Merge pull request #154 from neurogenomics/fix-mouse-support

Fix support for mouse genome [HOTFIX]

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: EpiCompare
 Title: Comparison, Benchmarking & QC of Epigenomic Datasets
-Version: 1.9.10
+Version: 1.10.1
 Authors@R: c(
     person(given = "Sera", family = "Choi", 
         email = "[email protected]", 

NEWS.md

@@ -1,3 +1,15 @@
+## CHANGES IN VERSION 1.10.1 [HOTFIX]
+
+### Bug Fixes
+
+* `prepare_output_build`
+  - Fix support for mouse genome builds (mm9 and mm10).
+
+### Documentation
+
+* `Epicompare.Rmd`
+  - Mention support for mouse genome builds.
+
 ## CHANGES IN VERSION 1.9.5
 
 ### New features

R/EpiCompare.R

@@ -11,7 +11,7 @@
 #' and paths.Files must be listed and named using \code{list()}.
 #' E.g. \code{list("name1"=file1, "name2"=file2)}. If no names are specified,
 #' default file names will be assigned.
-#' @param genome_build A named list indicating the human genome build used to
+#' @param genome_build A named list indicating the genome build used to
 #' generate each of the following inputs:
 #' \itemize{
 #' \item{"peakfiles" : }{Genome build for the \code{peakfiles} input.
@@ -27,10 +27,12 @@
 #' This should \emph{only} be done in situations where all three inputs
 #' (\code{peakfiles}, \code{reference}, \code{blacklist}) are of the same
 #' genome build. For example:\cr
-#' \code{genome_build = "hg19"}
+#' \code{genome_build = "hg19"}\cr\cr
+#' Supported genome builds are: "hg19", "hg38", "mm9" and "mm10".
 #' @param genome_build_output Genome build to standardise all inputs to.
 #' Liftovers will be performed automatically as needed.
-#' Default: "hg19".
+#' Default: "hg19".\cr\cr
+#' \strong{Note:} Cross-species liftovers are supported.
 #' @param blacklist A \link[GenomicRanges]{GRanges} object
 #'  containing blacklisted genomic regions.
 #' Blacklists included in \pkg{EpiCompare} are:

R/prepare_output_build.R

@@ -1,9 +1,10 @@
 prepare_output_build <- function(genome_build_output){
-    opts <- c("hg19","hg38")
+    opts <- c("hg19","hg38","mm9","mm10")
     if(is.null(genome_build_output) ||
        missing(genome_build_output) ||
        (!tolower(genome_build_output) %in% opts)){
-        stop("Must provide valid genome_build_output: 'hg19' or 'hg38'")
+        stop("Must provide valid genome_build_output: ",
+        "'hg19', 'hg38', 'mm9', or 'mm10'")
     }
     return(tolower(genome_build_output)[[1]])
 }

README.md

@@ -1,15 +1,15 @@
 ⚖<code>EpiCompare</code>⚖<br>QC and Benchmarking of Epigenomic Datasets
 ================
 <img src='https://github.com/neurogenomics/EpiCompare/raw/master/inst/hex/hex.png' title='Hex sticker for EpiCompare' height='300'><br>
-[![](https://img.shields.io/badge/release%20version-1.9.3-green.svg)](https://www.bioconductor.org/packages/EpiCompare)
-[![](https://img.shields.io/badge/download-27/month-green.svg)](https://bioconductor.org/packages/stats/bioc/EpiCompare)
-[![](https://img.shields.io/badge/download-1266/total-green.svg)](https://bioconductor.org/packages/stats/bioc/EpiCompare)
+[![](https://img.shields.io/badge/release%20version-1.10.0-green.svg)](https://www.bioconductor.org/packages/EpiCompare)
+[![](https://img.shields.io/badge/download-47/month-green.svg)](https://bioconductor.org/packages/stats/bioc/EpiCompare)
+[![](https://img.shields.io/badge/download-1451/total-green.svg)](https://bioconductor.org/packages/stats/bioc/EpiCompare)
 [![download](http://www.bioconductor.org/shields/downloads/release/EpiCompare.svg)](https://bioconductor.org/packages/stats/bioc/EpiCompare)
 [![License:
 GPL-3](https://img.shields.io/badge/license-GPL--3-blue.svg)](https://cran.r-project.org/web/licenses/GPL-3)
 [![](https://img.shields.io/badge/doi-https://doi.org/10.1101/2022.07.22.501149-blue.svg)](https://doi.org/https://doi.org/10.1101/2022.07.22.501149)
 <br>
-[![](https://img.shields.io/badge/devel%20version-1.9.10-black.svg)](https://github.com/neurogenomics/EpiCompare)
+[![](https://img.shields.io/badge/devel%20version-1.10.1-black.svg)](https://github.com/neurogenomics/EpiCompare)
 [![](https://img.shields.io/github/languages/code-size/neurogenomics/EpiCompare.svg)](https://github.com/neurogenomics/EpiCompare)
 [![](https://img.shields.io/github/last-commit/neurogenomics/EpiCompare.svg)](https://github.com/neurogenomics/EpiCompare/commits/master)
 <br> [![R build
@@ -22,7 +22,7 @@ Authors: <i>Sera Choi, Brian Schilder, Leyla Abbasova, Alan Murphy,
 Nathan Skene, Thomas Roberts, Hiranyamaya Dash</i>  
 </h4>
 <h5>  
-<i>Updated</i>: Oct-18-2024  
+<i>Updated</i>: Jan-15-2025  
 </h5>
 
