Update DESCRIPTION

DESCRIPTION

@@ -7,58 +7,31 @@ Maintainer: Dawit A. Yohannes <dawit.yohannes@helsinki.fi>
 URL: https://www.helsinki.fi/en/researchgroups/immunomics
 Title: Differential abundance Analysis for deep sequenced immune repertoire (Repseq) datasets
 Description: RepAn mainly performs differential abundance analysis by comparing immune repertoire
-    samples in two conditon groups to find condition associated CDR3 sequences. It conducts the comparison between sample groups 
+    samples in two condition groups to find condition associated CDR3 sequences. It conducts the comparison between sample groups 
     at population level at the level of sub-repertoires, which are clusters of CDR3s that have shared immuno-genomic features across samples. 
     RepAn also implements basic analysis functions for immune repertoire datasets.
 License: GPL-3
 Depends:
-    R (>= 2.15.1),
+    R (>= 2.15.1)
+Suggests:
     Matrix (>= 1.2-7.1),
     dynamicTreeCut,
     ggplot2 (>= 1.0.0),
     cluster (>= 2.0.5),
     Biostrings (>= 2.38.4),
-    RankProd (>= 2.42.0),
     doParallel (>= 1.0.10),
     parallel,
     preprocessCore (>= 1.32.0),
     randomForest (>= 4.6-12),
     gplots (>= 3.0.1),
-    wordspace (>= 0.2-0),
     e1071 (>= 1.6-7),
     data.table (>= 1.9.6),
-    gplots (>= 3.0.1),
-    kmer (>= 1.0.2),
-    dendextend (>= 1.3.0),
-    ape (>= 5.1),
-    RankProd,
-    preprocessCore,
-    ggseqlogo (>= 0.1),
-    fclust
-biocViews:
-Imports:
-    dynamicTreeCut,
-    ggplot2 (>= 1.0.0),
-    cluster (>= 2.0.5),
-    Biostrings (>= 2.38.4),
-    RankProd (>= 2.42.0),
-    doParallel (>= 1.0.10),
-    parallel,
-    preprocessCore (>= 1.32.0),
-    randomForest (>= 4.6-12),
-    gplots (>= 3.0.1),
-    wordspace (>= 0.2-0),
-    e1071 (>= 1.6-7),
-    data.table (>= 1.9.6),
-    gplots (>= 3.0.1),
     kmer (>= 1.0.2),
     dendextend (>= 1.3.0),
     ape (>= 5.1),
     RankProd,
-    preprocessCore,
     ggseqlogo (>= 0.1),
     fclust
 LazyData: true
 RoxygenNote: 6.1.0
 Encoding: UTF-8
-

NAMESPACE

@@ -1,18 +1,3 @@
 # Generated by roxygen2: do not edit by hand
 
 exportPattern("^[^\\.]")
-import(Matrix)
-import(cluster)
-import(kmer)
-import(wordspace)
-import(parallel)
-import(doParallel)
-import(gplots)
-import(ggplot2)
-importFrom(ape,as.AAbin)
-importFrom(fclust,SIL)
-importFrom(dynamicTreeCut,cutreeDynamic)
-importFrom(randomForest,randomForest)
-importFrom(randomForest,importance)
-importFrom(e1071,cmeans)
-importFrom(data.table,fread)

README.md

@@ -11,16 +11,9 @@ put through a ranking based filtering to identify the most likely condition asso
 For detailed description of the differential abundance analysis method, please see (https://doi.org/10.1186/s12859-021-04087-7)
 
 ## Installation
-To install RepAn package in R, first install R devtools package and run its install_github function as follows: 
-
-```
-install.packages("devtools")
-devtools::install_github("dyohanne/RepAn")
-```
-If installing R package dependencies with the previous command gives errors, first install RepAn without the dependencies and use the package installation functions that come with RepAn as follows:
-
+To install RepAn package in R, first install RepAn from the development branch without the dependencies and use the package installation functions that come with RepAn as follows:
 ```
-devtools::install_github("dyohanne/RepAn",dependencies=F)
+devtools::install_github("dyohanne/RepAn@development", dependencies = FALSE, upgrade = "never")
 loadPacks()
 loadBioconductorPacks()
 ```