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-20434_irnt/ukb-d-20434_irnt.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-20434_irnt/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 15:31:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20434_irnt/ukb-d-20434_irnt.vcf.gz ...
Read summary statistics for 13558230 SNPs.
Dropped 12675 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0297 (0.0071)
Lambda GC: 1.0377
Mean Chi^2: 1.0361
Intercept: 1.0013 (0.0065)
Ratio: 0.037 (0.1809)
Analysis finished at Mon Nov 25 15:33:22 2019
Total time elapsed: 2.0m:20.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0242,
    "mean_EFFECT": 0,
    "n": 59260,
    "n_snps": 13558230,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1250856,
    "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": 561144,
    "n_est": 59417.1794,
    "ratio_se_n": 1.0013,
    "mean_diff": 2.4453e-07,
    "ratio_diff": 0.1293,
    "sd_y_est1": 0.9481,
    "sd_y_est2": 0.9494,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0297,
    "ldsc_observed_scale_h2_se": 0.0071,
    "ldsc_intercept_beta": 1.0013,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0377,
    "ldsc_mean_chisq": 1.0361,
    "ldsc_ratio": 0.036
}

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 13546218 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57025 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33319 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051421e+00 6.184955e+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 7.902336e+07 5.591547e+07 3.02000e+02 3.292654e+07 7.013466e+07 1.148563e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.010000e-05 3.201120e-02 -4.74617e-01 -8.570100e-03 3.510000e-05 8.594200e-03 3.973920e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.301850e-02 2.217090e-02 4.67770e-03 6.583000e-03 1.209970e-02 3.304420e-02 1.115320e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.963095e-01 2.900009e-01 1.00000e-07 2.436918e-01 4.948687e-01 7.477338e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.963068e-01 2.900025e-01 1.00000e-07 2.436874e-01 4.948667e-01 7.477332e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911757e-01 2.544928e-01 1.00000e-03 7.531200e-03 6.045970e-02 2.960660e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561144 0.9586123 NA NA NA NA NA 1.966002e-01 2.471543e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.087060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.926000e+04 0.000000e+00 5.92600e+04 5.926000e+04 5.926000e+04 5.926000e+04 5.926000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0087757 0.0095666 0.3589724 0.3589681 0.1124230 0.1894970 59260
1 693731 rs12238997 A G -0.0011047 0.0090528 0.9028799 0.9028795 0.1173880 0.1417730 59260
1 707522 rs371890604 G C -0.0181554 0.0101362 0.0732757 0.0732701 0.0991931 0.1293930 59260
1 717587 rs144155419 G A 0.0451176 0.0244755 0.0652785 0.0652738 0.0156760 0.0045926 59260
1 723329 rs189787166 A T -0.1349340 0.0684705 0.0487630 0.0487596 0.0018969 0.0003994 59260
1 730087 rs148120343 T C -0.0209509 0.0125618 0.0953542 0.0953502 0.0575176 0.0127796 59260
1 731718 rs142557973 T C -0.0044569 0.0085853 0.6036664 0.6036653 0.1233970 0.1543530 59260
1 732032 rs61770163 A C -0.0089940 0.0091474 0.3255008 0.3254979 0.1229410 0.1555510 59260
1 734349 rs141242758 T C -0.0036268 0.0085876 0.6727861 0.6727852 0.1226920 0.1525560 59260
1 740284 rs61770167 C T 0.0022553 0.0394709 0.9544360 0.9544356 0.0058214 0.0023962 59260
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0063883 0.0104263 0.5400724 0.5400699 0.0555340 0.0309934 59260
23 154923374 rs111332691 T A -0.0045036 0.0115279 0.6960413 0.6960402 0.0434104 0.0116556 59260
23 154925045 rs509981 C T 0.0028910 0.0054612 0.5965612 0.5965579 0.2449440 0.3634440 59260
23 154925895 rs538470 C T 0.0031224 0.0055848 0.5760962 0.5760941 0.2412120 0.3634440 59260
23 154927581 rs644138 G A 0.0037514 0.0051396 0.4654446 0.4654421 0.3008750 0.4635760 59260
23 154929412 rs557132 C T 0.0027425 0.0054621 0.6156076 0.6156043 0.2448430 0.3568210 59260
23 154929637 rs35185538 CT C 0.0005338 0.0057037 0.9254341 0.9254341 0.2285640 0.3011920 59260
23 154929952 rs4012982 CAA C 0.0033583 0.0057536 0.5594303 0.5594279 0.2385370 0.3165560 59260
23 154930230 rs781880 A G 0.0026389 0.0054613 0.6289484 0.6289473 0.2451450 0.3618540 59260
23 154930487 rs781879 T A 0.0065078 0.0184872 0.7248297 0.7248279 0.0196687 0.1263580 59260

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112423 ES:SE:LP:AF:SS:ID   -0.00877574:0.00956658:0.444939:0.112423:59260:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117388 ES:SE:LP:AF:SS:ID   -0.00110467:0.00905284:0.04437:0.117388:59260:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0991931    ES:SE:LP:AF:SS:ID   -0.0181554:0.0101362:1.13504:0.0991931:59260:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015676 ES:SE:LP:AF:SS:ID   0.0451176:0.0244755:1.18523:0.015676:59260:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00189689   ES:SE:LP:AF:SS:ID   -0.134934:0.0684705:1.31191:0.00189689:59260:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0575176    ES:SE:LP:AF:SS:ID   -0.0209509:0.0125618:1.02066:0.0575176:59260:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123397 ES:SE:LP:AF:SS:ID   -0.00445694:0.00858529:0.219203:0.123397:59260:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122941 