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-30180_irnt/ukb-d-30180_irnt.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-30180_irnt/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 14:57:39 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30180_irnt/ukb-d-30180_irnt.vcf.gz ...
Read summary statistics for 13586282 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: 0.1366 (0.0093)
Lambda GC: 1.5216
Mean Chi^2: 2.1455
Intercept: 1.1704 (0.02)
Ratio: 0.1487 (0.0175)
Analysis finished at Mon Nov 25 14:59:58 2019
Total time elapsed: 2.0m:19.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3296,
    "mean_EFFECT": -0,
    "n": 349861,
    "n_snps": 13586282,
    "n_clumped_hits": 297,
    "n_p_sig": 56499,
    "n_mono": 0,
    "n_ns": 1251790,
    "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": 569186,
    "n_est": 351190.1861,
    "ratio_se_n": 1.0019,
    "mean_diff": 2.7684e-08,
    "ratio_diff": 0.0698,
    "sd_y_est1": 0.9864,
    "sd_y_est2": 0.9883,
    "r2_sum1": 0.0653,
    "r2_sum2": 0.0671,
    "r2_sum3": 0.0668,
    "r2_sum4": 0.0666,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1366,
    "ldsc_observed_scale_h2_se": 0.0093,
    "ldsc_intercept_beta": 1.1704,
    "ldsc_intercept_se": 0.02,
    "ldsc_lambda_gc": 1.5216,
    "ldsc_mean_chisq": 2.1455,
    "ldsc_ratio": 0.1488
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 13574236 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 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 9.051329e+00 6.184984e+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 7.902513e+07 5.591486e+07 3.02000e+02 3.293100e+07 7.013871e+07 1.148589e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.120000e-05 1.457290e-02 -5.60339e-01 -4.424300e-03 -1.900000e-05 4.377600e-03 3.155550e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.909700e-03 9.559200e-03 1.93830e-03 2.821300e-03 5.199000e-03 1.424090e-02 4.852160e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.524127e-01 3.027180e-01 0.00000e+00 1.782711e-01 4.367219e-01 7.147086e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.524122e-01 3.027182e-01 0.00000e+00 1.782700e-01 4.367216e-01 7.147083e-01 1.000000e+00 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908059e-01 2.544033e-01 1.00000e-03 7.430400e-03 6.003370e-02 2.953180e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569186 0.9581058 NA NA NA NA NA 1.963355e-01 2.471013e-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 3.498610e+05 0.000000e+00 3.49861e+05 3.498610e+05 3.498610e+05 3.498610e+05 3.498610e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0009563 0.0041288 0.8168310 0.8168312 0.1106490 0.1894970 349861
1 693731 rs12238997 A G 0.0053509 0.0039015 0.1702159 0.1702153 0.1158220 0.1417730 349861
1 707522 rs371890604 G C 0.0024702 0.0043876 0.5734400 0.5734394 0.0972503 0.1293930 349861
1 717587 rs144155419 G A 0.0241725 0.0104547 0.0207721 0.0207712 0.0157178 0.0045926 349861
1 723329 rs189787166 A T -0.0124421 0.0310351 0.6884906 0.6884907 0.0017201 0.0003994 349861
1 730087 rs148120343 T C -0.0023031 0.0054330 0.6716330 0.6716336 0.0564796 0.0127796 349861
1 731718 rs142557973 T C 0.0054696 0.0036999 0.1393330 0.1393327 0.1217450 0.1543530 349861
1 732032 rs61770163 A C 0.0037674 0.0039473 0.3398717 0.3398714 0.1211440 0.1555510 349861
1 734349 rs141242758 T C 0.0054234 0.0037019 0.1429151 0.1429145 0.1209740 0.1525560 349861
1 740284 rs61770167 C T 0.0391665 0.0169357 0.0207420 0.0207414 0.0057855 0.0023962 349861
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0030512 0.0042728 0.4751580 0.4751578 0.0561652 0.0309934 349861
23 154923374 rs111332691 T A -0.0025936 0.0046974 0.5808567 0.5808561 0.0447935 0.0116556 349861
23 154925045 rs509981 C T -0.0075014 0.0022605 0.0009052 0.0009051 0.2454440 0.3634440 349861
23 154925895 rs538470 C T -0.0072752 0.0023122 0.0016529 0.0016528 0.2417890 0.3634440 349861
23 154927581 rs644138 G A -0.0058629 0.0021256 0.0058123 0.0058121 0.3020040 0.4635760 349861
23 154929412 rs557132 C T -0.0075766 0.0022612 0.0008060 0.0008059 0.2452990 0.3568210 349861
23 154929637 rs35185538 CT C -0.0089867 0.0023602 0.0001403 0.0001403 0.2295300 0.3011920 349861
23 154929952 rs4012982 CAA C -0.0082912 0.0023783 0.0004900 0.0004899 0.2392530 0.3165560 349861
23 154930230 rs781880 A G -0.0073280 0.0022608 0.0011897 0.0011895 0.2457090 0.3618540 349861
23 154930487 rs781879 T A -0.0025297 0.0077610 0.7444594 0.7444587 0.0195209 0.1263580 349861

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110649 ES:SE:LP:AF:SS:ID   0.000956323:0.0041288:0.0878678:0.110649:349861:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115822 ES:SE:LP:AF:SS:ID   0.0053509:0.00390146:0.769:0.115822:349861:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972503    ES:SE:LP:AF:SS:ID   0.00247019:0.0043876:0.241512:0.0972503:349861:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157178    ES:SE:LP:AF:SS:ID   0.0241725:0.0104547:1.68252:0.0157178:349861:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00172013   ES:SE:LP:AF:SS:ID   -0.0124421:0.0310351:0.162102:0.00172013:349861:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564796    ES:SE:LP:AF:SS:ID   -0.0023031:0.00543303:0.172868:0.0564796:349861:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121745 ES:SE:LP:AF:SS:ID   0.00546955:0.00369994:0.855946:0.121745:349861:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121144 