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-20428/ukb-d-20428.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-20428/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 17:12:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20428/ukb-d-20428.vcf.gz ...
Read summary statistics for 13543745 SNPs.
Dropped 12660 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, 1283493 SNPs remain.
After merging with regression SNP LD, 1283493 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0396 (0.0115)
Lambda GC: 1.024
Mean Chi^2: 1.0259
Intercept: 0.9972 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:14:21 2019
Total time elapsed: 2.0m:3.31s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0202,
    "mean_EFFECT": 0,
    "n": 36366,
    "n_snps": 13543745,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250287,
    "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": 557968,
    "n_est": 36478.3915,
    "ratio_se_n": 1.0015,
    "mean_diff": 0,
    "ratio_diff": 17.1764,
    "sd_y_est1": 0.4891,
    "sd_y_est2": 0.4898,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283493,
    "ldsc_nsnp_merge_regression_ld": 1283493,
    "ldsc_observed_scale_h2_beta": 0.0396,
    "ldsc_observed_scale_h2_se": 0.0115,
    "ldsc_intercept_beta": 0.9972,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.024,
    "ldsc_mean_chisq": 1.0259,
    "ldsc_ratio": -0.1081
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
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 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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 13531749 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57004 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33310 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051507e+00 6.185067e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902350e+07 5.591531e+07 3.02000e+02 3.292488e+07 7.013931e+07 1.148568e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.100000e-05 2.107350e-02 -2.92742e-01 -5.599200e-03 9.500000e-06 5.634800e-03 2.470040e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.511620e-02 1.455180e-02 3.08220e-03 4.332600e-03 7.950400e-03 2.168730e-02 8.015620e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.969529e-01 2.894654e-01 3.00000e-07 2.453268e-01 4.957104e-01 7.475685e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.969485e-01 2.894680e-01 3.00000e-07 2.453197e-01 4.957052e-01 7.475662e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.913692e-01 2.545400e-01 1.00000e-03 7.579200e-03 6.068510e-02 2.964870e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 557968 0.9588025 NA NA NA NA NA 1.967443e-01 2.471903e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.636600e+04 0.000000e+00 3.63660e+04 3.636600e+04 3.636600e+04 3.636600e+04 3.636600e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0089094 0.0063096 0.1579440 0.1579355 0.1122420 0.1894970 36366
1 693731 rs12238997 A G 0.0080227 0.0059578 0.1781222 0.1781138 0.1174560 0.1417730 36366
1 707522 rs371890604 G C 0.0070560 0.0066929 0.2917743 0.2917671 0.0990527 0.1293930 36366
1 717587 rs144155419 G A 0.0116306 0.0157039 0.4589285 0.4589247 0.0163901 0.0045926 36366
1 723329 rs189787166 A T 0.0347339 0.0463861 0.4539824 0.4539779 0.0018222 0.0003994 36366
1 730087 rs148120343 T C 0.0022460 0.0082733 0.7860298 0.7860273 0.0572163 0.0127796 36366
1 731718 rs142557973 T C 0.0063101 0.0056469 0.2638080 0.2638007 0.1240130 0.1543530 36366
1 732032 rs61770163 A C 0.0088484 0.0060211 0.1416899 0.1416817 0.1234320 0.1555510 36366
1 734349 rs141242758 T C 0.0066982 0.0056513 0.2359310 0.2359233 0.1232020 0.1525560 36366
1 740284 rs61770167 C T 0.0070954 0.0265342 0.7891581 0.7891570 0.0056011 0.0023962 36366
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0018222 0.0067795 0.7881030 0.7881011 0.0566664 0.0309934 36366
23 154923374 rs111332691 T A -0.0022398 0.0075707 0.7673509 0.7673484 0.0438596 0.0116556 36366
23 154925045 rs509981 C T 0.0008126 0.0036127 0.8220340 0.8220324 0.2431230 0.3634440 36366
23 154925895 rs538470 C T 0.0007899 0.0036942 0.8306919 0.8306904 0.2395350 0.3634440 36366
23 154927581 rs644138 G A 0.0002493 0.0033899 0.9413840 0.9413838 0.3002490 0.4635760 36366
23 154929412 rs557132 C T 0.0006990 0.0036138 0.8466170 0.8466161 0.2429610 0.3568210 36366
23 154929637 rs35185538 CT C 0.0044170 0.0037726 0.2416713 0.2416634 0.2274650 0.3011920 36366
23 154929952 rs4012982 CAA C -0.0000628 0.0038065 0.9868330 0.9868325 0.2373370 0.3165560 36366
23 154930230 rs781880 A G 0.0006102 0.0036131 0.8658780 0.8658772 0.2432630 0.3618540 36366
23 154930487 rs781879 T A -0.0002658 0.0119855 0.9823040 0.9823042 0.0202333 0.1263580 36366

