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-5843_2/ukb-d-5843_2.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-5843_2/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 16:51:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5843_2/ukb-d-5843_2.vcf.gz ...
Read summary statistics for 9997323 SNPs.
Dropped 7714 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, 1278100 SNPs remain.
After merging with regression SNP LD, 1278100 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.005 (0.0158)
Lambda GC: 1.0009
Mean Chi^2: 1.0083
Intercept: 1.0112 (0.0064)
Ratio: 1.3491 (0.7668)
Analysis finished at Mon Nov 25 16:52:45 2019
Total time elapsed: 1.0m:39.64s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9416,
    "inflation_factor": 1.002,
    "mean_EFFECT": -6.7154e-06,
    "n": 29317,
    "n_snps": 9997323,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1082605,
    "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": 197610,
    "n_est": 29364.6396,
    "ratio_se_n": 1.0008,
    "mean_diff": -0,
    "ratio_diff": 390.7966,
    "sd_y_est1": 0.2226,
    "sd_y_est2": 0.2228,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1278100,
    "ldsc_nsnp_merge_regression_ld": 1278100,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0112,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0009,
    "ldsc_mean_chisq": 1.0083,
    "ldsc_ratio": 1.3494
}

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 TRUE
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 9990159 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 48173 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30130 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079674e+00 6.177239e+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 7.875763e+07 5.609018e+07 3.02000e+02 3.247474e+07 6.965878e+07 1.147415e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -6.700000e-06 4.446200e-03 -3.94803e-02 -2.068900e-03 -2.650000e-05 2.014300e-03 5.127340e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.790400e-03 2.301700e-03 1.50840e-03 2.024700e-03 2.755400e-03 4.904200e-03 1.322890e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.991890e-01 2.894219e-01 0.00000e+00 2.480310e-01 4.995707e-01 7.500203e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.991836e-01 2.894252e-01 0.00000e+00 2.480217e-01 4.995650e-01 7.500184e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.546310e-01 2.629496e-01 8.19140e-03 3.852270e-02 1.494370e-01 4.061650e-01 9.918090e-01 ▇▂▂▁▁
numeric AF_reference 197610 0.9802337 NA NA NA NA NA 2.542796e-01 2.537973e-01 0.00000e+00 4.293130e-02 1.653350e-01 4.023560e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.931700e+04 0.000000e+00 2.93170e+04 2.931700e+04 2.931700e+04 2.931700e+04 2.931700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0002201 0.0032207 0.9455261 0.9455258 0.1122900 0.1894970 29317
1 693731 rs12238997 A G 0.0005752 0.0030374 0.8498160 0.8498147 0.1171770 0.1417730 29317
1 707522 rs371890604 G C 0.0023083 0.0034295 0.5008942 0.5008892 0.0977152 0.1293930 29317
1 717587 rs144155419 G A -0.0068902 0.0080521 0.3921697 0.3921636 0.0161831 0.0045926 29317
1 730087 rs148120343 T C -0.0030375 0.0042596 0.4757886 0.4757836 0.0568591 0.0127796 29317
1 731718 rs142557973 T C -0.0004146 0.0028853 0.8857470 0.8857464 0.1232340 0.1543530 29317
1 732032 rs61770163 A C 0.0013019 0.0030805 0.6725723 0.6725690 0.1222040 0.1555510 29317
1 734349 rs141242758 T C -0.0004496 0.0028870 0.8762441 0.8762430 0.1224360 0.1525560 29317
1 749963 rs529266287 T TAA -0.0001806 0.0028477 0.9494371 0.9494364 0.8685340 0.7641770 29317
1 751343 rs28544273 T A -0.0006975 0.0028242 0.8049311 0.8049290 0.1240620 0.2426120 29317
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0006165 0.0033418 0.8536489 0.8536473 0.0555757 0.0309934 29317
23 154923374 rs111332691 T A 0.0037262 0.0036574 0.3082968 0.3082888 0.0446158 0.0116556 29317
23 154925045 rs509981 C T -0.0006742 0.0017717 0.7035549 0.7035515 0.2413810 0.3634440 29317
23 154925895 rs538470 C T -0.0010842 0.0018105 0.5492651 0.5492633 0.2380390 0.3634440 29317
23 154927581 rs644138 G A -0.0003644 0.0016645 0.8267279 0.8267263 0.2974820 0.4635760 29317
23 154929412 rs557132 C T -0.0006950 0.0017723 0.6949443 0.6949412 0.2412050 0.3568210 29317
23 154929637 rs35185538 CT C -0.0001755 0.0018492 0.9243750 0.9243745 0.2254660 0.3011920 29317
23 154929952 rs4012982 CAA C -0.0008853 0.0018643 0.6348571 0.6348541 0.2349990 0.3165560 29317
23 154930230 rs781880 A G -0.0008211 0.0017719 0.6430637 0.6430601 0.2415880 0.3618540 29317
23 154930487 rs781879 T A -0.0051585 0.0060343 0.3926359 0.3926287 0.0190625 0.1263580 29317

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11229  ES:SE:LP:AF:SS:ID   -0.000220056:0.00322066:0.0243265:0.11229:29317:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117177 ES:SE:LP:AF:SS:ID   0.000575154:0.00303744:0.0706751:0.117177:29317:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977152    ES:SE:LP:AF:SS:ID   0.00230834:0.00342946:0.300254:0.0977152:29317:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0161831    ES:SE:LP:AF:SS:ID   -0.00689021:0.00805213:0.406526:0.0161831:29317:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0568591    ES:SE:LP:AF:SS:ID   -0.00303753:0.00425961:0.322586:0.0568591:29317:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123234 ES:SE:LP:AF:SS:ID   -0.000414579:0.00288526:0.0526903:0.123234:29317:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122204 