:0.00126857:0.356547:0.400457:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103543 ES:SE:LP:AF:ID  -0.00135156:0.00202845:0.29243:0.103543:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456874 ES:SE:LP:AF:ID  0.00153184:0.00124904:0.657577:0.456874:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  -0.00270041:0.00246252:0.568636:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240975 ES:SE:LP:AF:ID  0.00104063:0.00142664:0.327902:0.240975:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913488 ES:SE:LP:AF:ID  0.00143558:0.00177966:0.376751:0.913488:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116354 ES:SE:LP:AF:ID  -0.000271617:0.00119524:0.0861861:0.116354:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067296 ES:SE:LP:AF:ID  -0.00330095:0.00175168:1.22185:0.067296:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515658 ES:SE:LP:AF:ID  -0.00197065:0.000885708:1.58503:0.515658:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033001 ES:SE:LP:AF:ID  -0.00347041:0.00223289:0.920819:0.033001:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036622 ES:SE:LP:AF:ID  -0.00271109:0.00202805:0.744727:0.036622:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036733 ES:SE:LP:AF:ID  -0.00251728:0.00202053:0.677781:0.036733:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036435 ES:SE:LP:AF:ID  -0.00267759:0.00203503:0.721246:0.036435:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016407 ES:SE:LP:AF:ID  -0.00224383:0.00313374:0.327902:0.016407:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036977 ES:SE:LP:AF:ID  -0.00258888:0.00201239:0.69897:0.036977:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037074 ES:SE:LP:AF:ID  -0.00260031:0.00200548:0.721246:0.037074:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101246 ES:SE:LP:AF:ID  0.00170033:0.00146083:0.619789:0.101246:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959089 ES:SE:LP:AF:ID  0.00165837:0.00193411:0.408935:0.959089:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  0.00233977:0.00351151:0.29243:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053273 ES:SE:LP:AF:ID  -0.00118533:0.00279198:0.173925:0.053273:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  -0.00247184:0.00201852:0.657577:0.03659:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036906 ES:SE:LP:AF:ID  -0.00247695:0.0020001:0.657577:0.036906:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843184 ES:SE:LP:AF:ID  0.000620189:0.00103597:0.259637:0.843184:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055947 ES:SE:LP:AF:ID  -0.000672804:0.00167696:0.161151:0.055947:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122327 ES:SE:LP:AF:ID  -7.85469e-05:0.00113386:0.0268721:0.122327:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025697 ES:SE:LP:AF:ID  -0.000724296:0.00279053:0.09691:0.025697:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121571 ES:SE:LP:AF:ID  -0.000115127:0.00113434:0.0362122:0.121571:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132347 ES:SE:LP:AF:ID  -0.000598296:0.00111812:0.229148:0.132347:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011122 ES:SE:LP:AF:ID  0.00283447:0.00406718:0.309804:0.011122:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005713 ES:SE:LP:AF:ID  0.00296088:0.00524161:0.244125:0.005713:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036824 ES:SE:LP:AF:ID  -0.00213601:0.00197983:0.552842:0.036824:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838927 ES:SE:LP:AF:ID  0.000328392:0.0010033:0.130768:0.838927:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838554 ES:SE:LP:AF:ID  0.00019284:0.00100221:0.0705811:0.838554:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869761 ES:SE:LP:AF:ID  -0.000215189:0.00107539:0.0757207:0.869761:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129894 ES:SE:LP:AF:ID  0.000232339:0.00107755:0.0809219:0.129894:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037335 ES:SE:LP:AF:ID  -0.00230075:0.00194625:0.619789:0.037335:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037578 ES:SE:LP:AF:ID  -0.00224169:0.00193397:0.60206:0.037578:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000304322:0.00107328:0.107905:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869199 ES:SE:LP:AF:ID  -0.000281237:0.00107371:0.102373:0.869199:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -0.00226663:0.00194229:0.619789:0.037539:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.000295085:0.00107326:0.107905:0.869104:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838003 ES:SE:LP:AF:ID  0.000248884:0.000999418:0.09691:0.838003:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037552 ES:SE:LP:AF:ID  -0.00235155:0.00194501:0.638272:0.037552:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838632 ES:SE:LP:AF:ID  0.000240204:0.00100223:0.091515:0.838632:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013784 ES:SE:LP:AF:ID  -0.000419825:0.00349735:0.0457575:0.013784:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005538 ES:SE:LP:AF:ID  -0.00433139:0.00540183:0.376751:0.005538:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839742 ES:SE:LP:AF:ID  0.000545629:0.00101579:0.229148:0.839742:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869381 ES:SE:LP:AF:ID  -0.000192854:0.001072:0.0655015:0.869381:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868926 ES:SE:LP:AF:ID  -0.000272307:0.0010693:0.09691:0.868926:rs3131962