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-5540_0/ukb-d-5540_0.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-5540_0/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 16:40:28 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5540_0/ukb-d-5540_0.vcf.gz ...
Read summary statistics for 13529572 SNPs.
Dropped 12636 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, 1283492 SNPs remain.
After merging with regression SNP LD, 1283492 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0422 (0.0146)
Lambda GC: 0.9907
Mean Chi^2: 0.9852
Intercept: 1.0067 (0.0059)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 16:42:34 2019
Total time elapsed: 2.0m:6.29s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0455,
    "mean_EFFECT": -1.2599e-06,
    "n": 25891,
    "n_snps": 13529572,
    "n_clumped_hits": 5,
    "n_p_sig": 242,
    "n_mono": 0,
    "n_ns": 1249813,
    "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": 554387,
    "n_est": 26035.6191,
    "ratio_se_n": 1.0028,
    "mean_diff": -0,
    "ratio_diff": 2.808,
    "sd_y_est1": 0.1051,
    "sd_y_est2": 0.1054,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.007,
    "r2_sum3": 0.007,
    "r2_sum4": 0.0068,
    "ldsc_nsnp_merge_refpanel_ld": 1283492,
    "ldsc_nsnp_merge_regression_ld": 1283492,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0067,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 0.9907,
    "ldsc_mean_chisq": 0.9852,
    "ldsc_ratio": -0.4527
}

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 13517599 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56982 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33313 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.052107e+00 6.184973e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902096e+07 5.591600e+07 302.000000 3.292450e+07 7.013270e+07 1.148524e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.300000e-06 5.314300e-03 -0.106517 -1.305300e-03 6.600000e-05 1.530300e-03 6.217420e-02 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.839200e-03 3.694400e-03 0.000757 1.103600e-03 2.021700e-03 5.503100e-03 1.973400e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.993092e-01 2.856450e-01 0.000000 2.582040e-01 4.904029e-01 7.470557e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.993030e-01 2.856487e-01 0.000000 2.581932e-01 4.903966e-01 7.470526e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.915618e-01 2.545726e-01 0.001000 7.635900e-03 6.098200e-02 2.969020e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 554387 0.9590241 NA NA NA NA NA 1.968939e-01 2.472203e-01 0.000000 5.790700e-03 8.506390e-02 3.091390e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.589100e+04 0.000000e+00 25891.000000 2.589100e+04 2.589100e+04 2.589100e+04 2.589100e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0026868 0.0016154 0.0962787 0.0962654 0.1123900 0.1894970 25891
1 693731 rs12238997 A G -0.0019763 0.0015157 0.1922981 0.1922851 0.1184310 0.1417730 25891
1 707522 rs371890604 G C -0.0029690 0.0017064 0.0818691 0.0818589 0.0994014 0.1293930 25891
1 717587 rs144155419 G A 0.0043673 0.0040582 0.2818643 0.2818548 0.0161054 0.0045926 25891
1 723329 rs189787166 A T -0.0283076 0.0121015 0.0193335 0.0193261 0.0017077 0.0003994 25891
1 730087 rs148120343 T C -0.0036693 0.0021104 0.0821032 0.0820915 0.0578270 0.0127796 25891
1 731718 rs142557973 T C -0.0018294 0.0014387 0.2035462 0.2035328 0.1247330 0.1543530 25891
1 732032 rs61770163 A C -0.0022492 0.0015345 0.1427260 0.1427133 0.1238590 0.1555510 25891
1 734349 rs141242758 T C -0.0018139 0.0014400 0.2077859 0.2077752 0.1239450 0.1525560 25891
1 740284 rs61770167 C T -0.0027411 0.0066816 0.6816305 0.6816257 0.0057356 0.0023962 25891
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0014960 0.0016627 0.3682697 0.3682611 0.0564305 0.0309934 25891
23 154923374 rs111332691 T A 0.0005887 0.0018643 0.7521960 0.7521930 0.0437797 0.0116556 25891
23 154925045 rs509981 C T -0.0008741 0.0008873 0.3245443 0.3245350 0.2451760 0.3634440 25891
23 154925895 rs538470 C T -0.0007119 0.0009065 0.4322739 0.4322675 0.2418920 0.3634440 25891
23 154927581 rs644138 G A -0.0011836 0.0008306 0.1541509 0.1541386 0.3020490 0.4635760 25891
23 154929412 rs557132 C T -0.0008798 0.0008875 0.3215711 0.3215619 0.2450470 0.3568210 25891
23 154929637 rs35185538 CT C -0.0001826 0.0009277 0.8439461 0.8439450 0.2281770 0.3011920 25891
23 154929952 rs4012982 CAA C -0.0009505 0.0009344 0.3090352 0.3090252 0.2390010 0.3165560 25891
23 154930230 rs781880 A G -0.0008153 0.0008879 0.3584726 0.3584644 0.2453960 0.3618540 25891
23 154930487 rs781879 T A 0.0033264 0.0031598 0.2924718 0.2924639 0.0186130 0.1263580 25891

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11239  ES:SE:LP:AF:SS:ID   -0.00268684:0.00161543:1.01647:0.11239:25891:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.118431 ES:SE:LP:AF:SS:ID   -0.00197627:0.00151572:0.716025:0.118431:25891:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0994014    ES:SE:LP:AF:SS:ID   -0.00296905:0.00170635:1.08688:0.0994014:25891:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0161054    ES:SE:LP:AF:SS:ID   0.00436727:0.00405819:0.54996:0.0161054:25891:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00170769   ES:SE:LP:AF:SS:ID   -0.0283076:0.0121015:1.71369:0.00170769:25891:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.057827 ES:SE:LP:AF:SS:ID   -0.00366934:0.00211042:1.08564:0.057827:25891:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124733 