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-30790_irnt/ukb-d-30790_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-30790_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 14:54:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30790_irnt/ukb-d-30790_irnt.vcf.gz ...
Read summary statistics for 13583853 SNPs.
Dropped 12709 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: 0.1476 (0.1327)
Lambda GC: 1.0342
Mean Chi^2: 2.113
Intercept: 1.0097 (0.009)
Ratio: 0.0087 (0.0081)
Analysis finished at Mon Nov 25 14:57:17 2019
Total time elapsed: 2.0m:47.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0238,
    "mean_EFFECT": 0,
    "n": 273896,
    "n_snps": 13583853,
    "n_clumped_hits": 14,
    "n_p_sig": 7974,
    "n_mono": 0,
    "n_ns": 1251716,
    "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": 568583,
    "n_est": 274960.617,
    "ratio_se_n": 1.0019,
    "mean_diff": -2.064e-06,
    "ratio_diff": 1.0327,
    "sd_y_est1": 1.0018,
    "sd_y_est2": 1.0038,
    "r2_sum1": 0.0276,
    "r2_sum2": 0.0275,
    "r2_sum3": 0.0274,
    "r2_sum4": 0.0273,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.1476,
    "ldsc_observed_scale_h2_se": 0.1327,
    "ldsc_intercept_beta": 1.0097,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.0342,
    "ldsc_mean_chisq": 2.113,
    "ldsc_ratio": 0.0087
}

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 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 13571808 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57079 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33336 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051285e+00 6.184985e+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 7.902522e+07 5.591492e+07 3.02000e+02 3.293025e+07 7.013957e+07 1.148595e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.730000e-05 1.710380e-02 -8.34150e-01 -4.232100e-03 7.400000e-06 4.206400e-03 1.604100e+00 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.136970e-02 1.096620e-02 2.22630e-03 3.238300e-03 5.965800e-03 1.633500e-02 5.523000e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.962665e-01 2.897770e-01 0.00000e+00 2.443802e-01 4.949405e-01 7.475100e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.962659e-01 2.897774e-01 0.00000e+00 2.443808e-01 4.949437e-01 7.475118e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908360e-01 2.544079e-01 1.00000e-03 7.439100e-03 6.007200e-02 2.953700e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568583 0.9581427 NA NA NA NA NA 1.963564e-01 2.471036e-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 2.738960e+05 0.000000e+00 2.73896e+05 2.738960e+05 2.738960e+05 2.738960e+05 2.738960e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0073083 0.0047459 0.1235799 0.1235802 0.1103400 0.1894970 273896
1 693731 rs12238997 A G -0.0055884 0.0044798 0.2122198 0.2122265 0.1156800 0.1417730 273896
1 707522 rs371890604 G C -0.0076603 0.0050420 0.1286901 0.1286875 0.0970790 0.1293930 273896
1 717587 rs144155419 G A -0.0015596 0.0120130 0.8967001 0.8967041 0.0156870 0.0045926 273896
1 723329 rs189787166 A T -0.0152530 0.0352330 0.6650802 0.6650743 0.0017565 0.0003994 273896
1 730087 rs148120343 T C -0.0089275 0.0062516 0.1532798 0.1532820 0.0562580 0.0127796 273896
1 731718 rs142557973 T C -0.0070989 0.0042481 0.0947022 0.0947066 0.1215900 0.1543530 273896
1 732032 rs61770163 A C -0.0096156 0.0045341 0.0339461 0.0339446 0.1210100 0.1555510 273896
1 734349 rs141242758 T C -0.0067528 0.0042501 0.1120900 0.1120927 0.1208200 0.1525560 273896
1 740284 rs61770167 C T 0.0050937 0.0195660 0.7946100 0.7946060 0.0057178 0.0023962 273896
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0021411 0.0049169 0.6632298 0.6632305 0.056105 0.0309934 273896
23 154923374 rs111332691 T A -0.0033466 0.0054002 0.5354402 0.5354436 0.044659 0.0116556 273896
23 154925045 rs509981 C T 0.0008770 0.0025962 0.7355192 0.7355274 0.245450 0.3634440 273896
23 154925895 rs538470 C T 0.0008325 0.0026560 0.7539404 0.7539483 0.241770 0.3634440 273896
23 154927581 rs644138 G A 0.0002371 0.0024421 0.9226400 0.9226430 0.301950 0.4635760 273896
23 154929412 rs557132 C T 0.0007280 0.0025969 0.7792306 0.7792329 0.245320 0.3568210 273896
23 154929637 rs35185538 CT C 0.0012679 0.0027099 0.6398807 0.6398725 0.229550 0.3011920 273896
23 154929952 rs4012982 CAA C 0.0000902 0.0027302 0.9736599 0.9736590 0.239420 0.3165560 273896
23 154930230 rs781880 A G 0.0006698 0.0025966 0.7964500 0.7964464 0.245710 0.3618540 273896
23 154930487 rs781879 T A 0.0141980 0.0088599 0.1090400 0.1090448 0.019705 0.1263580 273896

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11034  ES:SE:LP:AF:SS:ID   -0.0073083:0.0047459:0.908052:0.11034:273896:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11568  ES:SE:LP:AF:SS:ID   -0.0055884:0.0044798:0.673214:0.11568:273896:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097079 ES:SE:LP:AF:SS:ID   -0.0076603:0.005042:0.890455:0.097079:273896:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015687 ES:SE:LP:AF:SS:ID   -0.0015596:0.012013:0.0473528:0.015687:273896:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017565    ES:SE:LP:AF:SS:ID   -0.015253:0.035233:0.177126:0.0017565:273896:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056258 ES:SE:LP:AF:SS:ID   -0.0089275:0.0062516:0.814515:0.056258:273896:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12159  ES:SE:LP:AF:SS:ID   -0.0070989:0.0042481:1.02364:0.12159:273896:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12101  ES:SE:LP:AF:SS:ID   -0.0096156:0.0045341:1.46921:0.12101:273896:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12082  ES:SE:LP:AF:SS:ID   -0.0067528:0.0042501:0.950433:0.12082:273896:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057178    ES:SE:LP:AF:SS:ID   0.0050937:0.019566:0.099846:0.0057178:273896:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018548    ES:SE:LP:AF:SS:ID   -0.0047497:0.037055:0.0467188:0.0018548:273896:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86997  ES:SE:LP:AF:SS:ID   0.0039328:0.0041917:0.458271:0.86997:273896:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015055    ES:SE:LP:AF:SS:ID   -0.060291:0.038274:0.938547:0.0015055:273896:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12273  ES:SE:LP:AF:SS:ID   -0.0055463:0.0041506:0.741219:0.12273:273896:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14258  ES:SE:LP:AF:SS:ID   -0.0055361:0.0041015:0.751806:0.14258:273896:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12284  ES:SE:LP:AF:SS:ID   -0.0054969:0.0041446:0.733416:0.12284:273896:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87109  ES:SE:LP:AF:SS:ID   0.0049546:0.0040387:0.657755:0.87109:273896:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87567  ES:SE:LP:AF:SS:ID   0.0046884:0.0041055:0.596091:0.87567:273896:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12844  ES:SE:LP:AF:SS:ID   -0.005132:0.004049:0.688267:0.12844:273896:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036444 ES:SE:LP:AF:SS:ID   -0.0017486:0.0073368:0.0906473:0.036444:273896:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87069  ES:SE:LP:AF:SS:ID   0.0051889:0.0040348:0.702393:0.87069:273896:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87078  ES:SE:LP:AF:SS:ID   0.0053194:0.0040365:0.72686:0.87078:273896:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87068  ES:SE:LP:AF:SS:ID   0.0051842:0.0040346:0.701562:0.87068:273896:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050575    ES:SE:LP:AF:SS:ID   -0.0088435:0.020671:0.174717:0.0050575:273896:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050247    ES:SE:LP:AF:SS:ID   -0.0089242:0.020727:0.176011:0.0050247:273896:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055754    ES:SE:LP:AF:SS:ID   0.0055397:0.02007:0.106493:0.0055754:273896:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87077  ES:SE:LP:AF:SS:ID   0.0048959:0.0040272:0.649558:0.87077:273896:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12579  ES:SE:LP:AF:SS:ID   -0.0051318:0.0041091:0.674259:0.12579:273896:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87033  ES:SE:LP:AF:SS:ID   0.0048371:0.0040175:0.640943:0.87033:273896:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86961  ES:SE:LP:AF:SS:ID   0.0052396:0.0040141:0.717174:0.86961:273896:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87048  ES:SE:LP:AF:SS:ID   0.0048873:0.004021:0.649364:0.87048:273896:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87049  ES:SE:LP:AF:SS:ID   0.004896:0.0040213:0.650917:0.87049:273896:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8705   ES:SE:LP:AF:SS:ID   0.0049162:0.0040214:0.654607:0.8705:273896:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87095  ES:SE:LP:AF:SS:ID   0.0048312:0.0040317:0.636745:0.87095:273896:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098586 ES:SE:LP:AF:SS:ID   -0.0061902:0.0046899:0.72846:0.098586:273896:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064586    ES:SE:LP:AF:SS:ID   0.015464:0.018129:0.404868:0.0064586:273896:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87485  ES:SE:LP:AF:SS:ID   0.0045753:0.0040917:0.579236:0.87485:273896:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86421  ES:SE:LP:AF:SS:ID   0.0049403:0.004013:0.660966:0.86421:273896:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86961  ES:SE:LP:AF:SS:ID   0.0052495:0.0040514:0.70981:0.86961:273896:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86652  ES:SE:LP:AF:SS:ID   0.0054186:0.0040523:0.741914:0.86652:273896:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0985   ES:SE:LP:AF:SS:ID   -0.0045776:0.0048539:0.461363:0.0985:273896:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87171  ES:SE:LP:AF:SS:ID   0.0047423:0.0040986:0.606864:0.87171:273896:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87171  ES:SE:LP:AF:SS:ID   0.0047424:0.0040986:0.606881:0.87171:273896:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87171  ES:SE:LP:AF:SS:ID   0.0047462:0.0040987:0.607532:0.87171:273896:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.8721   ES:SE:LP:AF:SS:ID   0.0047162:0.0041009:0.601834:0.8721:273896:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12536  ES:SE:LP:AF:SS:ID   -0.0054977:0.004104:0.743812:0.12536:273896:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10523  ES:SE:LP:AF:SS:ID   -0.0055629:0.0044709:0.670806:0.10523:273896:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85567  ES:SE:LP:AF:SS:ID   0.0035318:0.0040121:0.421693:0.85567:273896:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016731    ES:SE:LP:AF:SS:ID   -0.023356:0.035334:0.293607:0.0016731:273896:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.8384   ES:SE:LP:AF:SS:ID   0.0025619:0.0039486:0.286963:0.8384:273896:rs376645387