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-20527/ukb-d-20527.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-20527/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 17:09:14 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20527/ukb-d-20527.vcf.gz ...
Read summary statistics for 11654768 SNPs.
Dropped 9984 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, 1282767 SNPs remain.
After merging with regression SNP LD, 1282767 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0147 (0.004)
Lambda GC: 1.0235
Mean Chi^2: 1.0297
Intercept: 0.9961 (0.0063)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:10:57 2019
Total time elapsed: 1.0m:42.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.948,
    "inflation_factor": 1.0256,
    "mean_EFFECT": 1.413e-07,
    "n": 117954,
    "n_snps": 11654768,
    "n_clumped_hits": 0,
    "n_p_sig": 4,
    "n_mono": 0,
    "n_ns": 1168920,
    "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": 253894,
    "n_est": 118188.2032,
    "ratio_se_n": 1.001,
    "mean_diff": -6.9786e-07,
    "ratio_diff": 0.5209,
    "sd_y_est1": 0.1802,
    "sd_y_est2": 0.1804,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282767,
    "ldsc_nsnp_merge_regression_ld": 1282767,
    "ldsc_observed_scale_h2_beta": 0.0147,
    "ldsc_observed_scale_h2_se": 0.004,
    "ldsc_intercept_beta": 0.9961,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0235,
    "ldsc_mean_chisq": 1.0297,
    "ldsc_ratio": -0.1313
}

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 11645394 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 52606 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31854 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.072512e+00 6.184567e+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 7.886420e+07 5.599170e+07 3.02000e+02 3.265977e+07 6.988064e+07 1.147345e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.000000e-07 2.680500e-03 -2.64458e-02 -9.813000e-04 -6.900000e-06 9.564000e-04 3.533280e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.093800e-03 1.658700e-03 6.15000e-04 8.465000e-04 1.304900e-03 2.859600e-03 9.658700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.959481e-01 2.894981e-01 0.00000e+00 2.447102e-01 4.945725e-01 7.464711e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.959468e-01 2.894989e-01 0.00000e+00 2.447076e-01 4.945711e-01 7.464703e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.207074e-01 2.603260e-01 3.11720e-03 1.802130e-02 1.010365e-01 3.520480e-01 9.968830e-01 ▇▂▁▁▁
numeric AF_reference 253894 0.9782154 NA NA NA NA NA 2.215693e-01 2.516537e-01 0.00000e+00 1.497600e-02 1.198080e-01 3.526360e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.179540e+05 0.000000e+00 1.17954e+05 1.179540e+05 1.179540e+05 1.179540e+05 1.179540e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0012372 0.0012934 0.3388192 0.3388182 0.1116860 0.1894970 117954
1 693731 rs12238997 A G 0.0010024 0.0012249 0.4131569 0.4131559 0.1166930 0.1417730 117954
1 707522 rs371890604 G C 0.0008669 0.0013744 0.5281837 0.5281835 0.0983327 0.1293930 117954
1 717587 rs144155419 G A -0.0002265 0.0032946 0.9451850 0.9451842 0.0157487 0.0045926 117954
1 730087 rs148120343 T C 0.0021958 0.0017044 0.1976310 0.1976293 0.0569043 0.0127796 117954
1 731718 rs142557973 T C 0.0012135 0.0011622 0.2964197 0.2964201 0.1226220 0.1543530 117954
1 732032 rs61770163 A C 0.0009355 0.0012387 0.4501228 0.4501204 0.1222250 0.1555510 117954
1 734349 rs141242758 T C 0.0011488 0.0011628 0.3231752 0.3231722 0.1218780 0.1525560 117954
1 740284 rs61770167 C T 0.0011589 0.0053108 0.8272670 0.8272666 0.0058535 0.0023962 117954
1 749963 rs529266287 T TAA -0.0003925 0.0011458 0.7319493 0.7319493 0.8690470 0.7641770 117954
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0035293 0.0013671 0.0098351 0.0098338 0.0554451 0.0309934 117954
23 154923374 rs111332691 T A 0.0000631 0.0014892 0.9661759 0.9661764 0.0447971 0.0116556 117954
23 154925045 rs509981 C T -0.0014287 0.0007173 0.0463767 0.0463750 0.2447330 0.3634440 117954
23 154925895 rs538470 C T -0.0013408 0.0007334 0.0675305 0.0675282 0.2411620 0.3634440 117954
23 154927581 rs644138 G A -0.0003402 0.0006749 0.6141847 0.6141825 0.3005390 0.4635760 117954
23 154929412 rs557132 C T -0.0014478 0.0007174 0.0435983 0.0435956 0.2446080 0.3568210 117954
23 154929637 rs35185538 CT C -0.0014130 0.0007495 0.0593827 0.0593813 0.2288490 0.3011920 117954
23 154929952 rs4012982 CAA C -0.0013002 0.0007551 0.0850687 0.0850672 0.2386950 0.3165560 117954
23 154930230 rs781880 A G -0.0014415 0.0007172 0.0444529 0.0444504 0.2450310 0.3618540 117954
23 154930487 rs781879 T A -0.0054082 0.0024380 0.0265332 0.0265309 0.0196820 0.1263580 117954

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111686 ES:SE:LP:AF:SS:ID   0.00123716:0.00129342:0.470032:0.111686:117954:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116693 ES:SE:LP:AF:SS:ID   0.0010024:0.0012249:0.383885:0.116693:117954:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983327    ES:SE:LP:AF:SS:ID   0.000866927:0.00137437:0.277215:0.0983327:117954:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157487    ES:SE:LP:AF:SS:ID   -0.000226524:0.00329463:0.0244832:0.0157487:117954:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569043    ES:SE:LP:AF:SS:ID   0.0021958:0.00170437:0.704145:0.0569043:117954:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122622 ES:SE:LP:AF:SS:ID   0.00121348:0.00116218:0.528093:0.122622:117954:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122225 ES:SE:LP:AF:SS:ID   