ES:SE:LP:AF:SS:ID   -0.00182938:0.0014387:0.691337:0.124733:25891:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123859 ES:SE:LP:AF:SS:ID   -0.00224924:0.00153452:0.845497:0.123859:25891:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123945 ES:SE:LP:AF:SS:ID   -0.00181394:0.00143997:0.682384:0.123945:25891:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00573558   ES:SE:LP:AF:SS:ID   -0.00274111:0.00668163:0.166451:0.00573558:25891:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00177335   ES:SE:LP:AF:SS:ID   -0.00315752:0.0130049:0.0924994:0.00177335:25891:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86687  ES:SE:LP:AF:SS:ID   0.00191172:0.00141974:0.749229:0.86687:25891:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00146633   ES:SE:LP:AF:SS:ID   -0.00585785:0.0133661:0.179667:0.00146633:25891:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.126037 ES:SE:LP:AF:SS:ID   -0.00152203:0.00140602:0.554343:0.126037:25891:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145626 ES:SE:LP:AF:SS:ID   -0.00133168:0.00139258:0.469868:0.145626:25891:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12613  ES:SE:LP:AF:SS:ID   -0.00151185:0.00140403:0.550394:0.12613:25891:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867393 ES:SE:LP:AF:SS:ID   0.00160087:0.00136826:0.61617:0.867393:25891:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872481 ES:SE:LP:AF:SS:ID   0.00136504:0.00139099:0.486206:0.872481:25891:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132095 ES:SE:LP:AF:SS:ID   -0.00151357:0.00137185:0.568786:0.132095:25891:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0376965    ES:SE:LP:AF:SS:ID   -0.000435276:0.00246541:0.0655717:0.0376965:25891:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867039 ES:SE:LP:AF:SS:ID   0.00159083:0.00136748:0.611355:0.867039:25891:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867159 ES:SE:LP:AF:SS:ID   0.00160755:0.00136837:0.619628:0.867159:25891:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.866996 ES:SE:LP:AF:SS:ID   0.00158649:0.00136728:0.60919:0.866996:25891:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00545242   ES:SE:LP:AF:SS:ID   -0.00134711:0.00679851:0.0742085:0.00545242:25891:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00541463   ES:SE:LP:AF:SS:ID   -0.0013578:0.00681818:0.0746095:0.00541463:25891:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00548347   ES:SE:LP:AF:SS:ID   -0.00709798:0.00686605:0.521074:0.00548347:25891:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86719  ES:SE:LP:AF:SS:ID   0.00163078:0.00136486:0.634203:0.86719:25891:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.1293   ES:SE:LP:AF:SS:ID   -0.00164002:0.00139215:0.621991:0.1293:25891:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86673  ES:SE:LP:AF:SS:ID   0.00159314:0.00136127:0.616409:0.86673:25891:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866009 ES:SE:LP:AF:SS:ID   0.00159066:0.00136113:0.615179:0.866009:25891:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866879 ES:SE:LP:AF:SS:ID   0.00161087:0.00136278:0.624885:0.866879:25891:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866886 ES:SE:LP:AF:SS:ID   0.00161055:0.00136289:0.624651:0.866886:25891:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866886 ES:SE:LP:AF:SS:ID   0.00161111:0.00136287:0.624962:0.866886:25891:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86733  ES:SE:LP:AF:SS:ID   0.00161246:0.00136622:0.623569:0.86733:25891:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.101123 ES:SE:LP:AF:SS:ID   -0.00280552:0.00158906:1.11076:0.101123:25891:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00635939   ES:SE:LP:AF:SS:ID   -0.00870075:0.00617601:0.798857:0.00635939:25891:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.871571 ES:SE:LP:AF:SS:ID   0.00146773:0.00138697:0.53766:0.871571:25891:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860407 ES:SE:LP:AF:SS:ID   0.00150482:0.00136212:0.569807:0.860407:25891:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866134 ES:SE:LP:AF:SS:ID   0.00151512:0.00137454:0.568067:0.866134:25891:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86277  ES:SE:LP:AF:SS:ID   0.00152334:0.0013731:0.573066:0.86277:25891:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100258 ES:SE:LP:AF:SS:ID   -0.00181421:0.00165478:0.563938:0.100258:25891:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.868339 ES:SE:LP:AF:SS:ID   0.00135308:0.00139006:0.481009:0.868339:25891:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.868339 ES:SE:LP:AF:SS:ID   0.00135307:0.00139006:0.481003:0.868339:25891:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.868335 ES:SE:LP:AF:SS:ID   0.00135273:0.00139006:0.48084:0.868335:25891:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868821 ES:SE:LP:AF:SS:ID   0.0012243:0.00139135:0.421471:0.868821:25891:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128755 ES:SE:LP:AF:SS:ID   -0.00153327:0.001391:0.568072:0.128755:25891:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107943 ES:SE:LP:AF:SS:ID   -0.0024217:0.00151434:0.959425:0.107943:25891:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.851844 ES:SE:LP:AF:SS:ID   0.0016777:0.0013617:0.661669:0.851844:25891:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00163862   ES:SE:LP:AF:SS:ID   -0.0276223:0.0120613:1.65718:0.00163862:25891:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836921 ES:SE:LP:AF:SS:ID   -0.00151758:0.00134595:0.585806:0.836921:25891:rs376645387