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-2664_1/ukb-d-2664_1.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-2664_1/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 17:11:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-2664_1/ukb-d-2664_1.vcf.gz ...
Read summary statistics for 13179190 SNPs.
Dropped 12143 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, 1283436 SNPs remain.
After merging with regression SNP LD, 1283436 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0112 (0.0033)
Lambda GC: 1.0359
Mean Chi^2: 1.0363
Intercept: 1.0064 (0.0065)
Ratio: 0.175 (0.1784)
Analysis finished at Mon Nov 25 17:13:35 2019
Total time elapsed: 2.0m:18.56s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9514,
    "inflation_factor": 1.0229,
    "mean_EFFECT": 2.614e-06,
    "n": 134033,
    "n_snps": 13179190,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1236479,
    "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": 470330,
    "n_est": 134750.1032,
    "ratio_se_n": 1.0027,
    "mean_diff": 8.5775e-06,
    "ratio_diff": 8.1502,
    "sd_y_est1": 0.2571,
    "sd_y_est2": 0.2578,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283436,
    "ldsc_nsnp_merge_regression_ld": 1283436,
    "ldsc_observed_scale_h2_beta": 0.0112,
    "ldsc_observed_scale_h2_se": 0.0033,
    "ldsc_intercept_beta": 1.0064,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0359,
    "ldsc_mean_chisq": 1.0363,
    "ldsc_ratio": 0.1763
}

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 13167705 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56241 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33082 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.056909e+00 6.185644e+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 7.898919e+07 5.592610e+07 3.02000e+02 3.287121e+07 7.007849e+07 1.148133e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.600000e-06 5.255200e-03 -5.49483e-02 -1.506400e-03 -8.800000e-06 1.476800e-03 6.930340e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.831300e-03 3.571400e-03 8.00500e-04 1.176400e-03 2.080300e-03 5.458400e-03 1.959860e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.963839e-01 2.899421e-01 1.00000e-07 2.436268e-01 4.951343e-01 7.477062e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.963827e-01 2.899428e-01 1.00000e-07 2.436250e-01 4.951327e-01 7.477056e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.963645e-01 2.557188e-01 1.31410e-03 8.934300e-03 6.713760e-02 3.064330e-01 9.986860e-01 ▇▂▁▁▁
numeric AF_reference 470330 0.9643127 NA NA NA NA NA 2.005587e-01 2.480250e-01 0.00000e+00 6.589500e-03 9.005590e-02 3.160940e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.340330e+05 0.000000e+00 1.34033e+05 1.340330e+05 1.340330e+05 1.340330e+05 1.340330e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0025764 0.0017373 0.1380810 0.1380776 0.1108750 0.1894970 134033
1 693731 rs12238997 A G -0.0002293 0.0016398 0.8887880 0.8887874 0.1162060 0.1417730 134033
1 707522 rs371890604 G C -0.0011589 0.0018472 0.5304030 0.5304013 0.0975793 0.1293930 134033
1 717587 rs144155419 G A -0.0002574 0.0043874 0.9532249 0.9532245 0.0158040 0.0045926 134033
1 723329 rs189787166 A T 0.0040982 0.0133164 0.7582685 0.7582670 0.0016598 0.0003994 134033
1 730087 rs148120343 T C -0.0021810 0.0022939 0.3417079 0.3417060 0.0564609 0.0127796 134033
1 731718 rs142557973 T C -0.0006424 0.0015555 0.6796104 0.6796114 0.1220990 0.1543530 134033
1 732032 rs61770163 A C -0.0010789 0.0016593 0.5155443 0.5155424 0.1216070 0.1555510 134033
1 734349 rs141242758 T C -0.0006335 0.0015561 0.6839416 0.6839408 0.1213600 0.1525560 134033
1 740284 rs61770167 C T -0.0047485 0.0072118 0.5102606 0.5102600 0.0056841 0.0023962 134033
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0001846 0.0017665 0.9167861 0.9167858 0.0562252 0.0309934 134033
23 154923374 rs111332691 T A 0.0016545 0.0019389 0.3934894 0.3934869 0.0445972 0.0116556 134033
23 154925045 rs509981 C T -0.0003719 0.0009318 0.6898315 0.6898314 0.2467450 0.3634440 134033
23 154925895 rs538470 C T -0.0003676 0.0009530 0.6997115 0.6997121 0.2431150 0.3634440 134033
23 154927581 rs644138 G A -0.0002779 0.0008770 0.7513685 0.7513674 0.3034400 0.4635760 134033
23 154929412 rs557132 C T -0.0003651 0.0009321 0.6953044 0.6953046 0.2465880 0.3568210 134033
23 154929637 rs35185538 CT C -0.0004191 0.0009712 0.6660625 0.6660618 0.2305740 0.3011920 134033
23 154929952 rs4012982 CAA C -0.0006833 0.0009795 0.4854338 0.4854333 0.2404630 0.3165560 134033
23 154930230 rs781880 A G -0.0004595 0.0009319 0.6219851 0.6219844 0.2469830 0.3618540 134033
23 154930487 rs781879 T A -0.0018094 0.0031746 0.5687036 0.5687028 0.0199986 0.1263580 134033

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110875 ES:SE:LP:AF:SS:ID   -0.00257638:0.00173729:0.859866:0.110875:134033:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116206 ES:SE:LP:AF:SS:ID   -0.000229309:0.00163981:0.0512018:0.116206:134033:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0975793    ES:SE:LP:AF:SS:ID   -0.00115889:0.00184715:0.275394:0.0975793:134033:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015804 ES:SE:LP:AF:SS:ID   -0.000257354:0.00438736:0.0208046:0.015804:134033:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00165976   ES:SE:LP:AF:SS:ID   0.00409822:0.0133164:0.120177:0.00165976:134033:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564609    ES:SE:LP:AF:SS:ID   -0.00218103:0.00229389:0.466345:0.0564609:134033:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122099 