0.000935499:0.00123872:0.346669:0.122225:117954:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121878 ES:SE:LP:AF:SS:ID   0.00114879:0.00116279:0.490562:0.121878:117954:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00585349   ES:SE:LP:AF:SS:ID   0.00115886:0.00531079:0.0823543:0.00585349:117954:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.869047 ES:SE:LP:AF:SS:ID   -0.000392458:0.00114575:0.135519:0.869047:117954:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123657 ES:SE:LP:AF:SS:ID   0.000449212:0.0011352:0.159694:0.123657:117954:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143285 ES:SE:LP:AF:SS:ID   0.000500738:0.00112275:0.183359:0.143285:117954:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123778 ES:SE:LP:AF:SS:ID   0.000406399:0.00113363:0.142683:0.123778:117954:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869805 ES:SE:LP:AF:SS:ID   -0.000544368:0.00110395:0.206254:0.869805:117954:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874595 ES:SE:LP:AF:SS:ID   -0.000250166:0.00112255:0.0842584:0.874595:117954:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129653 ES:SE:LP:AF:SS:ID   0.000530813:0.00110704:0.199563:0.129653:117954:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365609    ES:SE:LP:AF:SS:ID   0.00252405:0.00200947:0.679665:0.0365609:117954:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869399 ES:SE:LP:AF:SS:ID   -0.000521689:0.0011029:0.196405:0.869399:117954:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86947  ES:SE:LP:AF:SS:ID   -0.000434762:0.00110331:0.158927:0.86947:117954:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869398 ES:SE:LP:AF:SS:ID   -0.000523417:0.00110287:0.197174:0.869398:117954:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00511758   ES:SE:LP:AF:SS:ID   -0.00956473:0.00564109:1.04588:0.00511758:117954:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00508671   ES:SE:LP:AF:SS:ID   -0.00951749:0.00565348:1.03487:0.00508671:117954:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00568173   ES:SE:LP:AF:SS:ID   -0.00145729:0.00543876:0.103065:0.00568173:117954:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869471 ES:SE:LP:AF:SS:ID   -0.000619612:0.00110083:0.241442:0.869471:117954:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126927 ES:SE:LP:AF:SS:ID   0.000490716:0.00112375:0.178914:0.126927:117954:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868991 ES:SE:LP:AF:SS:ID   -0.00067195:0.00109794:0.267179:0.868991:117954:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868392 ES:SE:LP:AF:SS:ID   -0.000492785:0.00109752:0.184798:0.868392:117954:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869181 ES:SE:LP:AF:SS:ID   -0.000642052:0.00109903:0.25252:0.869181:117954:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869188 ES:SE:LP:AF:SS:ID   -0.000642643:0.00109911:0.252779:0.869188:117954:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86919  ES:SE:LP:AF:SS:ID   -0.000644944:0.00109911:0.253873:0.86919:117954:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869626 ES:SE:LP:AF:SS:ID   -0.000643092:0.00110193:0.252208:0.869626:117954:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0995542    ES:SE:LP:AF:SS:ID   0.00101758:0.00128107:0.369562:0.0995542:117954:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00654177   ES:SE:LP:AF:SS:ID   1.1506e-05:0.00493697:0.00080854:0.00654177:117954:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873696 ES:SE:LP:AF:SS:ID   -0.000358806:0.00111888:0.125836:0.873696:117954:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862972 ES:SE:LP:AF:SS:ID   -0.000662442:0.00109724:0.262791:0.862972:117954:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868374 ES:SE:LP:AF:SS:ID   -0.000517006:0.00110782:0.193328:0.868374:117954:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865388 ES:SE:LP:AF:SS:ID   -0.000601038:0.00110799:0.230989:0.865388:117954:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997307    ES:SE:LP:AF:SS:ID   -0.00020945:0.00132397:0.058339:0.0997307:117954:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87069  ES:SE:LP:AF:SS:ID   -0.000503149:0.00112111:0.184701:0.87069:117954:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87069  ES:SE:LP:AF:SS:ID   -0.000503123:0.00112111:0.18469:0.87069:117954:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870688 ES:SE:LP:AF:SS:ID   -0.000504297:0.00112111:0.185191:0.870688:117954:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87101  ES:SE:LP:AF:SS:ID   -0.000531258:0.00112159:0.196721:0.87101:117954:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126515 ES:SE:LP:AF:SS:ID   0.000504214:0.00112254:0.184883:0.126515:117954:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106315 ES:SE:LP:AF:SS:ID   0.0013718:0.00121985:0.583729:0.106315:117954:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854429 ES:SE:LP:AF:SS:ID   -0.000917854:0.00109702:0.394939:0.854429:117954:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839121 ES:SE:LP:AF:SS:ID   0.000282963:0.00108684:0.0998564:0.839121:117954:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763055 ES:SE:LP:AF:SS:ID   -0.000355081:0.000871103:0.165228:0.763055:117954:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105253 ES:SE:LP:AF:SS:ID   7.68842e-05:0.00120501:0.0226757:0.105253:117954:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00773846   ES:SE:LP:AF:SS:ID   0.000461693:0.00444908:0.0374649:0.00773846:117954:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129933 ES:SE:LP:AF:SS:ID   0.000470836:0.00110648:0.173631:0.129933:117954:rs762168062