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-30600_raw/ukb-d-30600_raw.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-30600_raw/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 16:31:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30600_raw/ukb-d-30600_raw.vcf.gz ...
Read summary statistics for 13585333 SNPs.
Dropped 12711 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.118 (0.0071)
Lambda GC: 1.4737
Mean Chi^2: 1.8488
Intercept: 1.1182 (0.0151)
Ratio: 0.1392 (0.0178)
Analysis finished at Mon Nov 25 16:34:03 2019
Total time elapsed: 2.0m:17.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2927,
    "mean_EFFECT": -0.0001,
    "n": 315268,
    "n_snps": 13585333,
    "n_clumped_hits": 201,
    "n_p_sig": 32660,
    "n_mono": 0,
    "n_ns": 1251735,
    "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": 569017,
    "n_est": 316513.0336,
    "ratio_se_n": 1.002,
    "mean_diff": 0.0001,
    "ratio_diff": 39.3217,
    "sd_y_est1": 2.5617,
    "sd_y_est2": 2.5668,
    "r2_sum1": 0.3332,
    "r2_sum2": 0.0508,
    "r2_sum3": 0.0506,
    "r2_sum4": 0.0507,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.118,
    "ldsc_observed_scale_h2_se": 0.0071,
    "ldsc_intercept_beta": 1.1182,
    "ldsc_intercept_se": 0.0151,
    "ldsc_lambda_gc": 1.4737,
    "ldsc_mean_chisq": 1.8488,
    "ldsc_ratio": 0.1393
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 13573286 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57081 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33334 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051263e+00 6.184954e+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 7.902541e+07 5.591517e+07 3.02000e+02 3.293054e+07 7.013908e+07 1.148601e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.366000e-04 3.928250e-02 -9.31560e-01 -1.188000e-02 -8.600000e-05 1.170700e-02 6.886300e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.710520e-02 2.614550e-02 5.29760e-03 7.718400e-03 1.422100e-02 3.895000e-02 1.318500e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.574598e-01 3.015045e-01 0.00000e+00 1.858301e-01 4.431503e-01 7.189704e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.574593e-01 3.015048e-01 0.00000e+00 1.858302e-01 4.431451e-01 7.189688e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908194e-01 2.544077e-01 1.00000e-03 7.433800e-03 6.004500e-02 2.953300e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569017 0.9581153 NA NA NA NA NA 1.963463e-01 2.471050e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.152680e+05 0.000000e+00 3.15268e+05 3.152680e+05 3.152680e+05 3.152680e+05 3.152680e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0122520 0.011300 0.2782499 0.2782549 0.1105300 0.1894970 315268
1 693731 rs12238997 A G -0.0202170 0.010674 0.0582331 0.0582195 0.1158400 0.1417730 315268
1 707522 rs371890604 G C -0.0207170 0.012010 0.0845376 0.0845312 0.0972060 0.1293930 315268
1 717587 rs144155419 G A 0.0080514 0.028599 0.7783107 0.7783060 0.0157100 0.0045926 315268
1 723329 rs189787166 A T 0.0157760 0.084454 0.8518199 0.8518175 0.0017344 0.0003994 315268
1 730087 rs148120343 T C -0.0235850 0.014871 0.1127400 0.1127455 0.0564660 0.0127796 315268
1 731718 rs142557973 T C -0.0196100 0.010126 0.0527886 0.0527944 0.1217200 0.1543530 315268
1 732032 rs61770163 A C -0.0158290 0.010806 0.1429799 0.1429661 0.1210700 0.1555510 315268
1 734349 rs141242758 T C -0.0197960 0.010131 0.0506991 0.0507009 0.1209400 0.1525560 315268
1 740284 rs61770167 C T -0.0050288 0.046462 0.9138100 0.9138095 0.0057510 0.0023962 315268
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0037899 0.0116920 0.7458200 0.7458285 0.056093 0.0309934 315268
23 154923374 rs111332691 T A -0.0084475 0.0127960 0.5091304 0.5091465 0.044998 0.0116556 315268
23 154925045 rs509981 C T -0.0076971 0.0061764 0.2126802 0.2126868 0.245780 0.3634440 315268
23 154925895 rs538470 C T -0.0085787 0.0063181 0.1745300 0.1745280 0.242070 0.3634440 315268
23 154927581 rs644138 G A -0.0079819 0.0058093 0.1694502 0.1694459 0.302250 0.4635760 315268
23 154929412 rs557132 C T -0.0079864 0.0061782 0.1961201 0.1961238 0.245630 0.3568210 315268
23 154929637 rs35185538 CT C -0.0148130 0.0064469 0.0215750 0.0215792 0.230030 0.3011920 315268
23 154929952 rs4012982 CAA C -0.0081368 0.0064973 0.2104500 0.2104476 0.239560 0.3165560 315268
23 154930230 rs781880 A G -0.0089334 0.0061775 0.1481399 0.1481438 0.246010 0.3618540 315268
23 154930487 rs781879 T A 0.0222140 0.0212220 0.2952100 0.2952177 0.019483 0.1263580 315268

