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-22617_1163/ukb-d-22617_1163.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-22617_1163/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 14:58:57 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22617_1163/ukb-d-22617_1163.vcf.gz ...
Read summary statistics for 10227567 SNPs.
Dropped 8004 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, 1279589 SNPs remain.
After merging with regression SNP LD, 1279589 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0079 (0.0051)
Lambda GC: 0.9959
Mean Chi^2: 1.0055
Intercept: 0.9915 (0.0069)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 15:00:34 2019
Total time elapsed: 1.0m:36.13s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9427,
    "inflation_factor": 1.0022,
    "mean_EFFECT": 4.8905e-07,
    "n": 91149,
    "n_snps": 10227567,
    "n_clumped_hits": 1,
    "n_p_sig": 12,
    "n_mono": 0,
    "n_ns": 1096593,
    "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": 201415,
    "n_est": 91216.4435,
    "ratio_se_n": 1.0004,
    "mean_diff": 2.7369e-06,
    "ratio_diff": 8.4819,
    "sd_y_est1": 0.1378,
    "sd_y_est2": 0.1378,
    "r2_sum1": 6.3318e-06,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1279589,
    "ldsc_nsnp_merge_regression_ld": 1279589,
    "ldsc_observed_scale_h2_beta": 0.0079,
    "ldsc_observed_scale_h2_se": 0.0051,
    "ldsc_intercept_beta": 0.9915,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 0.9959,
    "ldsc_mean_chisq": 1.0055,
    "ldsc_ratio": -1.5455
}

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 10220123 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 48929 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30440 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.078861e+00 6.178202e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.876843e+07 5.606096e+07 3.0200e+02 3.252499e+07 6.968765e+07 1.147161e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.000000e-07 1.645100e-03 -1.5429e-02 -7.387000e-04 -7.700000e-06 7.209000e-04 2.156270e-02 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.386600e-03 8.800000e-04 5.3320e-04 7.140000e-04 9.865000e-04 1.806600e-03 5.071200e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.990962e-01 2.888956e-01 0.0000e+00 2.485988e-01 4.995385e-01 7.492763e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.990944e-01 2.888966e-01 0.0000e+00 2.485966e-01 4.995363e-01 7.492753e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.494118e-01 2.628830e-01 7.1306e-03 3.475780e-02 1.418160e-01 3.985430e-01 9.928690e-01 ▇▂▂▁▁
numeric AF_reference 201415 0.9803067 NA NA NA NA NA 2.491715e-01 2.537551e-01 0.0000e+00 3.773960e-02 1.582470e-01 3.951680e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 9.114900e+04 0.000000e+00 9.1149e+04 9.114900e+04 9.114900e+04 9.114900e+04 9.114900e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0014087 0.0011279 0.2117020 0.2116990 0.1114870 0.1894970 91149
1 693731 rs12238997 A G 0.0002363 0.0010683 0.8249520 0.8249524 0.1164590 0.1417730 91149
1 707522 rs371890604 G C -0.0000635 0.0012005 0.9577951 0.9577947 0.0978765 0.1293930 91149
1 717587 rs144155419 G A 0.0046874 0.0028617 0.1014290 0.1014255 0.0157837 0.0045926 91149
1 730087 rs148120343 T C 0.0004922 0.0014807 0.7396019 0.7396008 0.0569973 0.0127796 91149
1 731718 rs142557973 T C 0.0001009 0.0010137 0.9206781 0.9206780 0.1223590 0.1543530 91149
1 732032 rs61770163 A C -0.0000707 0.0010809 0.9478120 0.9478123 0.1220470 0.1555510 91149
1 734349 rs141242758 T C 0.0001270 0.0010145 0.9004131 0.9004131 0.1215880 0.1525560 91149
1 749963 rs529266287 T TAA -0.0001798 0.0009979 0.8569820 0.8569816 0.8689170 0.7641770 91149
