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-1150_2/ukb-d-1150_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-1150_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 17:10:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1150_2/ukb-d-1150_2.vcf.gz ...
Read summary statistics for 13585047 SNPs.
Dropped 12706 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: 0.0256 (0.0032)
Lambda GC: 1.1421
Mean Chi^2: 1.167
Intercept: 1.0086 (0.0098)
Ratio: 0.0517 (0.0587)
Analysis finished at Mon Nov 25 17:13:07 2019
Total time elapsed: 2.0m:7.61s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0876,
    "mean_EFFECT": -1.4845e-06,
    "n": 303009,
    "n_snps": 13585047,
    "n_clumped_hits": 2,
    "n_p_sig": 136,
    "n_mono": 0,
    "n_ns": 1251774,
    "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": 568959,
    "n_est": 304139.6126,
    "ratio_se_n": 1.0019,
    "mean_diff": -9.8451e-07,
    "ratio_diff": 1.8794,
    "sd_y_est1": 0.4951,
    "sd_y_est2": 0.496,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0002,
    "r2_sum3": 0.0002,
    "r2_sum4": 0.0002,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0256,
    "ldsc_observed_scale_h2_se": 0.0032,
    "ldsc_intercept_beta": 1.0086,
    "ldsc_intercept_se": 0.0098,
    "ldsc_lambda_gc": 1.1421,
    "ldsc_mean_chisq": 1.167,
    "ldsc_ratio": 0.0515
}

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 13573005 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 9.051353e+00 6.184965e+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 7.902464e+07 5.591467e+07 3.02000e+02 3.293066e+07 7.013788e+07 1.148574e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.500000e-06 7.484200e-03 -1.05134e-01 -2.065500e-03 -6.000000e-07 2.061500e-03 9.810940e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.343000e-03 5.153700e-03 1.04680e-03 1.521400e-03 2.803300e-03 7.678100e-03 2.567430e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.863415e-01 2.929145e-01 0.00000e+00 2.289112e-01 4.817936e-01 7.399715e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.863409e-01 2.929148e-01 0.00000e+00 2.289102e-01 4.817933e-01 7.399720e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908216e-01 2.544060e-01 1.00000e-03 7.435800e-03 6.005850e-02 2.953490e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568959 0.9581187 NA NA NA NA NA 1.963476e-01 2.471028e-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 3.030090e+05 0.000000e+00 3.03009e+05 3.030090e+05 3.030090e+05 3.030090e+05 3.030090e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0025816 0.0022269 0.2463310 0.2463288 0.1106100 0.1894970 303009
1 693731 rs12238997 A G -0.0008455 0.0021048 0.6878916 0.6878923 0.1156930 0.1417730 303009
1 707522 rs371890604 G C -0.0024040 0.0023672 0.3098347 0.3098357 0.0971589 0.1293930 303009
1 717587 rs144155419 G A 0.0016871 0.0056367 0.7647016 0.7647009 0.0157272 0.0045926 303009
1 723329 rs189787166 A T -0.0180536 0.0165948 0.2766362 0.2766361 0.0017443 0.0003994 303009
1 730087 rs148120343 T C -0.0027534 0.0029341 0.3480319 0.3480318 0.0563773 0.0127796 303009
1 731718 rs142557973 T C -0.0018143 0.0019959 0.3633407 0.3633423 0.1216550 0.1543530 303009
1 732032 rs61770163 A C -0.0002866 0.0021291 0.8929240 0.8929242 0.1210630 0.1555510 303009
1 734349 rs141242758 T C -0.0017635 0.0019968 0.3771473 0.3771448 0.1208920 0.1525560 303009
1 740284 rs61770167 C T -0.0014628 0.0090979 0.8722639 0.8722637 0.0058287 0.0023962 303009
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0003215 0.0023096 0.8893049 0.8893052 0.0561101 0.0309934 303009
23 154923374 rs111332691 T A -0.0014374 0.0025360 0.5708631 0.5708624 0.0447775 0.0116556 303009
23 154925045 rs509981 C T -0.0006649 0.0012198 0.5857186 0.5857177 0.2461110 0.3634440 303009
23 154925895 rs538470 C T -0.0007448 0.0012477 0.5505896 0.5505875 0.2424160 0.3634440 303009
23 154927581 rs644138 G A -0.0004220 0.0011474 0.7130073 0.7130084 0.3025960 0.4635760 303009
23 154929412 rs557132 C T -0.0006143 0.0012202 0.6146204 0.6146183 0.2459650 0.3568210 303009
23 154929637 rs35185538 CT C 0.0001517 0.0012734 0.9051659 0.9051661 0.2301710 0.3011920 303009
23 154929952 rs4012982 CAA C -0.0000066 0.0012834 0.9959130 0.9959134 0.2398950 0.3165560 303009
23 154930230 rs781880 A G -0.0006575 0.0012200 0.5899416 0.5899395 0.2463730 0.3618540 303009
23 154930487 rs781879 T A -0.0030127 0.0041876 0.4718653 0.4718648 0.0195622 0.1263580 303009

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11061  ES:SE:LP:AF:SS:ID   -0.00258165:0.00222688:0.608481:0.11061:303009:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115693 ES:SE:LP:AF:SS:ID   -0.000845538:0.00210481:0.16248:0.115693:303009:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0971589    ES:SE:LP:AF:SS:ID   -0.00240405:0.0023672:0.50887:0.0971589:303009:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157272    ES:SE:LP:AF:SS:ID   0.00168714:0.0056367:0.116508:0.0157272:303009:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00174428   ES:SE:LP:AF:SS:ID   -0.0180536:0.0165948:0.558091:0.00174428:303009:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0563773    ES:SE:LP:AF:SS:ID   -0.0027534:0.0029341:0.458381:0.0563773:303009:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121655 ES:SE:LP:AF:SS:ID   -0.00181433:0.00199593:0.439686:0.121655:303009:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121063 ES:SE:LP:AF:SS:ID   -0.000286586:0.00212909:0.0491855:0.121063:303009:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120892 ES:SE:LP:AF:SS:ID   -0.00176353:0.00199682:0.423489:0.120892:303009:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00582866   ES:SE:LP:AF:SS:ID   -0.0014628:0.00909793:0.0593521:0.00582866:303009:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187948   ES:SE:LP:AF:SS:ID   0.00902306:0.0172619:0.221001:0.00187948:303009:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869812 ES:SE:LP:AF:SS:ID   0.00107454:0.00196834:0.232749:0.869812:303009:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00150526   ES:SE:LP:AF:SS:ID   -0.013605:0.0180374:0.346121:0.00150526:303009:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122838 ES:SE:LP:AF:SS:ID   -0.00112376:0.0019496:0.248458:0.122838:303009:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142693 ES:SE:LP:AF:SS:ID   -0.00122876:0.00192627:0.281048:0.142693:303009:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.122956 ES:SE:LP:AF:SS:ID   -0.0011599:0.00194684:0.258596:0.122956:303009:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870903 ES:SE:LP:AF:SS:ID   0.00192593:0.0018968:0.508727:0.870903:303009:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875547 ES:SE:LP:AF:SS:ID   0.00136122:0.00192852:0.318498:0.875547:303009:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128614 ES:SE:LP:AF:SS:ID   -0.002015:0.00190153:0.538658:0.128614:303009:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0364131    ES:SE:LP:AF:SS:ID   0.00227436:0.00344817:0.292838:0.0364131:303009:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870499 ES:SE:LP:AF:SS:ID   0.00201931:0.00189485:0.542772:0.870499:303009:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870603 ES:SE:LP:AF:SS:ID   0.00197338:0.00189568:0.525959:0.870603:303009:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870496 ES:SE:LP:AF:SS:ID   0.00203204:0.00189478:0.54741:0.870496:303009:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504134   ES:SE:LP:AF:SS:ID   -0.00569006:0.00974269:0.252434:0.00504134:303009:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500865   ES:SE:LP:AF:SS:ID   -0.0054615:0.00976879:0.239495:0.00500865:303009:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00562072   ES:SE:LP:AF:SS:ID   0.0106198:0.00938983:0.588283:0.00562072:303009:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870577 ES:SE:LP:AF:SS:ID   0.00197675:0.00189137:0.528773:0.870577:303009:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125962 ES:SE:LP:AF:SS:ID   -0.00180856:0.00193009:0.457498:0.125962:303009:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870139 ES:SE:LP:AF:SS:ID   0.00207196:0.00188676:0.565212:0.870139:303009:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869458 ES:SE:LP:AF:SS:ID   0.00197667:0.00188531:0.531022:0.869458:303009:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870299 ES:SE:LP:AF:SS:ID   0.00192761:0.00188843:0.51233:0.870299:303009:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870304 ES:SE:LP:AF:SS:ID   0.00192798:0.00188857:0.512412:0.870304:303009:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870312 ES:SE:LP:AF:SS:ID   0.00192317:0.00188862:0.510689:0.870312:303009:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870753 ES:SE:LP:AF:SS:ID   0.0019859:0.0018935:0.531253:0.870753:303009:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0987765    ES:SE:LP:AF:SS:ID   -0.00156609:0.00220103:0.321702:0.0987765:303009:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00650759   ES:SE:LP:AF:SS:ID   0.00411417:0.00848558:0.202186:0.00650759:303009:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874709 ES:SE:LP:AF:SS:ID   0.00177391:0.0019221:0.448478:0.874709:303009:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864077 ES:SE:LP:AF:SS:ID   0.00172304:0.00188475:0.442957:0.864077:303009:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869464 ES:SE:LP:AF:SS:ID   0.00186315:0.00190305:0.484704:0.869464:303009:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866385 ES:SE:LP:AF:SS:ID   0.00173197:0.00190331:0.440291:0.866385:303009:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0986435    ES:SE:LP:AF:SS:ID   -0.0016438:0.00227965:0.327105:0.0986435:303009:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871617 ES:SE:LP:AF:SS:ID   0.00176577:0.00192525:0.444837:0.871617:303009:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871616 ES:SE:LP:AF:SS:ID   0.00176578:0.00192525:0.444843:0.871616:303009:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871616 ES:SE:LP:AF:SS:ID   0.00177464:0.00192529:0.447748:0.871616:303009:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871994 ES:SE:LP:AF:SS:ID   0.00183136:0.00192639:0.46626:0.871994:303009:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125503 ES:SE:LP:AF:SS:ID   -0.00188214:0.00192782:0.482918:0.125503:303009:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105345 ES:SE:LP:AF:SS:ID   -0.00197687:0.0020989:0.46059:0.105345:303009:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855421 ES:SE:LP:AF:SS:ID   0.00216535:0.00188422:0.601236:0.855421:303009:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00167131   ES:SE:LP:AF:SS:ID   -0.0250295:0.0166044:0.880388:0.00167131:303009:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838198 ES:SE:LP:AF:SS:ID   -0.000850195:0.00185594:0.189172:0.838198:303009:rs376645387