ES:SE:LP:AF:SS:ID   0.00376738:0.0039473:0.468685:0.121144:349861:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120974 ES:SE:LP:AF:SS:ID   0.0054234:0.00370192:0.844922:0.120974:349861:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578551   ES:SE:LP:AF:SS:ID   0.0391665:0.0169357:1.68315:0.00578551:349861:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188271   ES:SE:LP:AF:SS:ID   -0.0129687:0.031984:0.164228:0.00188271:349861:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869759 ES:SE:LP:AF:SS:ID   -0.0042979:0.0036499:0.621635:0.869759:349861:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153174   ES:SE:LP:AF:SS:ID   -0.0718497:0.0330214:1.5292:0.00153174:349861:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122895 ES:SE:LP:AF:SS:ID   0.00525263:0.00361448:0.835163:0.122895:349861:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142708 ES:SE:LP:AF:SS:ID   0.00593871:0.00357279:1.0156:0.142708:349861:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123012 ES:SE:LP:AF:SS:ID   0.00546274:0.00360942:0.885516:0.123012:349861:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870893 ES:SE:LP:AF:SS:ID   -0.00538146:0.00351721:0.899598:0.870893:349861:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875492 ES:SE:LP:AF:SS:ID   -0.00540471:0.00357561:0.883891:0.875492:349861:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   0.00538889:0.00352597:0.898157:0.128631:349861:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363487    ES:SE:LP:AF:SS:ID   -0.0050014:0.00640013:0.361973:0.0363487:349861:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870486 ES:SE:LP:AF:SS:ID   -0.0053867:0.00351351:0.90225:0.870486:349861:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870587 ES:SE:LP:AF:SS:ID   -0.0051622:0.00351506:0.847886:0.870587:349861:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870481 ES:SE:LP:AF:SS:ID   -0.00540208:0.00351336:0.906046:0.870481:349861:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504546   ES:SE:LP:AF:SS:ID   -0.00389035:0.0180402:0.0813088:0.00504546:349861:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501229   ES:SE:LP:AF:SS:ID   -0.00351005:0.0180883:0.0725598:0.00501229:349861:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558051   ES:SE:LP:AF:SS:ID   0.0300128:0.0174792:1.06565:0.00558051:349861:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870566 ES:SE:LP:AF:SS:ID   -0.00513044:0.00350721:0.8431:0.870566:349861:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125972 ES:SE:LP:AF:SS:ID   0.00516196:0.00357892:0.826199:0.125972:349861:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87013  ES:SE:LP:AF:SS:ID   -0.00525994:0.00349876:0.876985:0.87013:349861:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869408 ES:SE:LP:AF:SS:ID   -0.00489452:0.00349544:0.791997:0.869408:349861:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870284 ES:SE:LP:AF:SS:ID   -0.00521918:0.00350179:0.866104:0.870284:349861:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87029  ES:SE:LP:AF:SS:ID   -0.00522329:0.00350204:0.866998:0.87029:349861:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870299 ES:SE:LP:AF:SS:ID   -0.005217:0.00350215:0.865453:0.870299:349861:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87074  ES:SE:LP:AF:SS:ID   -0.00516696:0.00351106:0.850402:0.87074:349861:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098799 ES:SE:LP:AF:SS:ID   0.00377501:0.00408132:0.44978:0.098799:349861:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647255   ES:SE:LP:AF:SS:ID   0.0271919:0.0157909:1.07022:0.00647255:349861:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874649 ES:SE:LP:AF:SS:ID   -0.00529033:0.00356353:0.861202:0.874649:349861:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864035 ES:SE:LP:AF:SS:ID   -0.00445484:0.00349446:0.693852:0.864035:349861:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   -0.00481155:0.0035284:0.762771:0.869419:349861:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866376 ES:SE:LP:AF:SS:ID   -0.00548935:0.0035292:0.921366:0.866376:349861:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987125    ES:SE:LP:AF:SS:ID   0.00186316:0.00422659:0.180888:0.0987125:349861:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871561 ES:SE:LP:AF:SS:ID   -0.0056388:0.0035694:0.942478:0.871561:349861:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871561 ES:SE:LP:AF:SS:ID   -0.00563846:0.0035694:0.942395:0.871561:349861:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   -0.00564175:0.00356946:0.943171:0.87156:349861:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871932 ES:SE:LP:AF:SS:ID   -0.00556098:0.00357149:0.922777:0.871932:349861:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125555 ES:SE:LP:AF:SS:ID   0.00521448:0.00357429:0.839841:0.125555:349861:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105385 ES:SE:LP:AF:SS:ID   0.00291029:0.00389193:0.342374:0.105385:349861:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855372 ES:SE:LP:AF:SS:ID   -0.00418288:0.00349348:0.636059:0.855372:349861:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164253   ES:SE:LP:AF:SS:ID   -0.00342391:0.031089:0.0398604:0.00164253:349861:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838283 ES:SE:LP:AF:SS:ID   -0.0018923:0.00344091:0.234808:0.838283:349861:rs376645387