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-1508_2/ukb-d-1508_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-1508_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 17:07:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1508_2/ukb-d-1508_2.vcf.gz ...
Read summary statistics for 13584119 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: 0.035 (0.0025)
Lambda GC: 1.1971
Mean Chi^2: 1.2092
Intercept: 1.0148 (0.0076)
Ratio: 0.0707 (0.0363)
Analysis finished at Mon Nov 25 17:09:51 2019
Total time elapsed: 2.0m:39.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1227,
    "mean_EFFECT": 0,
    "n": 283449,
    "n_snps": 13584119,
    "n_clumped_hits": 5,
    "n_p_sig": 336,
    "n_mono": 0,
    "n_ns": 1251740,
    "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": 568397,
    "n_est": 284628.5139,
    "ratio_se_n": 1.0021,
    "mean_diff": 0,
    "ratio_diff": 17.3064,
    "sd_y_est1": 0.4963,
    "sd_y_est2": 0.4973,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0007,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.035,
    "ldsc_observed_scale_h2_se": 0.0025,
    "ldsc_intercept_beta": 1.0148,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.1971,
    "ldsc_mean_chisq": 1.2092,
    "ldsc_ratio": 0.0707
}

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 13572073 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 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051326e+00 6.184943e+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 7.902547e+07 5.591513e+07 3.02000e+02 3.293094e+07 7.013849e+07 1.148601e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.110000e-05 7.787100e-03 -9.88123e-02 -2.151900e-03 2.120000e-05 2.204000e-03 1.005740e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.536500e-03 5.339900e-03 1.08030e-03 1.577000e-03 2.905200e-03 7.955700e-03 2.702780e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.813777e-01 2.935529e-01 0.00000e+00 2.224810e-01 4.748069e-01 7.355937e-01 1.000000e+00 ▇▇▇▇▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.813771e-01 2.935532e-01 0.00000e+00 2.224798e-01 4.748058e-01 7.355937e-01 9.999999e-01 ▇▇▇▇▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908360e-01 2.544122e-01 1.00000e-03 7.439300e-03 6.007160e-02 2.953780e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568397 0.9581572 NA NA NA NA NA 1.963564e-01 2.471072e-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 2.834490e+05 0.000000e+00 2.83449e+05 2.834490e+05 2.834490e+05 2.834490e+05 2.834490e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0038977 0.0023055 0.0909055 0.0909053 0.1110020 0.1894970 283449
1 693731 rs12238997 A G -0.0044780 0.0021776 0.0397466 0.0397451 0.1162560 0.1417730 283449
1 707522 rs371890604 G C -0.0047580 0.0024472 0.0518681 0.0518672 0.0976681 0.1293930 283449
1 717587 rs144155419 G A 0.0027552 0.0058588 0.6381694 0.6381690 0.0156561 0.0045926 283449
1 723329 rs189787166 A T -0.0260905 0.0171432 0.1280321 0.1280303 0.0017560 0.0003994 283449
1 730087 rs148120343 T C -0.0054542 0.0030341 0.0722354 0.0722334 0.0567111 0.0127796 283449
1 731718 rs142557973 T C -0.0034180 0.0020654 0.0979558 0.0979543 0.1221950 0.1543530 283449
1 732032 rs61770163 A C -0.0036401 0.0022024 0.0983785 0.0983774 0.1216330 0.1555510 283449
1 734349 rs141242758 T C -0.0035137 0.0020664 0.0890512 0.0890498 0.1214300 0.1525560 283449
1 740284 rs61770167 C T -0.0162077 0.0094541 0.0864629 0.0864622 0.0058008 0.0023962 283449
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0001023 0.0023886 0.9658489 0.9658492 0.0559389 0.0309934 283449
23 154923374 rs111332691 T A -0.0025305 0.0026235 0.3347819 0.3347809 0.0446430 0.0116556 283449
23 154925045 rs509981 C T -0.0008650 0.0012588 0.4920021 0.4920012 0.2457340 0.3634440 283449
23 154925895 rs538470 C T -0.0004625 0.0012880 0.7195434 0.7195426 0.2419890 0.3634440 283449
23 154927581 rs644138 G A -0.0008124 0.0011844 0.4927720 0.4927726 0.3020430 0.4635760 283449
23 154929412 rs557132 C T -0.0008628 0.0012592 0.4932090 0.4932069 0.2455770 0.3568210 283449
23 154929637 rs35185538 CT C -0.0020911 0.0013144 0.1116110 0.1116097 0.2298910 0.3011920 283449
23 154929952 rs4012982 CAA C -0.0007755 0.0013246 0.5582606 0.5582591 0.2394570 0.3165560 283449
23 154930230 rs781880 A G -0.0008242 0.0012591 0.5127528 0.5127519 0.2459850 0.3618540 283449
23 154930487 rs781879 T A -0.0083377 0.0043176 0.0534712 0.0534695 0.0196620 0.1263580 283449

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111002 ES:SE:LP:AF:SS:ID   -0.00389774:0.00230548:1.04141:0.111002:283449:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116256 ES:SE:LP:AF:SS:ID   -0.00447797:0.00217759:1.4007:0.116256:283449:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0976681    ES:SE:LP:AF:SS:ID   -0.00475795:0.00244721:1.2851:0.0976681:283449:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156561    ES:SE:LP:AF:SS:ID   0.00275518:0.00585884:0.195064:0.0156561:283449:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00175601   ES:SE:LP:AF:SS:ID   -0.0260905:0.0171432:0.892681:0.00175601:283449:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0567111    ES:SE:LP:AF:SS:ID   -0.00545416:0.00303406:1.14125:0.0567111:283449:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122195 ES:SE:LP:AF:SS:ID   -0.003418:0.00206544:1.00897:0.122195:283449:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121633 ES:SE:LP:AF:SS:ID   -0.00364008:0.00220241:1.0071:0.121633:283449:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12143  ES:SE:LP:AF:SS:ID   -0.00351372:0.00206637:1.05036:0.12143:283449:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00580075   ES:SE:LP:AF:SS:ID   -0.0162077:0.00945407:1.06317:0.00580075:283449:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00189494   ES:SE:LP:AF:SS:ID   0.0401782:0.0177966:1.62035:0.00189494:283449:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869328 ES:SE:LP:AF:SS:ID   0.00400736:0.00203766:1.30782:0.869328:283449:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00150014   ES:SE:LP:AF:SS:ID   -0.00108865:0.0186711:0.0206775:0.00150014:283449:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123376 ES:SE:LP:AF:SS:ID   -0.0035315:0.00201763:1.09657:0.123376:283449:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143082 ES:SE:LP:AF:SS:ID   -0.00261259:0.00199486:0.720534:0.143082:283449:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123491 ES:SE:LP:AF:SS:ID   -0.00356742:0.0020148:1.11562:0.123491:283449:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870404 ES:SE:LP:AF:SS:ID   0.00319934:0.00196354:0.986173:0.870404:283449:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875043 ES:SE:LP:AF:SS:ID   0.00322633:0.00199595:0.974694:0.875043:283449:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129114 ES:SE:LP:AF:SS:ID   -0.0035762:0.00196848:1.15953:0.129114:283449:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363928    ES:SE:LP:AF:SS:ID   -0.00147228:0.003576:0.167139:0.0363928:283449:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870008 ES:SE:LP:AF:SS:ID   0.00325081:0.00196157:1.01112:0.870008:283449:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870108 ES:SE:LP:AF:SS:ID   0.00323041:0.00196244:1.00113:0.870108:283449:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870011 ES:SE:LP:AF:SS:ID   0.00321636:0.00196152:0.995408:0.870011:283449:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00511627   ES:SE:LP:AF:SS:ID   0.000467212:0.0100062:0.0164824:0.00511627:283449:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00508228   ES:SE:LP:AF:SS:ID   0.000850993:0.0100336:0.0303935:0.00508228:283449:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00556722   ES:SE:LP:AF:SS:ID   -0.00135157:0.00978047:0.0505661:0.00556722:283449:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870087 ES:SE:LP:AF:SS:ID   0.00307174:0.00195808:0.932899:0.870087:283449:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12643  ES:SE:LP:AF:SS:ID   -0.003319:0.00199817:1.01452:0.12643:283449:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869641 ES:SE:LP:AF:SS:ID   0.00310108:0.00195345:0.949218:0.869641:283449:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868918 ES:SE:LP:AF:SS:ID   0.00299498:0.00195167:0.903469:0.868918:283449:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869802 ES:SE:LP:AF:SS:ID   0.00308271:0.00195511:0.939846:0.869802:283449:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869808 ES:SE:LP:AF:SS:ID   0.00308625:0.00195525:0.941331:0.869808:283449:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869817 ES:SE:LP:AF:SS:ID   0.00306471:0.00195531:0.93171:0.869817:283449:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870264 ES:SE:LP:AF:SS:ID   0.00306199:0.00196019:0.927136:0.870264:283449:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0992258    ES:SE:LP:AF:SS:ID   -0.00466455:0.00227704:1.39244:0.0992258:283449:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00646935   ES:SE:LP:AF:SS:ID   0.00451316:0.00883131:0.215152:0.00646935:283449:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874194 ES:SE:LP:AF:SS:ID   0.00304512:0.00198932:0.900199:0.874194:283449:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863513 ES:SE:LP:AF:SS:ID   0.00287185:0.00195085:0.850796:0.863513:283449:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86895  ES:SE:LP:AF:SS:ID   0.0034986:0.00196997:1.12068:0.86895:283449:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865891 ES:SE:LP:AF:SS:ID   0.00325868:0.00197053:1.00794:0.865891:283449:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0991024    ES:SE:LP:AF:SS:ID   -0.00296682:0.00235941:0.680696:0.0991024:283449:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871095 ES:SE:LP:AF:SS:ID   0.00315052:0.00199261:0.94364:0.871095:283449:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871095 ES:SE:LP:AF:SS:ID   0.0031503:0.00199261:0.943545:0.871095:283449:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871095 ES:SE:LP:AF:SS:ID   0.00315936:0.00199266:0.947487:0.871095:283449:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871465 ES:SE:LP:AF:SS:ID   0.00314336:0.00199374:0.939737:0.871465:283449:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126025 ES:SE:LP:AF:SS:ID   -0.00340628:0.00199539:1.05646:0.126025:283449:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105879 ES:SE:LP:AF:SS:ID   -0.00453641:0.00217154:1.43526:0.105879:283449:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854903 ES:SE:LP:AF:SS:ID   0.00367553:0.00195019:1.2257:0.854903:283449:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00167036   ES:SE:LP:AF:SS:ID   -0.0176921:0.0172089:0.517249:0.00167036:283449:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838532 ES:SE:LP:AF:SS:ID   -0.00124734:0.00192537:0.286437:0.838532:283449:rs376645387