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-11045/UKB-b-11045_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11045/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11045/UKB-b-11045_data.vcf.gz ...
Read summary statistics for 2460802 SNPs.
Dropped 285 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, 623434 SNPs remain.
After merging with regression SNP LD, 623434 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.001 (0.0013)
Lambda GC: 1.0199
Mean Chi^2: 1.0279
Intercept: 1.0164 (0.01)
Ratio: 0.5882 (0.3604)
Analysis finished at Thu Oct 17 14:40:53 2019
Total time elapsed: 34.13s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7637,
    "inflation_factor": 1,
    "mean_EFFECT": -1.2591e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 19487,
    "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": 623434,
    "ldsc_nsnp_merge_regression_ld": 623434,
    "ldsc_observed_scale_h2_beta": 0.001,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0164,
    "ldsc_intercept_se": 0.01,
    "ldsc_lambda_gc": 1.0199,
    "ldsc_mean_chisq": 1.0279,
    "ldsc_ratio": 0.5878
}
 

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 TRUE
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 1.000000 4 58 0 2460520 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 2460802 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.652597e+00 5.766274e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.855659e+07 5.661983e+07 5687.0000000 3.168917e+07 6.898031e+07 1.147543e+08 2.491917e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -1.000000e-07 1.264000e-04 -0.0006629 -8.460000e-05 -6.000000e-07 8.450000e-05 6.550000e-04 ▁▂▇▂▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.244000e-04 6.600000e-06 0.0001131 1.188000e-04 1.225000e-04 1.289000e-04 2.449000e-04 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.960364e-01 2.899497e-01 0.0000005 2.399999e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.960353e-01 2.899244e-01 0.0000005 2.434978e-01 4.957610e-01 7.464845e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 4.547715e-01 1.496894e-01 0.2369670 3.232080e-01 4.330420e-01 5.750780e-01 7.630330e-01 ▇▆▅▅▃
numeric AF_reference 19487 0.992081 NA NA NA NA NA NA NA 4.362123e-01 1.751978e-01 0.0001997 2.981230e-01 4.211260e-01 5.642970e-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 0.0003093 0.0002081 0.1400000 0.1372712 0.623765 0.7821490 NA
1 54676 rs2462492 C T -0.0001385 0.0002062 0.5000000 0.5019110 0.400401 NA NA
1 91536 rs6702460 G T 0.0001467 0.0002030 0.4700002 0.4699185 0.456846 0.4207270 NA
1 534192 rs6680723 C T 0.0001781 0.0002319 0.4400003 0.4425689 0.240959 NA NA
1 706368 rs55727773 A G 0.0000535 0.0001440 0.7099994 0.7102048 0.515645 0.2751600 NA
1 763394 rs369924889 G A -0.0002201 0.0001688 0.1900002 0.1922980 0.706753 0.6176120 NA
1 768253 rs2977608 A C 0.0001170 0.0001377 0.4000000 0.3955289 0.761297 0.4894170 NA
1 776546 rs12124819 A G 0.0000935 0.0001539 0.5400003 0.5434521 0.265385 0.0756789 NA
1 814495 rs74461805 C A 0.0001361 0.0001974 0.4899999 0.4905036 0.340396 NA NA
1 830181 rs28444699 A G -0.0000934 0.0001321 0.4799997 0.4792223 0.697255 0.6912940 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0001703 0.0001355 0.2099999 0.2086511 0.713656 0.6369810 NA
22 51181919 rs9616825 G C 0.0001145 0.0001348 0.4000000 0.3957868 0.695470 0.6194090 NA
22 51182485 rs6009961 A G 0.0001684 0.0001359 0.2200002 0.2154047 0.715502 0.6383790 NA
22 51186143 rs2879914 T C 0.0000415 0.0001260 0.7400005 0.7420544 0.381825 0.2733630 NA
22 51186228 rs3865766 C T 0.0000359 0.0001228 0.7700005 0.7700129 0.451061 0.4532750 NA
22 51197266 rs61290853 A G -0.0000638 0.0001268 0.6200004 0.6151087 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0001275 0.0001436 0.3700002 0.3743499 0.254562 0.0984425 NA
22 51211106 rs9628250 T C 0.0000285 0.0001423 0.8400000 0.8410657 0.271547 0.1671330 NA
22 51212875 rs2238837 A C 0.0000258 0.0001352 0.8499999 0.8486617 0.331457 0.3724040 NA
22 51237063 rs3896457 T C -0.0000647 0.0001384 0.6400000 0.6403034 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  0.000309277:0.000208123:0.853872:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000138451:0.000206186:0.30103:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  0.000146701:0.000203015:0.327902:0.456846:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  0.000178065:0.000231897:0.356547:0.240959:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  5.34917e-05:0.000143957:0.148742:0.515645:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -0.000220052:0.000168776:0.721246:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761297 ES:SE:LP:AF:ID  0.000117037:0.00013775:0.39794:0.761297:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265385 ES:SE:LP:AF:ID  9.34928e-05:0.000153872:0.267606:0.265385:rs12124819
