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-30880_irnt/ukb-d-30880_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-30880_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 14:56:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30880_irnt/ukb-d-30880_irnt.vcf.gz ...
Read summary statistics for 13585993 SNPs.
Dropped 12709 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: 0.2039 (0.0492)
Lambda GC: 1.6312
Mean Chi^2: 3.7104
Intercept: 1.12 (0.0156)
Ratio: 0.0443 (0.0058)
Analysis finished at Mon Nov 25 14:58:23 2019
Total time elapsed: 2.0m:15.94s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3819,
    "mean_EFFECT": -2.3439e-06,
    "n": 343836,
    "n_snps": 13585993,
    "n_clumped_hits": 256,
    "n_p_sig": 50138,
    "n_mono": 0,
    "n_ns": 1251781,
    "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": 569154,
    "n_est": 345181.7796,
    "ratio_se_n": 1.002,
    "mean_diff": 2.5164e-07,
    "ratio_diff": 0.3734,
    "sd_y_est1": 0.8457,
    "sd_y_est2": 0.8473,
    "r2_sum1": 0.0585,
    "r2_sum2": 0.0818,
    "r2_sum3": 0.0815,
    "r2_sum4": 0.081,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.2039,
    "ldsc_observed_scale_h2_se": 0.0492,
    "ldsc_intercept_beta": 1.12,
    "ldsc_intercept_se": 0.0156,
    "ldsc_lambda_gc": 1.6312,
    "ldsc_mean_chisq": 3.7104,
    "ldsc_ratio": 0.0443
}

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 13573948 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 9.051238e+00 6.184962e+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 7.902571e+07 5.591523e+07 3.02000e+02 3.293111e+07 7.013925e+07 1.148602e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.300000e-06 1.298030e-02 -4.65770e-01 -3.888300e-03 1.300000e-06 3.892400e-03 3.379000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.569600e-03 8.266300e-03 1.67660e-03 2.439900e-03 4.496000e-03 1.231500e-02 4.178200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.465692e-01 3.036434e-01 0.00000e+00 1.701300e-01 4.278396e-01 7.097608e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.465687e-01 3.036436e-01 0.00000e+00 1.701301e-01 4.278420e-01 7.097564e-01 9.999998e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908099e-01 2.544045e-01 1.00000e-03 7.431500e-03 6.004100e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569154 0.9581073 NA NA NA NA NA 1.963392e-01 2.471027e-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 3.438360e+05 0.000000e+00 3.43836e+05 3.438360e+05 3.438360e+05 3.438360e+05 3.438360e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0027613 0.0035721 0.4395102 0.4395113 0.1105200 0.1894970 343836
1 693731 rs12238997 A G -0.0011528 0.0033737 0.7325799 0.7325752 0.1158100 0.1417730 343836
1 707522 rs371890604 G C 0.0015503 0.0037946 0.6828699 0.6828668 0.0972540 0.1293930 343836
1 717587 rs144155419 G A -0.0124990 0.0090588 0.1676598 0.1676595 0.0156620 0.0045926 343836
1 723329 rs189787166 A T -0.0092025 0.0266960 0.7303096 0.7303090 0.0017349 0.0003994 343836
1 730087 rs148120343 T C -0.0046803 0.0047018 0.3195200 0.3195285 0.0564260 0.0127796 343836
1 731718 rs142557973 T C -0.0011052 0.0031998 0.7298002 0.7297962 0.1217000 0.1543530 343836
1 732032 rs61770163 A C 0.0000848 0.0034144 0.9802000 0.9801968 0.1211000 0.1555510 343836
1 734349 rs141242758 T C -0.0009744 0.0032015 0.7608499 0.7608557 0.1209200 0.1525560 343836
1 740284 rs61770167 C T 0.0226630 0.0146850 0.1227600 0.1227640 0.0057564 0.0023962 343836
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0017117 0.0036969 0.6433495 0.6433575 0.056204 0.0309934 343836
23 154923374 rs111332691 T A 0.0089624 0.0040583 0.0272157 0.0272155 0.044880 0.0116556 343836
23 154925045 rs509981 C T 0.0012802 0.0019549 0.5125603 0.5125532 0.245700 0.3634440 343836
23 154925895 rs538470 C T 0.0011665 0.0019998 0.5596700 0.5596858 0.242030 0.3634440 343836
23 154927581 rs644138 G A 0.0015711 0.0018386 0.3928204 0.3928231 0.302290 0.4635760 343836
23 154929412 rs557132 C T 0.0012743 0.0019555 0.5146204 0.5146275 0.245560 0.3568210 343836
23 154929637 rs35185538 CT C 0.0007136 0.0020409 0.7266194 0.7266163 0.229820 0.3011920 343836
23 154929952 rs4012982 CAA C 0.0009065 0.0020566 0.6593606 0.6593611 0.239530 0.3165560 343836
23 154930230 rs781880 A G 0.0013977 0.0019552 0.4746997 0.4746937 0.245960 0.3618540 343836
23 154930487 rs781879 T A 0.0056700 0.0067020 0.3975402 0.3975438 0.019564 0.1263580 343836

