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/dev/ukb-d-import/processed/ukb-d-41220_7/ukb-d-41220_7.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-41220_7/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 16:52:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-41220_7/ukb-d-41220_7.vcf.gz ...
Read summary statistics for 9685742 SNPs.
Dropped 7299 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1274777 SNPs remain.
After merging with regression SNP LD, 1274777 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0252 (0.2942)
Lambda GC: 1.0021
Mean Chi^2: 0.999
Intercept: 0.9983 (0.0058)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 16:54:22 2019
Total time elapsed: 1.0m:27.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9397,
    "inflation_factor": 0.9999,
    "mean_EFFECT": 0,
    "n": 1460,
    "n_snps": 9685742,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1062489,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 192962,
    "n_est": 1457.6572,
    "ratio_se_n": 0.9992,
    "mean_diff": 0,
    "ratio_diff": 42.4874,
    "sd_y_est1": 0.5027,
    "sd_y_est2": 0.5023,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1274777,
    "ldsc_nsnp_merge_regression_ld": 1274777,
    "ldsc_observed_scale_h2_beta": 0.0252,
    "ldsc_observed_scale_h2_se": 0.2942,
    "ldsc_intercept_beta": 0.9983,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 1.0021,
    "ldsc_mean_chisq": 0.999,
    "ldsc_ratio": 1.7
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 9678989 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47032 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29681 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079802e+00 6.175351e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.873251e+07 5.611160e+07 302.0000000 3.243354e+07 6.961084e+07 1.147459e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.420000e-05 4.181490e-02 -0.4117890 -1.996380e-02 -1.730000e-05 2.005020e-02 3.957120e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.638360e-02 2.070990e-02 0.0175037 2.037690e-02 2.716640e-02 4.654000e-02 1.192600e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.002748e-01 2.884610e-01 0.0000015 2.506998e-01 5.000265e-01 7.499374e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.001637e-01 2.885278e-01 0.0000014 2.505076e-01 4.999188e-01 7.498914e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.619298e-01 2.628627e-01 0.0099060 4.432720e-02 1.598680e-01 4.167570e-01 9.900940e-01 ▇▂▂▁▁
numeric AF_reference 192962 0.9800777 NA NA NA NA NA 2.613654e-01 2.536764e-01 0.0000000 5.031950e-02 1.751200e-01 4.123400e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.460000e+03 0.000000e+00 1460.0000000 1.460000e+03 1.460000e+03 1.460000e+03 1.460000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0404234 0.0309245 0.1913670 0.1911569 0.1185430 0.1894970 1460
1 693731 rs12238997 A G -0.0208518 0.0298441 0.4848585 0.4847452 0.1239850 0.1417730 1460
1 707522 rs371890604 G C -0.0292280 0.0329951 0.3758590 0.3757099 0.1050130 0.1293930 1460
1 717587 rs144155419 G A -0.0593015 0.0844093 0.4824530 0.4823381 0.0154768 0.0045926 1460
1 730087 rs148120343 T C -0.0338285 0.0408409 0.4076402 0.4075009 0.0634515 0.0127796 1460
1 731718 rs142557973 T C -0.0165202 0.0284344 0.5613361 0.5612449 0.1301520 0.1543530 1460
1 732032 rs61770163 A C -0.0232824 0.0299059 0.4363892 0.4362614 0.1299570 0.1555510 1460
1 734349 rs141242758 T C -0.0192172 0.0283532 0.4980214 0.4979119 0.1292980 0.1525560 1460
1 749963 rs529266287 T TAA 0.0232823 0.0275823 0.3987521 0.3986119 0.8603010 0.7641770 1460
1 751343 rs28544273 T A -0.0241191 0.0273148 0.3773810 0.3772337 0.1339860 0.2426120 1460
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0089661 0.0407236 0.8257700 0.8257385 0.0556433 0.0309934 1460
23 154923374 rs111332691 T A -0.0009268 0.0427101 0.9826900 0.9826867 0.0482877 0.0116556 1460
23 154925045 rs509981 C T -0.0052043 0.0211243 0.8054330 0.8053978 0.2511710 0.3634440 1460
23 154925895 rs538470 C T -0.0053763 0.0217077 0.8044269 0.8043910 0.2471760 0.3634440 1460
23 154927581 rs644138 G A -0.0031828 0.0199353 0.8731750 0.8731521 0.3071170 0.4635760 1460
23 154929412 rs557132 C T -0.0052317 0.0211251 0.8044360 0.8044012 0.2511500 0.3568210 1460
23 154929637 rs35185538 CT C -0.0059923 0.0221833 0.7871020 0.7870625 0.2348470 0.3011920 1460
23 154929952 rs4012982 CAA C -0.0095592 0.0223668 0.6691631 0.6690994 0.2431870 0.3165560 1460
23 154930230 rs781880 A G -0.0064720 0.0211518 0.7596648 0.7596202 0.2508150 0.3618540 1460
23 154930487 rs781879 T A -0.0396515 0.0715965 0.5797890 0.5797027 0.0201638 0.1263580 1460