1 751343 rs28544273 T A 0.0001759 0.0009894 0.8589150 0.8589147 0.1236990 0.2426120 91149
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0010046 0.0011867 0.3972263 0.3972251 0.0552869 0.0309934 91149
23 154923374 rs111332691 T A 0.0003723 0.0012914 0.7731415 0.7731404 0.0448387 0.0116556 91149
23 154925045 rs509981 C T 0.0004759 0.0006224 0.4444358 0.4444331 0.2444670 0.3634440 91149
23 154925895 rs538470 C T 0.0007011 0.0006363 0.2705061 0.2705034 0.2409490 0.3634440 91149
23 154927581 rs644138 G A 0.0006898 0.0005854 0.2386629 0.2386600 0.3001640 0.4635760 91149
23 154929412 rs557132 C T 0.0004958 0.0006226 0.4257945 0.4257914 0.2443160 0.3568210 91149
23 154929637 rs35185538 CT C 0.0006515 0.0006500 0.3161972 0.3161951 0.2286640 0.3011920 91149
23 154929952 rs4012982 CAA C 0.0003776 0.0006552 0.5644715 0.5644692 0.2382530 0.3165560 91149
23 154930230 rs781880 A G 0.0005868 0.0006223 0.3457244 0.3457215 0.2447660 0.3618540 91149
23 154930487 rs781879 T A -0.0012779 0.0021107 0.5448915 0.5448911 0.0196632 0.1263580 91149

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111487 ES:SE:LP:AF:SS:ID   0.00140868:0.00112793:0.674275:0.111487:91149:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116459 ES:SE:LP:AF:SS:ID   0.000236282:0.00106828:0.0835713:0.116459:91149:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0978765    ES:SE:LP:AF:SS:ID   -6.35314e-05:0.00120049:0.0187274:0.0978765:91149:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157837    ES:SE:LP:AF:SS:ID   0.00468738:0.00286168:0.993838:0.0157837:91149:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569973    ES:SE:LP:AF:SS:ID   0.000492158:0.0014807:0.131002:0.0569973:91149:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122359 ES:SE:LP:AF:SS:ID   0.000100947:0.00101373:0.0358922:0.122359:91149:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122047 ES:SE:LP:AF:SS:ID   -7.07476e-05:0.00108087:0.0232778:0.122047:91149:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121588 ES:SE:LP:AF:SS:ID   0.000126954:0.0010145:0.0455582:0.121588:91149:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868917 ES:SE:LP:AF:SS:ID   -0.000179844:0.000997926:0.0670283:0.868917:91149:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123699 ES:SE:LP:AF:SS:ID   0.000175866:0.000989368:0.0660498:0.123699:91149:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143202 ES:SE:LP:AF:SS:ID   0.000635285:0.000979481:0.286844:0.143202:91149:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123834 ES:SE:LP:AF:SS:ID   0.000164478:0.000987937:0.0615934:0.123834:91149:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869892 ES:SE:LP:AF:SS:ID   -2.7257e-05:0.000962649:0.00992278:0.869892:91149:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874553 ES:SE:LP:AF:SS:ID   -0.000172335:0.000978261:0.0654182:0.874553:91149:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129529 ES:SE:LP:AF:SS:ID   6.21515e-05:0.00096567:0.0228789:0.129529:91149:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358205    ES:SE:LP:AF:SS:ID   0.00101535:0.00176417:0.248008:0.0358205:91149:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869539 ES:SE:LP:AF:SS:ID   -1.13678e-06:0.000961845:0.000409733:0.869539:91149:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869616 ES:SE:LP:AF:SS:ID   -1.0604e-05:0.000962265:0.0038352:0.869616:91149:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869535 ES:SE:LP:AF:SS:ID   -1.63208e-06:0.000961805:0.000588433:0.869535:91149:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.86952  ES:SE:LP:AF:SS:ID   -6.71234e-05:0.000959823:0.0249144:0.86952:91149:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126911 ES:SE:LP:AF:SS:ID   0.000189162:0.000979811:0.0721617:0.126911:91149:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86905  