Skip to content

Commit

Permalink
fix bug in summarizeResults
Browse files Browse the repository at this point in the history 
error if filtering criteria too stringent
only 1 CNV left resulting in dataframe being turned into vector resulting in error in setting rowname and colname
also error if no CNVs
  • Loading branch information
@JEFworks
JEFworks committed Aug 20, 2019
1 parent f0eed94 commit b3648e7
Show file tree
Hide file tree
Showing 2 changed files with 80 additions and 44 deletions.
113 changes: 74 additions & 39 deletions R/HoneyBADGER.R
View file
Original file line number Diff line number Diff line change
Expand Up @@ -1885,75 +1885,110 @@ HoneyBADGER$methods(
if(geneBased & !alleleBased) {
rgs <- cnvs[['gene-based']][['all']]
retest <- results[['gene-based']]

amp.gexp.prob <- do.call(rbind, lapply(retest, function(x) x[[1]]))
del.gexp.prob <- do.call(rbind, lapply(retest, function(x) x[[2]]))
df <- cbind(as.data.frame(rgs),
avg.amp.gexp=rowMeans(amp.gexp.prob),
avg.del.gexp=rowMeans(del.gexp.prob),
amp.gexp.prob,
df <- cbind(as.data.frame(rgs), avg.amp.gexp = rowMeans(amp.gexp.prob),
avg.del.gexp = rowMeans(del.gexp.prob), amp.gexp.prob,
del.gexp.prob)

## filter to regions with at least some highly confident cells
names <- apply(as.data.frame(rgs), 1, paste0, collapse = ":")
vi1 <- rowSums(amp.gexp.prob > t) > min.num.cells
amp.gexp.prob <- amp.gexp.prob[vi1,] ## amplifications
if(sum(vi1) > 1) {
amp.gexp.prob <- amp.gexp.prob[vi1, ]
rownames(amp.gexp.prob) <- paste0("amp", names[vi1])
colnames(amp.gexp.prob) <- paste0("amp.gexp.", colnames(amp.gexp.prob))
} else if (sum(vi) == 1) {
amp.gexp.prob <- t(amp.gexp.prob[vi1, ])
rownames(amp.gexp.prob) <- paste0("amp", names[vi1])
colnames(amp.gexp.prob) <- paste0("amp.gexp.", colnames(amp.gexp.prob))
} else {
amp.gexp.prob <- c()
}
vi2 <- rowSums(del.gexp.prob > t) > min.num.cells
del.gexp.prob <- del.gexp.prob[vi2,] ## amplifications

names <- apply(as.data.frame(rgs), 1, paste0, collapse=":")
rownames(amp.gexp.prob) <- paste0('amp', names[vi1])
rownames(del.gexp.prob) <- paste0('del', names[vi2])
if(sum(vi2) > 1) {
del.gexp.prob <- del.gexp.prob[vi2, ]
rownames(del.gexp.prob) <- paste0("del", names[vi2])
colnames(del.gexp.prob) <- paste0("del.gexp.", colnames(del.gexp.prob))
} else if (sum(vi) == 1) {
del.gexp.prob <- t(del.gexp.prob[vi2, ])
rownames(del.gexp.prob) <- paste0("del", names[vi2])
colnames(del.gexp.prob) <- paste0("del.gexp.", colnames(del.gexp.prob))
} else {
del.gexp.prob <- c()
}

ret <- rbind(del.gexp.prob, amp.gexp.prob)
cnvs[['gene-based']][['amp']] <<- rgs[vi1]
cnvs[['gene-based']][['del']] <<- rgs[vi2]
summary[['gene-based']] <<- ret

colnames(amp.gexp.prob) <- paste0('amp.gexp.', colnames(amp.gexp.prob))
colnames(del.gexp.prob) <- paste0('del.gexp.', colnames(del.gexp.prob))
cnvs[["gene-based"]][["amp"]] <<- rgs[vi1]
cnvs[["gene-based"]][["del"]] <<- rgs[vi2]
summary[["gene-based"]] <<- ret

}
if(alleleBased & !geneBased) {
rgs <- cnvs[['allele-based']][['all']]
retest <- results[['allele-based']]

del.loh.allele.prob <- do.call(rbind, lapply(retest, function(x) x))
df <- cbind(as.data.frame(rgs), avg.del.loh.allele=rowMeans(del.loh.allele.prob), del.loh.allele.prob)
df <- cbind(as.data.frame(rgs),
avg.del.loh.allele=rowMeans(del.loh.allele.prob),
del.loh.allele.prob)

