| ... | ... |
@@ -1,7 +1,7 @@ |
| 1 | 1 |
Package: scmeth |
| 2 | 2 |
Type: Package |
| 3 | 3 |
Title: Functions to conduct quality control analysis in methylation data |
| 4 |
-Version: 0.99.28 |
|
| 4 |
+Version: 0.99.29 |
|
| 5 | 5 |
Author: Divy Kangeyan <[email protected]> |
| 6 | 6 |
Maintainer: Divy Kangeyan <[email protected]> |
| 7 | 7 |
Depends: R (>= 3.5.0) |
| ... | ... |
@@ -17,7 +17,6 @@ import(DT) |
| 17 | 17 |
import(GenomicRanges) |
| 18 | 18 |
import(SummarizedExperiment) |
| 19 | 19 |
import(knitr) |
| 20 |
-import(magrittr) |
|
| 21 | 20 |
importFrom(Biostrings,DNAString) |
| 22 | 21 |
importFrom(Biostrings,vmatchPattern) |
| 23 | 22 |
importFrom(DelayedArray,colSums) |
| ... | ... |
@@ -30,9 +29,8 @@ importFrom(annotatr,builtin_genomes) |
| 30 | 29 |
importFrom(annotatr,summarize_annotations) |
| 31 | 30 |
importFrom(bsseq,getCoverage) |
| 32 | 31 |
importFrom(ggthemes,theme_tufte) |
| 33 |
-importFrom(plyr,ddply) |
|
| 34 |
-importFrom(plyr,summarise) |
|
| 35 | 32 |
importFrom(scales,comma) |
| 33 |
+importFrom(stats,aggregate) |
|
| 36 | 34 |
importFrom(stats,dbinom) |
| 37 | 35 |
importFrom(stats,relevel) |
| 38 | 36 |
importFrom(stats,sd) |
| ... | ... |
@@ -14,9 +14,7 @@ |
| 14 | 14 |
#'@importFrom utils read.table |
| 15 | 15 |
#'@importFrom utils read.csv |
| 16 | 16 |
#'@importFrom stats sd |
| 17 |
-#'@importFrom plyr summarise |
|
| 18 |
-#'@importFrom plyr ddply |
|
| 19 |
-#'@import magrittr |
|
| 17 |
+#'@importFrom stats aggregate |
|
| 20 | 18 |
#'@export |
| 21 | 19 |
|
| 22 | 20 |
mbiasplot <- function(dir=NULL,mbiasFiles=NULL){
|
| ... | ... |
@@ -59,9 +57,16 @@ mbiasplot <- function(dir=NULL,mbiasFiles=NULL){
|
| 59 | 57 |
id.vars=c('position', 'X..methylation', 'read'))
|
| 60 | 58 |
mt$read_rep <- paste(mt$read, mt$L1, sep="_") |
| 61 | 59 |
|
| 62 |
- sum_mt <- plyr::ddply(mt, c("position", "read"), plyr::summarise,
|
|
| 63 |
- meth = mean(X..methylation), sdMeth = sd(X..methylation), |
|
| 64 |
- seMeth = sd(X..methylation)/sqrt(length(X..methylation))) |
|
| 60 |
+ meanTable <- stats::aggregate( X..methylation ~ position+read, data=mt, FUN=mean) |
|
| 61 |
+ sdTable <- stats::aggregate( X..methylation ~ position+read, data=mt, FUN=sd) |
|
| 62 |
+ seTable <- stats::aggregate( X..methylation ~ position+read, data=mt, FUN=function(x){sd(x)/sqrt(length(x))})
|
|
| 63 |
+ |
|
| 64 |
+ sum_mt<-data.frame('position'=meanTable$position,'read'=meanTable$read,
|
|
| 65 |
+ 'meth'=meanTable$X..methylation, 'sdMeth'=sdTable$X..methylation, |
|
| 66 |
+ 'seMeth'=seTable$X..methylation) |
|
| 67 |
+ #sum_mt <- plyr::ddply(mt, .(position, read), plyr::summarise, |
|
| 68 |
+ #meth = mean(X..methylation), sdMeth = sd(X..methylation), |
|
| 69 |
+ #seMeth = sd(X..methylation)/sqrt(length(X..methylation))) |
|
| 65 | 70 |
#sum_mt <- mt %>% dplyr::group_by(position,read) %>% |
| 66 | 71 |
#dplyr::summarise(meth = mean(X..methylation), |
| 67 | 72 |
# sdMeth=stats::sd(X..methylation)) |