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11053  ES:SE:LP:AF:SS:ID   -0.012252:0.0113:0.555565:0.11053:315268:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11584  ES:SE:LP:AF:SS:ID   -0.020217:0.010674:1.23483:0.11584:315268:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097206 ES:SE:LP:AF:SS:ID   -0.020717:0.01201:1.07295:0.097206:315268:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.01571  ES:SE:LP:AF:SS:ID   0.0080514:0.028599:0.108847:0.01571:315268:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017344    ES:SE:LP:AF:SS:ID   0.015776:0.084454:0.0696522:0.0017344:315268:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056466 ES:SE:LP:AF:SS:ID   -0.023585:0.014871:0.947922:0.056466:315268:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12172  ES:SE:LP:AF:SS:ID   -0.01961:0.010126:1.27746:0.12172:315268:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12107  ES:SE:LP:AF:SS:ID   -0.015829:0.010806:0.844725:0.12107:315268:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12094  ES:SE:LP:AF:SS:ID   -0.019796:0.010131:1.295:0.12094:315268:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.005751 ES:SE:LP:AF:SS:ID   -0.0050288:0.046462:0.0391441:0.005751:315268:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018561    ES:SE:LP:AF:SS:ID   0.10816:0.088175:0.657637:0.0018561:315268:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86975  ES:SE:LP:AF:SS:ID   0.015622:0.009988:0.928855:0.86975:315268:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015181    ES:SE:LP:AF:SS:ID   -0.070677:0.090793:0.360205:0.0015181:315268:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12291  ES:SE:LP:AF:SS:ID   -0.017275:0.0098922:1.09283:0.12291:315268:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14272  ES:SE:LP:AF:SS:ID   -0.014647:0.0097755:0.872733:0.14272:315268:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12302  ES:SE:LP:AF:SS:ID   -0.017259:0.0098783:1.09356:0.12302:315268:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87097  ES:SE:LP:AF:SS:ID   0.014148:0.0096285:0.848538:0.87097:315268:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.8755   ES:SE:LP:AF:SS:ID   0.017449:0.0097855:1.12744:0.8755:315268:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12858  ES:SE:LP:AF:SS:ID   -0.014217:0.0096517:0.851582:0.12858:315268:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036314 ES:SE:LP:AF:SS:ID   0.016458:0.017517:0.459108:0.036314:315268:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.013473:0.0096181:0.792473:0.87056:315268:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87067  ES:SE:LP:AF:SS:ID   0.014035:0.0096229:0.839471:0.87067:315268:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.013468:0.0096178:0.792043:0.87056:315268:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050386    ES:SE:LP:AF:SS:ID   0.095538:0.049333:1.2774:0.0050386:315268:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050052    ES:SE:LP:AF:SS:ID   0.095382:0.049467:1.26898:0.0050052:315268:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055164    ES:SE:LP:AF:SS:ID   -0.0014682:0.048106:0.010706:0.0055164:315268:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87065  ES:SE:LP:AF:SS:ID   0.01351:0.0096018:0.797484:0.87065:315268:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   -0.014986:0.0097958:0.899457:0.12592:315268:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87022  ES:SE:LP:AF:SS:ID   0.013321:0.0095789:0.784257:0.87022:315268:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   0.012093:0.0095702:0.685396:0.86949:315268:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.012911:0.009587:0.749385:0.87037:315268:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.012919:0.0095876:0.749971:0.87037:315268:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   0.012827:0.0095879:0.742417:0.87038:315268:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87082  ES:SE:LP:AF:SS:ID   0.013373:0.0096123:0.784759:0.87082:315268:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098798 ES:SE:LP:AF:SS:ID   -0.025191:0.011171:1.61742:0.098798:315268:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0063989    ES:SE:LP:AF:SS:ID   -0.0072353:0.043469:0.0615753:0.0063989:315268:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87467  ES:SE:LP:AF:SS:ID   0.017093:0.009753:1.09873:0.87467:315268:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   0.012228:0.0095674:0.69635:0.8641:315268:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   0.013831:0.0096582:0.817757:0.86949:315268:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86645  ES:SE:LP:AF:SS:ID   0.015377:0.0096602:0.952959:0.86645:315268:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098789 ES:SE:LP:AF:SS:ID   -0.014161:0.011561:0.656414:0.098789:315268:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.017481:0.0097696:1.13333:0.87161:315268:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.017482:0.0097696:1.13347:0.87161:315268:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.017454:0.0097698:1.13072:0.87161:315268:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87197  ES:SE:LP:AF:SS:ID   0.017806:0.0097751:1.1642:0.87197:315268:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12554  ES:SE:LP:AF:SS:ID   -0.016375:0.0097823:1.02623:0.12554:315268:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10537  ES:SE:LP:AF:SS:ID   -0.022612:0.010655:1.47079:0.10537:315268:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85544  ES:SE:LP:AF:SS:ID   0.014124:0.0095629:0.854897:0.85544:315268:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016523    ES:SE:LP:AF:SS:ID   0.014339:0.084687:0.0627078:0.0016523:315268:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83824  ES:SE:LP:AF:SS:ID   -0.0057955:0.0094071:0.269339:0.83824:315268:rs376645387