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.118543 ES:SE:LP:AF:SS:ID   -0.0404234:0.0309245:0.718133:0.118543:1460:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.123985 ES:SE:LP:AF:SS:ID   -0.0208518:0.0298441:0.314385:0.123985:1460:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.105013 ES:SE:LP:AF:SS:ID   -0.029228:0.0329951:0.424975:0.105013:1460:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154768    ES:SE:LP:AF:SS:ID   -0.0593015:0.0844093:0.316545:0.0154768:1460:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0634515    ES:SE:LP:AF:SS:ID   -0.0338285:0.0408409:0.389723:0.0634515:1460:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.130152 ES:SE:LP:AF:SS:ID   -0.0165202:0.0284344:0.250777:0.130152:1460:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.129957 ES:SE:LP:AF:SS:ID   -0.0232824:0.0299059:0.360126:0.129957:1460:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.129298 ES:SE:LP:AF:SS:ID   -0.0192172:0.0283532:0.302752:0.129298:1460:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.860301 ES:SE:LP:AF:SS:ID   0.0232823:0.0275823:0.399297:0.860301:1460:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.133986 ES:SE:LP:AF:SS:ID   -0.0241191:0.0273148:0.42322:0.133986:1460:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.150936 ES:SE:LP:AF:SS:ID   -0.0192479:0.027236:0.318883:0.150936:1460:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.134012 ES:SE:LP:AF:SS:ID   -0.0241804:0.0272972:0.424972:0.134012:1460:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.860564 ES:SE:LP:AF:SS:ID   0.0191677:0.0267385:0.324608:0.860564:1460:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.8639   ES:SE:LP:AF:SS:ID   0.0199649:0.0270515:0.336662:0.8639:1460:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.138899 ES:SE:LP:AF:SS:ID   -0.017529:0.0267967:0.28978:0.138899:1460:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0380137    ES:SE:LP:AF:SS:ID   -0.0343473:0.0491277:0.314638:0.0380137:1460:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.860423 ES:SE:LP:AF:SS:ID   0.0195473:0.0267441:0.332587:0.860423:1460:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.860426 ES:SE:LP:AF:SS:ID   0.0195528:0.0267454:0.332682:0.860426:1460:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.860412 ES:SE:LP:AF:SS:ID   0.0195972:0.0267431:0.333666:0.860412:1460:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.859905 ES:SE:LP:AF:SS:ID   0.0200563:0.0266458:0.345098:0.859905:1460:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.136398 ES:SE:LP:AF:SS:ID   -0.0174757:0.0271416:0.284196:0.136398:1460:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.859589 ES:SE:LP:AF:SS:ID   0.0198899:0.0265991:0.342251:0.859589:1460:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.858598 ES:SE:LP:AF:SS:ID   0.0218139:0.0265798:0.385149:0.858598:1460:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.859628 ES:SE:LP:AF:SS:ID   0.0200559:0.0266098:0.345679:0.859628:1460:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.859629 ES:SE:LP:AF:SS:ID   0.0200575:0.0266107:0.345699:0.859629:1460:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.859659 ES:SE:LP:AF:SS:ID   0.020105:0.0266151:0.346659:0.859659:1460:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.859984 ES:SE:LP:AF:SS:ID   0.020608:0.0266644:0.356815:0.859984:1460:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.107595 ES:SE:LP:AF:SS:ID   -0.0186656:0.031024:0.261614:0.107595:1460:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.864017 ES:SE:LP:AF:SS:ID   0.0236532:0.0270527:0.417845:0.864017:1460:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.853446 ES:SE:LP:AF:SS:ID   0.023343:0.02657:0.420452:0.853446:1460:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.858163 ES:SE:LP:AF:SS:ID   0.0221696:0.0266972:0.390998:0.858163:1460:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.855672 ES:SE:LP:AF:SS:ID   0.0166048:0.0268502:0.270516:0.855672:1460:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.10646  ES:SE:LP:AF:SS:ID   -0.024242:0.0323513:0.343157:0.10646:1460:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.861189 ES:SE:LP:AF:SS:ID   0.0199305:0.0271904:0.333783:0.861189:1460:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.861189 ES:SE:LP:AF:SS:ID   0.0199305:0.0271904:0.333783:0.861189:1460:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.861183 ES:SE:LP:AF:SS:ID   0.0199341:0.0271908:0.333851:0.861183:1460:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.861444 ES:SE:LP:AF:SS:ID   0.0207667:0.0271843:0.351603:0.861444:1460:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.136011 ES:SE:LP:AF:SS:ID   -0.0245053:0.027133:0.435815:0.136011:1460:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.116038 ES:SE:LP:AF:SS:ID   -0.0118633:0.0293913:0.163332:0.116038:1460:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.844562 ES:SE:LP:AF:SS:ID   0.0188783:0.0265073:0.321972:0.844562:1460:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837436 ES:SE:LP:AF:SS:ID   0.05989:0.027621:1.51853:0.837436:1460:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.754727 ES:SE:LP:AF:SS:ID   0.0434418:0.0214769:1.36364:0.754727:1460:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.103767 ES:SE:LP:AF:SS:ID   -0.0557594:0.0305016:1.16912:0.103767:1460:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.139592 ES:SE:LP:AF:SS:ID   -0.0207208:0.0267367:0.35806:0.139592:1460:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.139239 ES:SE:LP:AF:SS:ID   -0.0199281:0.0267277:0.341004:0.139239:1460:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.103078 ES:SE:LP:AF:SS:ID   -0.0553301:0.0307674:1.14066:0.103078:1460:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.101967 ES:SE:LP:AF:SS:ID   -0.0549212:0.0311031:1.10988:0.101967:1460:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.817956 ES:SE:LP:AF:SS:ID   0.035201:0.02601:0.75411:0.817956:1460:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.859637 ES:SE:LP:AF:SS:ID   0.0202592:0.0266517:0.34941:0.859637:1460:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.13922  ES:SE:LP:AF:SS:ID   -0.0203918:0.0267157:0.351233:0.13922:1460:rs59066358