## filter to regions with at least some highly confident cells
vi1 <- rowSums(del.loh.allele.prob > t) > min.num.cells
del.loh.allele.prob <- del.loh.allele.prob[vi1,] ## amplifications

names <- apply(as.data.frame(rgs), 1, paste0, collapse=":")
rownames(del.loh.allele.prob) <- paste0('del.loh.', names[vi1])
if(sum(vi1) > 1) {
del.loh.allele.prob <- del.loh.allele.prob[vi1,]
rownames(del.loh.allele.prob) <- paste0('del.loh.', names[vi1])
colnames(del.loh.allele.prob) <- paste0('del.loh.allele.', colnames(del.loh.allele.prob))
} else if (sum(vi) == 1) {
del.loh.allele.prob <- t(del.loh.allele.prob[vi1,])
rownames(del.loh.allele.prob) <- paste0('del.loh.', names[vi1])
colnames(del.loh.allele.prob) <- paste0('del.loh.allele.', colnames(del.loh.allele.prob))
} else {
del.loh.allele.prob <- c()
}

cnvs[['allele-based']][['del.loh']] <<- rgs[vi1]
summary[['allele-based']] <<- del.loh.allele.prob

colnames(del.loh.allele.prob) <- paste0('del.loh.allele.', colnames(del.loh.allele.prob))
}
if(alleleBased & geneBased) {
rgs <- cnvs[['combine-based']][['all']]

retest <- results[['combine-based']]

amp.comb.prob <- do.call(rbind, lapply(retest, function(x) x[[1]]))
del.comb.prob <- do.call(rbind, lapply(retest, function(x) x[[2]]))

df <- cbind(as.data.frame(rgs), avg.amp.comb=rowMeans(amp.comb.prob), avg.del.comb=rowMeans(del.comb.prob), amp.comb.prob, del.comb.prob)

## filter to regions with at least some highly confident cells
df <- cbind(as.data.frame(rgs), avg.amp.comb = rowMeans(amp.comb.prob),
avg.del.comb = rowMeans(del.comb.prob), amp.comb.prob,
del.comb.prob)
names <- apply(as.data.frame(rgs), 1, paste0, collapse = ":")
vi1 <- rowSums(amp.comb.prob > t) > min.num.cells
amp.comb.prob <- amp.comb.prob[vi1,] ## amplifications
if(sum(vi1) > 1) {
amp.comb.prob <- amp.comb.prob[vi1, ]
rownames(amp.comb.prob) <- paste0("amp", names[vi1])
colnames(amp.comb.prob) <- paste0("amp.comb.", colnames(amp.comb.prob))
} else if (sum(vi) == 1) {
amp.comb.prob <- t(amp.comb.prob[vi1, ])
rownames(amp.comb.prob) <- paste0("amp", names[vi1])
colnames(amp.comb.prob) <- paste0("amp.comb.", colnames(amp.comb.prob))
} else {
amp.comb.prob <- c()
}
vi2 <- rowSums(del.comb.prob > t) > min.num.cells
del.comb.prob <- del.comb.prob[vi2,] ## amplifications

names <- apply(as.data.frame(rgs), 1, paste0, collapse=":")
rownames(amp.comb.prob) <- paste0('amp', names[vi1])
rownames(del.comb.prob) <- paste0('del', names[vi2])
if(sum(vi2) > 1) {
del.comb.prob <- del.comb.prob[vi2, ]
rownames(del.comb.prob) <- paste0("del", names[vi2])
colnames(del.comb.prob) <- paste0("del.comb.", colnames(del.comb.prob))
} else if (sum(vi) == 1) {
del.comb.prob <- t(del.comb.prob[vi2, ])
rownames(del.comb.prob) <- paste0("del", names[vi2])
colnames(del.comb.prob) <- paste0("del.comb.", colnames(del.comb.prob))
} else {
del.comb.prob <- c()
}

ret <- rbind(del.comb.prob, amp.comb.prob)

cnvs[['combine-based']][['amp']] <<- rgs[vi1]
cnvs[['combine-based']][['del']] <<- rgs[vi2]
summary[['combine-based']] <<- ret

colnames(amp.comb.prob) <- paste0('amp.comb.', colnames(amp.comb.prob))
colnames(del.comb.prob) <- paste0('del.comb.', colnames(del.comb.prob))
}
return(df)
}
Expand Down
11 changes: 6 additions & 5 deletions docs/Getting_Started.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,8 @@ data(gexp) ## tumor cells
data(ref) ## reference

require(biomaRt) ## for gene coordinates
mart.obj <- useMart(biomart = "ENSEMBL_MART_ENSEMBL", dataset = 'hsapiens_gene_ensembl', host = "jul2015.archive.ensembl.org")
#mart.obj <- useMart(biomart = "ENSEMBL_MART_ENSEMBL", dataset = 'hsapiens_gene_ensembl', host = "jul2015.archive.ensembl.org") ## version used in manuscript
mart.obj <- useMart(biomart = "ENSEMBL_MART_ENSEMBL", dataset = 'hsapiens_gene_ensembl') ## current version

print(gexp[1:5,1:5])
```
Expand Down Expand Up @@ -110,10 +111,10 @@ hb$calcGexpCnvBoundaries(init=TRUE, verbose=FALSE) ## HMM
```

```
## ERROR: Error: subscript contains invalid names
## ERROR: Error: subscript contains invalid names
## ERROR: Error: subscript contains invalid names
## ERROR: Error: subscript contains invalid names
Loading required package: rjags
Loading required package: coda
Linked to JAGS 4.3.0
Loaded modules: basemod,bugs
```

```r
Expand Down

0 comments on commit b3648e7

Please sign in to comment.