ES:SE:LP:AF:SS:ID   -0.000642403:0.00155548:0.16774:0.122099:134033:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121607 ES:SE:LP:AF:SS:ID   -0.00107893:0.0016593:0.287734:0.121607:134033:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12136  ES:SE:LP:AF:SS:ID   -0.000633471:0.00155609:0.164981:0.12136:134033:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00568407   ES:SE:LP:AF:SS:ID   -0.0047485:0.00721182:0.292208:0.00568407:134033:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00185254   ES:SE:LP:AF:SS:ID   -0.010224:0.0136497:0.343094:0.00185254:134033:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869196 ES:SE:LP:AF:SS:ID   0.00110599:0.0015338:0.327104:0.869196:134033:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153552   ES:SE:LP:AF:SS:ID   0.0277784:0.0139304:1.33588:0.00153552:134033:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123507 ES:SE:LP:AF:SS:ID   -0.000973283:0.001519:0.282584:0.123507:134033:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143367 ES:SE:LP:AF:SS:ID   -0.000878084:0.00150063:0.253014:0.143367:134033:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123629 ES:SE:LP:AF:SS:ID   -0.000999748:0.00151693:0.292551:0.123629:134033:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870443 ES:SE:LP:AF:SS:ID   0.00134604:0.00147922:0.440282:0.870443:134033:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874774 ES:SE:LP:AF:SS:ID   0.00132271:0.00150261:0.421691:0.874774:134033:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129057 ES:SE:LP:AF:SS:ID   -0.00123589:0.00148275:0.39302:0.129057:134033:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036118 ES:SE:LP:AF:SS:ID   0.00241257:0.00270577:0.42877:0.036118:134033:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870069 ES:SE:LP:AF:SS:ID   0.00133429:0.00147781:0.435822:0.870069:134033:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870146 ES:SE:LP:AF:SS:ID   0.00132563:0.00147823:0.431983:0.870146:134033:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870071 ES:SE:LP:AF:SS:ID   0.00136617:0.00147778:0.449478:0.870071:134033:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00508305   ES:SE:LP:AF:SS:ID   -0.00479794:0.00757702:0.278527:0.00508305:134033:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00504745   ES:SE:LP:AF:SS:ID   -0.00469295:0.0075973:0.270215:0.00504745:134033:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00570971   ES:SE:LP:AF:SS:ID   -0.0161632:0.00727811:1.57895:0.00570971:134033:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   0.00132915:0.00147499:0.434717:0.87014:134033:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126479 ES:SE:LP:AF:SS:ID   -0.00108618:0.00150378:0.327801:0.126479:134033:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869704 ES:SE:LP:AF:SS:ID   0.00124885:0.00147138:0.402289:0.869704:134033:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869014 ES:SE:LP:AF:SS:ID   0.00124297:0.0014702:0.400264:0.869014:134033:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86985  ES:SE:LP:AF:SS:ID   0.0012135:0.00147268:0.387283:0.86985:134033:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869853 ES:SE:LP:AF:SS:ID   0.00121337:0.00147279:0.387195:0.869853:134033:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869862 ES:SE:LP:AF:SS:ID   0.00121048:0.00147282:0.386004:0.869862:134033:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870293 ES:SE:LP:AF:SS:ID   0.00141301:0.0014765:0.470354:0.870293:134033:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991946    ES:SE:LP:AF:SS:ID   -0.000848813:0.00171698:0.206873:0.0991946:134033:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00663777   ES:SE:LP:AF:SS:ID   -0.0156638:0.00656097:1.77035:0.00663777:134033:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874064 ES:SE:LP:AF:SS:ID   0.00144993:0.00149785:0.477497:0.874064:134033:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863716 ES:SE:LP:AF:SS:ID   0.00119484:0.00146982:0.380629:0.863716:134033:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868938 ES:SE:LP:AF:SS:ID   0.00117804:0.00148307:0.369563:0.868938:134033:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865877 ES:SE:LP:AF:SS:ID   0.00111388:0.00148414:0.343958:0.865877:134033:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0991097    ES:SE:LP:AF:SS:ID   -0.00175434:0.00177658:0.490247:0.0991097:134033:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871    ES:SE:LP:AF:SS:ID   0.00100262:0.00150032:0.297603:0.871:134033:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871    ES:SE:LP:AF:SS:ID   0.0010025:0.00150032:0.297559:0.871:134033:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871001 ES:SE:LP:AF:SS:ID   0.00100004:0.00150039:0.296641:0.871001:134033:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871387 ES:SE:LP:AF:SS:ID   0.00118281:0.00150134:0.365731:0.871387:134033:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126105 ES:SE:LP:AF:SS:ID   -0.00119064:0.00150191:0.368633:0.126105:134033:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105767 ES:SE:LP:AF:SS:ID   -0.000715409:0.00163705:0.179074:0.105767:134033:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85509  ES:SE:LP:AF:SS:ID   0.00126086:0.00146921:0.408057:0.85509:134033:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00157626   ES:SE:LP:AF:SS:ID   0.00083668:0.0133862:0.0222023:0.00157626:134033:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838236 ES:SE:LP:AF:SS:ID   -0.000199927:0.00145029:0.0504358:0.838236:134033:rs376645387