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112242 ES:SE:LP:AF:SS:ID   0.00890945:0.00630959:0.801497:0.112242:36366:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117456 ES:SE:LP:AF:SS:ID   0.0080227:0.00595781:0.749282:0.117456:36366:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0990527    ES:SE:LP:AF:SS:ID   0.00705602:0.00669291:0.534953:0.0990527:36366:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0163901    ES:SE:LP:AF:SS:ID   0.0116306:0.0157039:0.338255:0.0163901:36366:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00182216   ES:SE:LP:AF:SS:ID   0.0347339:0.0463861:0.342961:0.00182216:36366:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0572163    ES:SE:LP:AF:SS:ID   0.00224598:0.00827331:0.104561:0.0572163:36366:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124013 ES:SE:LP:AF:SS:ID   0.0063101:0.00564686:0.578712:0.124013:36366:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123432 ES:SE:LP:AF:SS:ID   0.00884841:0.00602114:0.848661:0.123432:36366:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123202 ES:SE:LP:AF:SS:ID   0.00669816:0.00565132:0.627215:0.123202:36366:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00560112   ES:SE:LP:AF:SS:ID   0.00709539:0.0265342:0.102836:0.00560112:36366:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00201632   ES:SE:LP:AF:SS:ID   0.111214:0.0467951:1.75754:0.00201632:36366:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867317 ES:SE:LP:AF:SS:ID   -0.00643804:0.00555257:0.608585:0.867317:36366:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00145509   ES:SE:LP:AF:SS:ID   0.0780919:0.0521918:0.870965:0.00145509:36366:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.125223 ES:SE:LP:AF:SS:ID   0.00786968:0.00550762:0.815167:0.125223:36366:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14514  ES:SE:LP:AF:SS:ID   0.00567635:0.00544761:0.526624:0.14514:36366:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125295 ES:SE:LP:AF:SS:ID   0.00788633:0.00550053:0.819143:0.125295:36366:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868066 ES:SE:LP:AF:SS:ID   -0.00859429:0.00536301:0.96237:0.868066:36366:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873105 ES:SE:LP:AF:SS:ID   -0.00882471:0.00545045:0.976999:0.873105:36366:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131396 ES:SE:LP:AF:SS:ID   0.00776484:0.00537522:0.82801:0.131396:36366:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0362564    ES:SE:LP:AF:SS:ID   0.00895087:0.00984609:0.439717:0.0362564:36366:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867609 ES:SE:LP:AF:SS:ID   -0.00848037:0.00535543:0.945716:0.867609:36366:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867681 ES:SE:LP:AF:SS:ID   -0.00860813:0.00535657:0.966343:0.867681:36366:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867603 ES:SE:LP:AF:SS:ID   -0.00848195:0.00535519:0.946035:0.867603:36366:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00542852   ES:SE:LP:AF:SS:ID   0.0323397:0.0266227:0.648838:0.00542852:36366:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00540281   ES:SE:LP:AF:SS:ID   0.0321227:0.0266774:0.641013:0.00540281:36366:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.005916 ES:SE:LP:AF:SS:ID   -0.00415553:0.0259087:0.0591982:0.005916:36366:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86774  ES:SE:LP:AF:SS:ID   -0.00834142:0.00534859:0.924913:0.86774:36366:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128641 ES:SE:LP:AF:SS:ID   0.00814147:0.00545345:0.868154:0.128641:36366:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867225 ES:SE:LP:AF:SS:ID   -0.00827507:0.00533398:0.917872:0.867225:36366:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866651 ES:SE:LP:AF:SS:ID   -0.00849218:0.00532973:0.954333:0.866651:36366:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867414 ES:SE:LP:AF:SS:ID   -0.00823482:0.00533927:0.910074:0.867414:36366:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867422 ES:SE:LP:AF:SS:ID   -0.00823082:0.00533961:0.909347:0.867422:36366:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867424 ES:SE:LP:AF:SS:ID   -0.00823552:0.00533963:0.910095:0.867424:36366:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867875 ES:SE:LP:AF:SS:ID   -0.00838566:0.00535346:0.930835:0.867875:36366:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100516 ES:SE:LP:AF:SS:ID   0.00449842:0.00622166:0.328209:0.100516:36366:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0068429    ES:SE:LP:AF:SS:ID   -0.00027075:0.0235021:0.0040105:0.0068429:36366:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872172 ES:SE:LP:AF:SS:ID   -0.00811657:0.005435:0.868561:0.872172:36366:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.861039 ES:SE:LP:AF:SS:ID   -0.00919785:0.00532291:1.07572:0.861039:36366:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866824 ES:SE:LP:AF:SS:ID   -0.0084776:0.00538591:0.937459:0.866824:36366:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.863828 ES:SE:LP:AF:SS:ID   -0.00741162:0.00538436:0.772954:0.863828:36366:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100951 ES:SE:LP:AF:SS:ID   0.0121408:0.00642447:1.23066:0.100951:36366:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869049 ES:SE:LP:AF:SS:ID   -0.00694382:0.00544282:0.694556:0.869049:36366:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869049 ES:SE:LP:AF:SS:ID   -0.00694406:0.00544282:0.694591:0.869049:36366:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869045 ES:SE:LP:AF:SS:ID   -0.0069446:0.00544283:0.694664:0.869045:36366:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869424 ES:SE:LP:AF:SS:ID   -0.00725912:0.00544534:0.738711:0.869424:36366:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12806  ES:SE:LP:AF:SS:ID   0.00728672:0.00545222:0.741353:0.12806:36366:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106983 ES:SE:LP:AF:SS:ID   0.00409449:0.00594197:0.309116:0.106983:36366:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852819 ES:SE:LP:AF:SS:ID   -0.00933951:0.00532267:1.10059:0.852819:36366:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00174096   ES:SE:LP:AF:SS:ID   0.0194684:0.0465877:0.170033:0.00174096:36366:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837837 ES:SE:LP:AF:SS:ID   -0.00780502:0.00529669:0.851993:0.837837:36366:rs376645387