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  0.000136102:0.00019739:0.309804:0.340396:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697255 ES:SE:LP:AF:ID  -9.34424e-05:0.000132064:0.318759:0.697255:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705397 ES:SE:LP:AF:ID  -1.63607e-05:0.000129674:0.0457575:0.705397:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705442 ES:SE:LP:AF:ID  -1.71625e-05:0.000129669:0.05061:0.705442:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705627 ES:SE:LP:AF:ID  -1.83161e-05:0.000129675:0.05061:0.705627:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705655 ES:SE:LP:AF:ID  -1.64094e-05:0.000129689:0.0457575:0.705655:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730129 ES:SE:LP:AF:ID  -5.63657e-05:0.000133223:0.173925:0.730129:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294377 ES:SE:LP:AF:ID  1.56133e-05:0.000129683:0.0457575:0.294377:rs28765502
1   833641  rs28594623  T   C   .   PASS    AF=0.23975  ES:SE:LP:AF:ID  -7.45423e-06:0.000137627:0.0177288:0.23975:rs28594623
1   834832  rs4411087   G   C   .   PASS    AF=0.237178 ES:SE:LP:AF:ID  -2.9726e-06:0.000137962:0.00877392:0.237178:rs4411087
1   835499  rs4422948   A   G   .   PASS    AF=0.241162 ES:SE:LP:AF:ID  -4.35256e-06:0.000136999:0.0132283:0.241162:rs4422948
1   836896  rs28705752  T   C   .   PASS    AF=0.269511 ES:SE:LP:AF:ID  -7.56551e-06:0.000132194:0.0222764:0.269511:rs28705752
1   838555  rs4970383   C   A   .   PASS    AF=0.246204 ES:SE:LP:AF:ID  1.87363e-05:0.000136057:0.05061:0.246204:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270019 ES:SE:LP:AF:ID  -3.72309e-05:0.000132287:0.107905:0.270019:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  -0.000114153:0.000119613:0.468521:0.400124:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237102 ES:SE:LP:AF:ID  1.54135e-05:0.000138935:0.0409586:0.237102:rs1574243
1   843405  rs11516185  A   G   .   PASS    AF=0.362606 ES:SE:LP:AF:ID  -6.75031e-05:0.000148483:0.187087:0.362606:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590331 ES:SE:LP:AF:ID  1.70987e-05:0.000119264:0.05061:0.590331:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603723 ES:SE:LP:AF:ID  8.08e-07:0.000119933:0.00436481:0.603723:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603942 ES:SE:LP:AF:ID  -2.63991e-06:0.000119917:0.00877392:0.603942:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589686 ES:SE:LP:AF:ID  4.5395e-06:0.000119458:0.0132283:0.589686:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589665 ES:SE:LP:AF:ID  1.15879e-05:0.000119405:0.0362122:0.589665:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607671 ES:SE:LP:AF:ID  3.07393e-06:0.000120185:0.00877392:0.607671:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607829 ES:SE:LP:AF:ID  6.73308e-06:0.000120201:0.0177288:0.607829:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610316 ES:SE:LP:AF:ID  1.56148e-05:0.000120319:0.0457575:0.610316:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603283 ES:SE:LP:AF:ID  1.02042e-05:0.000119963:0.0315171:0.603283:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610337 ES:SE:LP:AF:ID  1.50515e-05:0.000120321:0.0457575:0.610337:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389936 ES:SE:LP:AF:ID  -1.80801e-05:0.000120344:0.0555173:0.389936:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.38992  ES:SE:LP:AF:ID  -1.80203e-05:0.00012035:0.0555173:0.38992:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350356 ES:SE:LP:AF:ID  -0.000129875:0.000123634:0.537602:0.350356:rs4040605
1   864938  rs2340587   G   A   .   PASS    AF=0.760006 ES:SE:LP:AF:ID  9.36586e-05:0.000137636:0.30103:0.760006:rs2340587
1   866893  rs2880024   T   C   .   PASS    AF=0.610552 ES:SE:LP:AF:ID  0.000201015:0.000120996:1.01323:0.610552:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297867 ES:SE:LP:AF:ID  -3.66615e-05:0.00013294:0.107905:0.297867:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.291285 ES:SE:LP:AF:ID  -0.000168705:0.000131882:0.69897:0.291285:rs28576697
1   871334  rs4072383   G   T   .   PASS    AF=0.72062  ES:SE:LP:AF:ID  0.000206696:0.000131065:0.958607:0.72062:rs4072383
1   872352  rs1806780   G   C   .   PASS    AF=0.267527 ES:SE:LP:AF:ID  -0.00018772:0.000132841:0.79588:0.267527:rs1806780
1   873558  rs1110052   G   T   .   PASS    AF=0.715251 ES:SE:LP:AF:ID  0.000248388:0.000130023:1.25181:0.715251:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.600085 ES:SE:LP:AF:ID  0.000150136:0.000122002:0.657577:0.600085:rs4970379
1   877147  rs114982608 G   A   .   PASS    AF=0.242966 ES:SE:LP:AF:ID  -0.000126213:0.000138178:0.443698:0.242966:rs114982608
1   881627  rs2272757   G   A   .   PASS    AF=0.652393 ES:SE:LP:AF:ID  0.000151692:0.000123243:0.657577:0.652393:rs2272757
1   882033  rs2272756   G   A   .   PASS    AF=0.243918 ES:SE:LP:AF:ID  -0.000137395:0.000137262:0.49485:0.243918:rs2272756
1   890104  rs28631199  G   A   .   PASS    AF=0.246771 ES:SE:LP:AF:ID  -0.000145982:0.000136722:0.537602:0.246771:rs28631199