ES:SE:LP:AF:SS:ID   -8.51084e-05:0.000957338:0.031909:0.86905:91149:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868436 ES:SE:LP:AF:SS:ID   -0.00011911:0.000956732:0.0453128:0.868436:91149:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869199 ES:SE:LP:AF:SS:ID   -9.28521e-05:0.000958206:0.0348905:0.869199:91149:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869205 ES:SE:LP:AF:SS:ID   -9.32684e-05:0.000958268:0.0350506:0.869205:91149:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869207 ES:SE:LP:AF:SS:ID   -9.34535e-05:0.000958277:0.0351221:0.869207:91149:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869687 ES:SE:LP:AF:SS:ID   -4.76358e-05:0.000960841:0.0175212:0.869687:91149:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991787    ES:SE:LP:AF:SS:ID   0.000258736:0.00111818:0.087771:0.0991787:91149:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873682 ES:SE:LP:AF:SS:ID   -0.00019342:0.000975071:0.0742966:0.873682:91149:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863058 ES:SE:LP:AF:SS:ID   -3.73417e-05:0.000956466:0.0137399:0.863058:91149:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868472 ES:SE:LP:AF:SS:ID   -4.64877e-05:0.000965956:0.0169983:0.868472:91149:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865369 ES:SE:LP:AF:SS:ID   -5.04412e-07:0.000966138:0.000181139:0.865369:91149:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0995228    ES:SE:LP:AF:SS:ID   0.000284418:0.00115628:0.0938261:0.0995228:91149:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870657 ES:SE:LP:AF:SS:ID   -0.000164903:0.000977143:0.0624891:0.870657:91149:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870657 ES:SE:LP:AF:SS:ID   -0.000164899:0.000977143:0.0624876:0.870657:91149:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870654 ES:SE:LP:AF:SS:ID   -0.000165379:0.000977146:0.0626813:0.870654:91149:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871019 ES:SE:LP:AF:SS:ID   -0.000195963:0.0009776:0.0751384:0.871019:91149:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126515 ES:SE:LP:AF:SS:ID   0.000244285:0.000978687:0.0953423:0.126515:91149:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106037 ES:SE:LP:AF:SS:ID   -0.000407169:0.00106384:0.153714:0.106037:91149:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85438  ES:SE:LP:AF:SS:ID   -1.96281e-06:0.000956101:0.000711958:0.85438:91149:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839153 ES:SE:LP:AF:SS:ID   0.000518701:0.000944668:0.234369:0.839153:91149:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763195 ES:SE:LP:AF:SS:ID   -1.99628e-05:0.000759564:0.00920267:0.763195:91149:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105092 ES:SE:LP:AF:SS:ID   -0.000117242:0.00104669:0.0405703:0.105092:91149:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00772317   ES:SE:LP:AF:SS:ID   -0.00115199:0.00387833:0.11552:0.00772317:91149:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129904 ES:SE:LP:AF:SS:ID   0.000157122:0.000965018:0.0601504:0.129904:91149:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129636 ES:SE:LP:AF:SS:ID   0.000198451:0.000963748:0.0773487:0.129636:91149:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104365 ES:SE:LP:AF:SS:ID   -5.38715e-05:0.00105481:0.01806:0.104365:91149:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00906976   ES:SE:LP:AF:SS:ID   -0.00381917:0.00370847:0.51844:0.00906976:91149:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00773917   ES:SE:LP:AF:SS:ID   -0.0010776:0.00389451:0.106785:0.00773917:91149:rs112563271
1   770886  rs371458725 G   A   .   PASS    AF=0.103379 ES:SE:LP:AF:SS:ID   -8.23662e-05:0.00106393:0.027662:0.103379:91149:rs371458725