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11052  ES:SE:LP:AF:SS:ID   -0.0027613:0.0035721:0.357031:0.11052:343836:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   -0.0011528:0.0033737:0.135145:0.11581:343836:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097254 ES:SE:LP:AF:SS:ID   0.0015503:0.0037946:0.165662:0.097254:343836:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015662 ES:SE:LP:AF:SS:ID   -0.012499:0.0090588:0.775571:0.015662:343836:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017349    ES:SE:LP:AF:SS:ID   -0.0092025:0.026696:0.136493:0.0017349:343836:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056426 ES:SE:LP:AF:SS:ID   -0.0046803:0.0047018:0.495502:0.056426:343836:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1217   ES:SE:LP:AF:SS:ID   -0.0011052:0.0031998:0.136796:0.1217:343836:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.1211   ES:SE:LP:AF:SS:ID   8.4753e-05:0.0034144:0.0086853:0.1211:343836:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12092  ES:SE:LP:AF:SS:ID   -0.0009744:0.0032015:0.118701:0.12092:343836:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057564    ES:SE:LP:AF:SS:ID   0.022663:0.014685:0.910943:0.0057564:343836:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018612    ES:SE:LP:AF:SS:ID   0.031602:0.027841:0.591184:0.0018612:343836:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   7.3576e-05:0.0031563:0.00815395:0.8698:343836:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015221    ES:SE:LP:AF:SS:ID   0.014289:0.028665:0.20892:0.0015221:343836:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12288  ES:SE:LP:AF:SS:ID   -0.00048069:0.0031257:0.0566143:0.12288:343836:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14268  ES:SE:LP:AF:SS:ID   -0.00094091:0.0030892:0.118792:0.14268:343836:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   -0.0003919:0.0031213:0.0457189:0.12299:343836:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87096  ES:SE:LP:AF:SS:ID   0.00011129:0.0030421:0.0128613:0.87096:343836:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87552  ES:SE:LP:AF:SS:ID   -0.00026757:0.0030922:0.0310317:0.87552:343836:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12857  ES:SE:LP:AF:SS:ID   -0.00052171:0.0030496:0.0634058:0.12857:343836:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036315 ES:SE:LP:AF:SS:ID   0.0018198:0.005537:0.129356:0.036315:343836:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.00026666:0.0030389:0.0314797:0.87056:343836:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   0.0001848:0.0030403:0.0215775:0.87066:343836:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87055  ES:SE:LP:AF:SS:ID   0.00029785:0.0030388:0.0353068:0.87055:343836:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050494    ES:SE:LP:AF:SS:ID   0.0073141:0.015586:0.194581:0.0050494:343836:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050163    ES:SE:LP:AF:SS:ID   0.0072602:0.015628:0.192303:0.0050163:343836:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055482    ES:SE:LP:AF:SS:ID   0.012214:0.015165:0.376151:0.0055482:343836:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   -7.2196e-06:0.0030336:0.000825944:0.87064:343836:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   0.00026131:0.0030952:0.0302487:0.12592:343836:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   -0.0002663:0.0030264:0.0315731:0.87021:343836:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   -7.2308e-05:0.0030236:0.00836641:0.86949:343836:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   -6.0395e-05:0.0030289:0.00696518:0.87036:343836:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   -6.5333e-05:0.0030291:0.00753927:0.87036:343836:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   -2.109e-05:0.0030292:0.00242142:0.87037:343836:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87081  ES:SE:LP:AF:SS:ID   2.3955e-05:0.0030369:0.00274034:0.87081:343836:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098797 ES:SE:LP:AF:SS:ID   -0.00063746:0.0035295:0.0671864:0.098797:343836:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.006435 ES:SE:LP:AF:SS:ID   0.014226:0.0137:0.524213:0.006435:343836:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.8747   ES:SE:LP:AF:SS:ID   0.00032377:0.0030819:0.0379481:0.8747:343836:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86411  ES:SE:LP:AF:SS:ID   0.00056182:0.0030229:0.069275:0.86411:343836:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.00025174:0.0030517:0.0295322:0.8695:343836:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.00064126:0.0030523:0.0790423:0.86644:343836:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098742 ES:SE:LP:AF:SS:ID   -0.00033827:0.003654:0.0332765:0.098742:343836:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.00045496:0.0030872:0.054118:0.87161:343836:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.00045506:0.0030872:0.0541328:0.87161:343836:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.00045075:0.0030873:0.053587:0.87161:343836:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87199  ES:SE:LP:AF:SS:ID   0.00019737:0.003089:0.0227109:0.87199:343836:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12551  ES:SE:LP:AF:SS:ID   -0.00044898:0.0030911:0.0532973:0.12551:343836:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   0.00055939:0.003366:0.0614753:0.10539:343836:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85547  ES:SE:LP:AF:SS:ID   -0.00017759:0.0030217:0.0208479:0.85547:343836:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016536    ES:SE:LP:AF:SS:ID   -0.020044:0.026763:0.34304:0.0016536:343836:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83828  ES:SE:LP:AF:SS:ID   -0.004398:0.0029752:0.855862:0.83828:343836:rs376645387