 # Introduction
@@ -384,9 +384,9 @@ Imperial College London
 utils::sessionInfo()
 ```
 
-    ## R version 4.4.1 (2024-06-14)
+    ## R version 4.4.2 (2024-10-31)
     ## Platform: aarch64-apple-darwin20
-    ## Running under: macOS 15.0.1
+    ## Running under: macOS Sequoia 15.2
     ## 
     ## Matrix products: default
     ## BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
@@ -402,22 +402,21 @@ utils::sessionInfo()
     ## [1] stats     graphics  grDevices utils     datasets  methods   base     
     ## 
     ## loaded via a namespace (and not attached):
-    ##  [1] gtable_0.3.5        jsonlite_1.8.9      renv_1.0.11        
-    ##  [4] dplyr_1.1.4         compiler_4.4.1      BiocManager_1.30.25
+    ##  [1] gtable_0.3.6        jsonlite_1.8.9      renv_1.0.11        
+    ##  [4] dplyr_1.1.4         compiler_4.4.2      BiocManager_1.30.25
     ##  [7] tidyselect_1.2.1    rvcheck_0.2.1       scales_1.3.0       
     ## [10] yaml_2.3.10         fastmap_1.2.0       here_1.0.1         
     ## [13] ggplot2_3.5.1       R6_2.5.1            generics_0.1.3     
-    ## [16] knitr_1.48          yulab.utils_0.1.7   tibble_3.2.1       
-    ## [19] desc_1.4.3          dlstats_0.1.7       rprojroot_2.0.4    
-    ## [22] munsell_0.5.1       pillar_1.9.0        RColorBrewer_1.1-3 
-    ## [25] rlang_1.1.4         utf8_1.2.4          badger_0.2.4       
-    ## [28] xfun_0.48           fs_1.6.4            cli_3.6.3          
-    ## [31] magrittr_2.0.3      rworkflows_1.0.2    digest_0.6.37      
-    ## [34] grid_4.4.1          rstudioapi_0.16.0   lifecycle_1.0.4    
-    ## [37] vctrs_0.6.5         evaluate_1.0.1      glue_1.8.0         
-    ## [40] data.table_1.16.2   fansi_1.0.6         colorspace_2.1-1   
-    ## [43] rmarkdown_2.28      tools_4.4.1         pkgconfig_2.0.3    
-    ## [46] htmltools_0.5.8.1
+    ## [16] knitr_1.49          yulab.utils_0.1.9   tibble_3.2.1       
+    ## [19] desc_1.4.3          dlstats_0.1.7       munsell_0.5.1      
+    ## [22] rprojroot_2.0.4     pillar_1.10.1       RColorBrewer_1.1-3 
+    ## [25] rlang_1.1.4         badger_0.2.4        xfun_0.50          
+    ## [28] fs_1.6.5            cli_3.6.3           magrittr_2.0.3     
+    ## [31] rworkflows_1.0.3    digest_0.6.37       grid_4.4.2         
+    ## [34] rstudioapi_0.17.1   lifecycle_1.0.4     vctrs_0.6.5        
+    ## [37] evaluate_1.0.1      glue_1.8.0          data.table_1.16.4  
+    ## [40] colorspace_2.1-1    rmarkdown_2.29      tools_4.4.2        
+    ## [43] pkgconfig_2.0.3     htmltools_0.5.8.1
 
 </details>
 

inst/markdown/EpiCompare.Rmd

@@ -82,7 +82,7 @@ if(params$save_output){
 # or... genome_build <- "hg19"
 builds <- prepare_genome_builds(genome_build = params$genome_build,
                                 blacklist = params$blacklist)
-## Standardise all data to hg19 build 
+## Standardise all data to specified build 
 output_build <- prepare_output_build(params$genome_build_output)
 
 #### ------ Prepare peaklist(s) ------ ####

vignettes/EpiCompare.Rmd

@@ -46,8 +46,8 @@ experimental conditions and data analysis workflows of one technology. This
 can help researchers to establish a consensus regarding the optimal use of the 
 method. 
 
-Currently, *EpiCompare* only works for human genome as it uses human-based 
-hg19 and/or hg38 genome references. 
+Currently, *EpiCompare* supports human and mouse genomes (hg19, hg38, mm9 and
+mm10).
 
 # Data