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Merged
xueweic merged 10 commits into from
Apr 21, 2025
Merged

minor fixed #67

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b10d893
minor fix
xueweic Apr 21, 2025
f4a12d1
Merge branch 'main' of https://github.com/xueweic/colocboost
xueweic Apr 21, 2025
8d2162f
Update CITATION
xueweic Apr 21, 2025
0de97f1
Update Summary_Statistics_Colocalization.Rmd
xueweic Apr 21, 2025
1b8b74e
Update LD_Free_Colocalization.Rmd
xueweic Apr 21, 2025
7015622
fix
xueweic Apr 21, 2025
d2bcc48
fix
xueweic Apr 21, 2025
6524c89
Merge branch 'StatFunGen:main' into main
xueweic Apr 21, 2025
6f15847
fix
xueweic Apr 21, 2025
8eb3ee1
Merge branch 'main' of https://github.com/xueweic/colocboost
xueweic Apr 21, 2025
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2 changes: 1 addition & 1 deletion inst/CITATION
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ citEntry(
author = c(person("Xuewei", "Cao"),
person("Haochen", "Sun"),
person("Ru", "Feng"),
person("Rajib", "Mazumder"),
person("Rahul", "Mazumder"),
person("Cristian F. B.", "Najar"),
person("Yang I.", "Li"),
person("Philip L.", "de Jager"),
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15 changes: 12 additions & 3 deletions vignettes/LD_Free_Colocalization.Rmd
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Expand Up @@ -129,13 +129,22 @@ for (i in 1:length(X)){
x <- X[[i]]
y <- Y[[i]]
effect_n[i] <- length(y)
rr <- susieR::univariate_regression(X = x, y = y)
effect_est <- cbind(effect_est, rr$betahat)
effect_se <- cbind(effect_se, rr$sebetahat)
# simply use `rr <- susieR::univariate_regression(X = x, y = y)`
output = matrix(0,ncol(x),2)
for (i in 1:ncol(x)) {
fit = summary(lm(y ~ x[,i]))$coef
if (nrow(fit) == 2)
output[i,] = as.vector(fit[2,1:2])
else
output[i,] = c(0,0)
}
effect_est <- cbind(effect_est, output[,1])
effect_se <- cbind(effect_se, output[,2])
}
colnames(effect_est) <- colnames(effect_se) <- c("Y1", "Y2", "Y3", "Y4", "Y5")
rownames(effect_est) <- rownames(effect_se) <- colnames(X[[1]])


# Run colocboost
res <- colocboost(effect_est = effect_est, effect_se = effect_se, effect_n = effect_n)

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14 changes: 11 additions & 3 deletions vignettes/Summary_Statistics_Colocalization.Rmd
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Expand Up @@ -189,9 +189,17 @@ for (i in 1:length(X)){
x <- X[[i]]
y <- Y[[i]]
effect_n[i] <- length(y)
rr <- susieR::univariate_regression(X = x, y = y)
effect_est <- cbind(effect_est, rr$betahat)
effect_se <- cbind(effect_se, rr$sebetahat)
# simply use `rr <- susieR::univariate_regression(X = x, y = y)`
output = matrix(0,ncol(x),2)
for (i in 1:ncol(x)) {
fit = summary(lm(y ~ x[,i]))$coef
if (nrow(fit) == 2)
output[i,] = as.vector(fit[2,1:2])
else
output[i,] = c(0,0)
}
effect_est <- cbind(effect_est, output[,1])
effect_se <- cbind(effect_se, output[,2])
}
colnames(effect_est) <- colnames(effect_se) <- c("Y1", "Y2", "Y3", "Y4", "Y5")
rownames(effect_est) <- rownames(effect_se) <- colnames(X[[1]])
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