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-2247_0/ukb-d-2247_0.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-2247_0/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 16:54:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-2247_0/ukb-d-2247_0.vcf.gz ...
Read summary statistics for 13586288 SNPs.
Dropped 12710 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0402 (0.0022)
Lambda GC: 1.2392
Mean Chi^2: 1.2984
Intercept: 1.0197 (0.0082)
Ratio: 0.0659 (0.0276)
Analysis finished at Mon Nov 25 16:56:44 2019
Total time elapsed: 2.0m:21.77s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1502,
    "mean_EFFECT": -0,
    "n": 346635,
    "n_snps": 13586288,
    "n_clumped_hits": 30,
    "n_p_sig": 1493,
    "n_mono": 0,
    "n_ns": 1251798,
    "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": 569177,
    "n_est": 347981.6966,
    "ratio_se_n": 1.0019,
    "mean_diff": -0,
    "ratio_diff": 17.338,
    "sd_y_est1": 0.4333,
    "sd_y_est2": 0.4341,
    "r2_sum1": 0.0007,
    "r2_sum2": 0.0039,
    "r2_sum3": 0.0038,
    "r2_sum4": 0.0038,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0402,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0197,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.2392,
    "ldsc_mean_chisq": 1.2984,
    "ldsc_ratio": 0.066
}

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 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 13574242 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57084 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33338 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051299e+00 6.184958e+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 7.902494e+07 5.591464e+07 3.02000e+02 3.293107e+07 7.013818e+07 1.148586e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.670000e-05 6.178400e-03 -1.79664e-01 -1.765000e-03 3.400000e-06 1.756100e-03 7.831060e-02 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.373300e-03 4.218700e-03 8.55000e-04 1.245100e-03 2.294400e-03 6.284800e-03 2.128160e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.768253e-01 2.951184e-01 0.00000e+00 2.157282e-01 4.694431e-01 7.324163e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.768248e-01 2.951187e-01 0.00000e+00 2.157273e-01 4.694428e-01 7.324164e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908052e-01 2.544026e-01 1.00000e-03 7.429300e-03 6.003580e-02 2.953050e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569177 0.9581065 NA NA NA NA NA 1.963353e-01 2.471010e-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 3.466350e+05 0.000000e+00 3.46635e+05 3.466350e+05 3.466350e+05 3.466350e+05 3.466350e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0007729 0.0018222 0.6714381 0.6714368 0.1106800 0.1894970 346635
1 693731 rs12238997 A G -0.0025470 0.0017214 0.1389860 0.1389843 0.1158360 0.1417730 346635
1 707522 rs371890604 G C -0.0014751 0.0019353 0.4459621 0.4459610 0.0973429 0.1293930 346635
1 717587 rs144155419 G A -0.0040976 0.0046222 0.3753384 0.3753384 0.0156654 0.0045926 346635
1 723329 rs189787166 A T 0.0151039 0.0136598 0.2688469 0.2688482 0.0017290 0.0003994 346635
1 730087 rs148120343 T C -0.0034765 0.0024005 0.1475479 0.1475476 0.0563902 0.0127796 346635
1 731718 rs142557973 T C -0.0029818 0.0016327 0.0678032 0.0678025 0.1217310 0.1543530 346635
1 732032 rs61770163 A C -0.0023146 0.0017414 0.1838002 0.1837994 0.1211720 0.1555510 346635
1 734349 rs141242758 T C -0.0028711 0.0016336 0.0788261 0.0788263 0.1209650 0.1525560 346635
1 740284 rs61770167 C T 0.0169745 0.0074579 0.0228434 0.0228429 0.0058136 0.0023962 346635
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0025991 0.0018849 0.1679349 0.1679348 0.0561546 0.0309934 346635
23 154923374 rs111332691 T A -0.0042548 0.0020710 0.0399356 0.0399344 0.0448123 0.0116556 346635
23 154925045 rs509981 C T 0.0024947 0.0009968 0.0123282 0.0123280 0.2455770 0.3634440 346635
23 154925895 rs538470 C T 0.0024838 0.0010197 0.0148576 0.0148575 0.2418800 0.3634440 346635
23 154927581 rs644138 G A 0.0027714 0.0009375 0.0031145 0.0031143 0.3021150 0.4635760 346635
23 154929412 rs557132 C T 0.0024571 0.0009971 0.0137331 0.0137324 0.2454300 0.3568210 346635
23 154929637 rs35185538 CT C 0.0012709 0.0010404 0.2219070 0.2219059 0.2297560 0.3011920 346635
23 154929952 rs4012982 CAA C 0.0029905 0.0010487 0.0043491 0.0043487 0.2393900 0.3165560 346635
23 154930230 rs781880 A G 0.0025703 0.0009969 0.0099312 0.0099309 0.2458500 0.3618540 346635
23 154930487 rs781879 T A 0.0048494 0.0034167 0.1558120 0.1558106 0.0195810 0.1263580 346635

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11068  ES:SE:LP:AF:SS:ID   -0.000772914:0.00182215:0.172994:0.11068:346635:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115836 ES:SE:LP:AF:SS:ID   -0.002547:0.00172143:0.857029:0.115836:346635:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973429    ES:SE:LP:AF:SS:ID   -0.00147505:0.00193534:0.350702:0.0973429:346635:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156654    ES:SE:LP:AF:SS:ID   -0.00409762:0.00462215:0.425577:0.0156654:346635:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00172895   ES:SE:LP:AF:SS:ID   0.0151039:0.0136598:0.570495:0.00172895:346635:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0563902    ES:SE:LP:AF:SS:ID   -0.00347652:0.0024005:0.831067:0.0563902:346635:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121731 ES:SE:LP:AF:SS:ID   -0.00298181:0.00163269:1.16875:0.121731:346635:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121172 