ES:SE:LP:AF:SS:ID   0.0013019:0.00308051:0.172261:0.122204:29317:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122436 ES:SE:LP:AF:SS:ID   -0.000449609:0.00288704:0.0573749:0.122436:29317:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868534 ES:SE:LP:AF:SS:ID   -0.000180585:0.00284769:0.0225338:0.868534:29317:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.124062 ES:SE:LP:AF:SS:ID   -0.000697494:0.00282417:0.0942413:0.124062:29317:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143368 ES:SE:LP:AF:SS:ID   7.75787e-05:0.00279847:0.00971266:0.143368:29317:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124208 ES:SE:LP:AF:SS:ID   -0.000674286:0.00281967:0.0909781:0.124208:29317:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869483 ES:SE:LP:AF:SS:ID   0.000617316:0.00274485:0.085097:0.869483:29317:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874513 ES:SE:LP:AF:SS:ID   0.000851228:0.00279167:0.11894:0.874513:29317:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129978 ES:SE:LP:AF:SS:ID   -0.000518298:0.00275114:0.0702904:0.129978:29317:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363782    ES:SE:LP:AF:SS:ID   -0.00102459:0.00499011:0.0771085:0.0363782:29317:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869204 ES:SE:LP:AF:SS:ID   0.000369297:0.00274293:0.0491967:0.869204:29317:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869328 ES:SE:LP:AF:SS:ID   0.000314099:0.00274464:0.0414892:0.869328:29317:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869171 ES:SE:LP:AF:SS:ID   0.000378061:0.00274262:0.0504329:0.869171:29317:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869276 ES:SE:LP:AF:SS:ID   0.000480065:0.0027386:0.065073:0.869276:29317:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127187 ES:SE:LP:AF:SS:ID   -0.000243354:0.00279407:0.0312393:0.127187:29317:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868864 ES:SE:LP:AF:SS:ID   0.000321543:0.00273287:0.0427089:0.868864:29317:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86813  ES:SE:LP:AF:SS:ID   0.000147993:0.00273039:0.0191906:0.86813:29317:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869004 ES:SE:LP:AF:SS:ID   0.000483396:0.00273464:0.0656571:0.869004:29317:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86901  ES:SE:LP:AF:SS:ID   0.000480584:0.00273484:0.0652441:0.86901:29317:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869017 ES:SE:LP:AF:SS:ID   0.000479778:0.00273492:0.065125:0.869017:29317:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86944  ES:SE:LP:AF:SS:ID   0.00041079:0.00274132:0.0550818:0.86944:29317:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.099544 ES:SE:LP:AF:SS:ID   0.00163276:0.00318636:0.215839:0.099544:29317:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873595 ES:SE:LP:AF:SS:ID   0.000566112:0.00278316:0.0763317:0.873595:29317:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86293  ES:SE:LP:AF:SS:ID   0.000486247:0.00273261:0.0661231:0.86293:29317:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868409 ES:SE:LP:AF:SS:ID   0.000595651:0.00275887:0.0814119:0.868409:29317:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865238 ES:SE:LP:AF:SS:ID   -1.27299e-05:0.00275704:0.0016029:0.865238:29317:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0991348    ES:SE:LP:AF:SS:ID   4.74543e-05:0.00329843:0.0050141:0.0991348:29317:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   0.000157785:0.00278674:0.0200658:0.87041:29317:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   0.000157746:0.00278674:0.0200603:0.87041:29317:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870408 ES:SE:LP:AF:SS:ID   0.000156432:0.00278675:0.0198898:0.870408:29317:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870781 ES:SE:LP:AF:SS:ID   0.000176536:0.00278997:0.0224831:0.870781:29317:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126677 ES:SE:LP:AF:SS:ID   -0.000583349:0.00279125:0.0785966:0.126677:29317:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106304 ES:SE:LP:AF:SS:ID   0.000276364:0.0030354:0.0327067:0.106304:29317:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854014 ES:SE:LP:AF:SS:ID   0.000699088:0.00273354:0.0979155:0.854014:29317:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838154 ES:SE:LP:AF:SS:ID   -0.00171968:0.00268324:0.282667:0.838154:29317:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762666 ES:SE:LP:AF:SS:ID   -0.00112809:0.00215926:0.220861:0.762666:29317:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105297 ES:SE:LP:AF:SS:ID   0.00233998:0.00296979:0.365781:0.105297:29317:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.130002 ES:SE:LP:AF:SS:ID   -0.000172069:0.0027541:0.0221927:0.130002:29317:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129764 ES:SE:LP:AF:SS:ID   -0.000464215:0.00275023:0.0625012:0.129764:29317:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104434 ES:SE:LP:AF:SS:ID   0.00234839:0.00299563:0.363429:0.104434:29317:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00929756   ES:SE:LP:AF:SS:ID   0.00969197:0.0105237:0.447239:0.00929756:29317:rs146076599
1   770886  rs371458725 G   A   .   PASS    AF=0.103397 ES:SE:LP:AF:SS:ID   0.00264842:0.00302176:0.419311:0.103397:29317:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.828456 ES:SE:LP:AF:SS:ID   -0.00041082:0.00269014:0.0561959:0.828456:29317:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.869    ES:SE:LP:AF:SS:ID   0.000407063:0.00273922:0.0545974:0.869:29317:rs2977605