ES:SE:LP:AF:SS:ID   -0.00899396:0.00914743:0.487448:0.122941:59260:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122692 ES:SE:LP:AF:SS:ID   -0.00362681:0.00858765:0.172123:0.122692:59260:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00582137   ES:SE:LP:AF:SS:ID   0.00225527:0.0394709:0.0202532:0.00582137:59260:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00184964   ES:SE:LP:AF:SS:ID   0.0268939:0.0749922:0.14274:0.00184964:59260:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867827 ES:SE:LP:AF:SS:ID   0.0121468:0.00845627:0.821354:0.867827:59260:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00156059   ES:SE:LP:AF:SS:ID   -0.0292101:0.0760061:0.154438:0.00156059:59260:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124997 ES:SE:LP:AF:SS:ID   -0.00922157:0.00837162:0.567557:0.124997:59260:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144455 ES:SE:LP:AF:SS:ID   -0.00735423:0.00829229:0.425796:0.144455:59260:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125097 ES:SE:LP:AF:SS:ID   -0.00925464:0.00836063:0.571334:0.125097:59260:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868706 ES:SE:LP:AF:SS:ID   0.00587799:0.00815077:0.32715:0.868706:59260:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873321 ES:SE:LP:AF:SS:ID   0.00859843:0.00828127:0.524133:0.873321:59260:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130719 ES:SE:LP:AF:SS:ID   -0.00591021:0.0081738:0.328234:0.130719:59260:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365592    ES:SE:LP:AF:SS:ID   -0.00134548:0.0148936:0.0324436:0.0365592:59260:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868323 ES:SE:LP:AF:SS:ID   0.0057117:0.00814305:0.316013:0.868323:59260:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868404 ES:SE:LP:AF:SS:ID   0.00551487:0.00814568:0.302432:0.868404:59260:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868327 ES:SE:LP:AF:SS:ID   0.0056238:0.00814282:0.309989:0.868327:59260:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00513037   ES:SE:LP:AF:SS:ID   -0.0364376:0.0417825:0.416609:0.00513037:59260:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509804   ES:SE:LP:AF:SS:ID   -0.0358133:0.0418767:0.406228:0.00509804:59260:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00569676   ES:SE:LP:AF:SS:ID   0.0422259:0.0401917:0.532481:0.00569676:59260:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868363 ES:SE:LP:AF:SS:ID   0.00579262:0.008128:0.322347:0.868363:59260:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128049 ES:SE:LP:AF:SS:ID   -0.00802814:0.00829586:0.477316:0.128049:59260:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867896 ES:SE:LP:AF:SS:ID   0.00575746:0.00810715:0.320935:0.867896:59260:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867337 ES:SE:LP:AF:SS:ID   0.0052168:0.00810296:0.284248:0.867337:59260:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868083 ES:SE:LP:AF:SS:ID   0.00538805:0.00811496:0.295236:0.868083:59260:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868089 ES:SE:LP:AF:SS:ID   0.00538044:0.00811553:0.294697:0.868089:59260:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868092 ES:SE:LP:AF:SS:ID   0.00538262:0.00811557:0.294842:0.868092:59260:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86849  ES:SE:LP:AF:SS:ID   0.00594556:0.00813508:0.332668:0.86849:59260:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100778 ES:SE:LP:AF:SS:ID   -0.0178619:0.00943374:1.23426:0.100778:59260:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00660258   ES:SE:LP:AF:SS:ID   0.0171164:0.0364491:0.194741:0.00660258:59260:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872528 ES:SE:LP:AF:SS:ID   0.00775962:0.00825967:0.459046:0.872528:59260:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.861967 ES:SE:LP:AF:SS:ID   0.00593381:0.00810266:0.333509:0.861967:59260:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867248 ES:SE:LP:AF:SS:ID   0.0072985:0.00818248:0.428974:0.867248:59260:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86448  ES:SE:LP:AF:SS:ID   0.00460132:0.00819153:0.240853:0.86448:59260:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.10092  ES:SE:LP:AF:SS:ID   -0.0051389:0.00976338:0.222826:0.10092:59260:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869516 ES:SE:LP:AF:SS:ID   0.00672248:0.0082797:0.380032:0.869516:59260:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869516 ES:SE:LP:AF:SS:ID   0.00672246:0.0082797:0.380031:0.869516:59260:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869513 ES:SE:LP:AF:SS:ID   0.00671948:0.00827971:0.379814:0.869513:59260:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869817 ES:SE:LP:AF:SS:ID   0.00710617:0.00828226:0.407939:0.869817:59260:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.127655 ES:SE:LP:AF:SS:ID   -0.00699923:0.00828758:0.399716:0.127655:59260:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107266 ES:SE:LP:AF:SS:ID   -0.0125861:0.00900552:0.789842:0.107266:59260:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853302 ES:SE:LP:AF:SS:ID   0.00309326:0.00810266:0.153266:0.853302:59260:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00180054   ES:SE:LP:AF:SS:ID   -0.127186:0.0690064:1.18496:0.00180054:59260:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837549 ES:SE:LP:AF:SS:ID   0.00499513:0.00802734:0.272646:0.837549:59260:rs376645387