ES:SE:LP:AF:SS:ID   -0.00231463:0.00174144:0.735654:0.121172:346635:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120965 ES:SE:LP:AF:SS:ID   -0.00287106:0.00163357:1.10333:0.120965:346635:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00581358   ES:SE:LP:AF:SS:ID   0.0169745:0.00745787:1.64124:0.00581358:346635:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188056   ES:SE:LP:AF:SS:ID   -0.000915075:0.0141159:0.0230483:0.00188056:346635:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869754 ES:SE:LP:AF:SS:ID   0.00233992:0.00161048:0.834919:0.869754:346635:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00151388   ES:SE:LP:AF:SS:ID   0.00429844:0.0146676:0.113803:0.00151388:346635:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122913 ES:SE:LP:AF:SS:ID   -0.00231506:0.00159496:0.833727:0.122913:346635:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142717 ES:SE:LP:AF:SS:ID   -0.00273421:0.0015762:1.08198:0.142717:346635:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123029 ES:SE:LP:AF:SS:ID   -0.00225945:0.00159274:0.806823:0.123029:346635:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870925 ES:SE:LP:AF:SS:ID   0.00229532:0.00155227:0.856286:0.870925:346635:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875487 ES:SE:LP:AF:SS:ID   0.00219782:0.00157786:0.786087:0.875487:346635:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128605 ES:SE:LP:AF:SS:ID   -0.00223541:0.00155609:0.821463:0.128605:346635:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363913    ES:SE:LP:AF:SS:ID   0.00425631:0.00282285:0.880728:0.0363913:346635:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870519 ES:SE:LP:AF:SS:ID   0.00214906:0.00155064:0.780484:0.870519:346635:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870625 ES:SE:LP:AF:SS:ID   0.00219906:0.00155137:0.805935:0.870625:346635:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870516 ES:SE:LP:AF:SS:ID   0.00211842:0.00155059:0.764782:0.870516:346635:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504155   ES:SE:LP:AF:SS:ID   0.00194169:0.00796008:0.092972:0.00504155:346635:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500847   ES:SE:LP:AF:SS:ID   0.00204692:0.00798114:0.0982214:0.00500847:346635:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558534   ES:SE:LP:AF:SS:ID   0.00781353:0.0077107:0.507378:0.00558534:346635:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870607 ES:SE:LP:AF:SS:ID   0.00226783:0.00154791:0.84498:0.870607:346635:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125953 ES:SE:LP:AF:SS:ID   -0.00204884:0.00157929:0.711029:0.125953:346635:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87017  ES:SE:LP:AF:SS:ID   0.00227456:0.00154418:0.851536:0.87017:346635:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869449 ES:SE:LP:AF:SS:ID   0.0019916:0.00154278:0.706123:0.869449:346635:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870321 ES:SE:LP:AF:SS:ID   0.00223205:0.00154551:0.82775:0.870321:346635:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870326 ES:SE:LP:AF:SS:ID   0.00223454:0.00154562:0.828991:0.870326:346635:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870335 ES:SE:LP:AF:SS:ID   0.0022347:0.00154567:0.829038:0.870335:346635:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870782 ES:SE:LP:AF:SS:ID   0.00226387:0.0015496:0.841538:0.870782:346635:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988654    ES:SE:LP:AF:SS:ID   -0.00137722:0.00180033:0.35234:0.0988654:346635:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647903   ES:SE:LP:AF:SS:ID   0.00269556:0.00696609:0.155653:0.00647903:346635:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874657 ES:SE:LP:AF:SS:ID   0.00199461:0.00157257:0.688961:0.874657:346635:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864054 ES:SE:LP:AF:SS:ID   0.00177226:0.00154231:0.601165:0.864054:346635:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869451 ES:SE:LP:AF:SS:ID   0.00184855:0.00155714:0.62862:0.869451:346635:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866419 ES:SE:LP:AF:SS:ID   0.00180396:0.00155749:0.607716:0.866419:346635:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987524    ES:SE:LP:AF:SS:ID   -0.0021034:0.00186475:0.586149:0.0987524:346635:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871596 ES:SE:LP:AF:SS:ID   0.00189857:0.00157527:0.641848:0.871596:346635:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871596 ES:SE:LP:AF:SS:ID   0.00189846:0.00157527:0.641797:0.871596:346635:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871596 ES:SE:LP:AF:SS:ID   0.00190335:0.0015753:0.64406:0.871596:346635:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871968 ES:SE:LP:AF:SS:ID   0.00199929:0.00157621:0.688984:0.871968:346635:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125542 ES:SE:LP:AF:SS:ID   -0.00198523:0.00157728:0.681605:0.125542:346635:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105439 ES:SE:LP:AF:SS:ID   -0.00198417:0.00171731:0.605671:0.105439:346635:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855424 ES:SE:LP:AF:SS:ID   0.00207735:0.00154164:0.750012:0.855424:346635:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016502    ES:SE:LP:AF:SS:ID   0.0140117:0.0136885:0.514252:0.0016502:346635:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838457 ES:SE:LP:AF:SS:ID   0.000399875:0.00151917:0.101065:0.838457:346635:rs376645387