Updating version to match Bioconductor

.github/workflows/BioC-check.yaml

@@ -27,17 +27,18 @@ jobs:
     steps:
       - uses: actions/checkout@v2
 
-      - uses: r-lib/actions/setup-pandoc@v1
+      - uses: r-lib/actions/setup-pandoc@v2
 
-      - uses: r-lib/actions/setup-r@v1
+      - uses: r-lib/actions/setup-r@v2
         with:
           r-version: ${{ matrix.config.r }}
           http-user-agent: ${{ matrix.config.http-user-agent }}
           use-public-rspm: true
 
-      - uses: r-lib/actions/setup-r-dependencies@v1
+      - uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          extra-packages: rcmdcheck
+          extra-packages: |
+            any::rcmdcheck
 
       - name: Install XQuartz on macOS
         if: runner.os == 'macOS'

.github/workflows/check-standard.yaml

@@ -27,11 +27,11 @@ jobs:
       R_KEEP_PKG_SOURCE: yes
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v2 
 
-      - uses: r-lib/actions/setup-pandoc@v1
+      - uses: r-lib/actions/setup-pandoc@v2
 
-      - uses: r-lib/actions/setup-r@v1
+      - uses: r-lib/actions/setup-r@v2
         with:
           r-version: ${{ matrix.config.r }}
           http-user-agent: ${{ matrix.config.http-user-agent }}
@@ -45,12 +45,14 @@ jobs:
         if: runner.os == 'macOS'
         run: brew install fftw
 
-      - uses: r-lib/actions/setup-r-dependencies@v1
+      - uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          extra-packages: rcmdcheck, tinytex
+          extra-packages: |
+            any::rcmdcheck
+            any::tinytex
 
-      - uses: r-lib/actions/setup-tinytex@v1
-      - uses: r-lib/actions/check-r-package@v1
+      - uses: r-lib/actions/setup-tinytex@v2
+      - uses: r-lib/actions/check-r-package@v2
 
       - name: Show testthat output
         if: always()

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: celda
 Title: CEllular Latent Dirichlet Allocation
-Version: 1.12.0
+Version: 1.14.2
 Authors@R: c(person("Joshua", "Campbell", email = "camp@bu.edu",
     role = c("aut", "cre")),
     person("Shiyi", "Yang", email="syyang@bu.edu", role = c("aut")),
@@ -30,7 +30,7 @@ LinkingTo: Rcpp, RcppEigen
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.1
 BugReports: https://github.com/campbio/celda/issues
-biocViews: SingleCell, GeneExpression, Clustering, Sequencing, Bayesian
+biocViews: SingleCell, GeneExpression, Clustering, Sequencing, Bayesian, ImmunoOncology, DataImport
 NeedsCompilation: yes

NEWS.md

@@ -1,3 +1,10 @@
+# celda v1.14.2 (2023-01-19)
+* Update to match Bioconductor release version
+
+# celda v1.13.0 (2022-10-20)
+* Bug fixes related to cluster labels stored as factors and plotting
+* Updated sparse matrix conversion to work with Matrix v1.4-2
+
 # celda v1.12.0 (2022-04-30)
 * Update to match Bioconductor 3.15 release version
 
@@ -11,18 +18,15 @@
 * Added ability to use batch parameter with the raw matrix in decontX
 
 # celda v1.10.0 (2021-12-28)
-
 * Update to match Bioconductor release version
 
 # celda v1.9.3 (2021-10-04)
-
 * Fixed bug in checking background matrix with decontX
 * Switched to using Github Actions for Continuous Integration
 * Fixed plotting bugs in celda results reports
 * Speed up final step in decontX when creating final decontaminated matrix
 
 # celda v1.9.2 (2021-07-19)
-
 * Added a `NEWS.md` file to track changes to the package.
 * Added new tutorials and documentation generated with pkgdown.
 * Removed warnings in plotRPC functions.
@@ -31,54 +35,41 @@
 * Several improvements to plotting functions. 
 
 # celda v1.7.7 (2021-04-12):
-
 * Added handling for sparse matrices
 
 # celda v1.7.6 (2021-04-04):
-
 * Added functions for creating HTML reports
 * Fixed bug in decontX plotting
 
 # celda v1.7.4 (2021-03-09):
-
 * Enable input of raw/droplet matrix into decontX to estimate ambient RNA
 
 # celda v1.1.6 (2019-07-16):
-
 * Add multiclass decision tree
 
 # celda v1.1.4 (2019-05-28):
-
 * Add Alternate headings support for plotDimReduceFeature
 
 # celda v1.1.3 (2019-05-14):
-
 * Add multiclass decision tree (MCDT) cell cluster annotation
 
 # celda v1.1.2 (2019-05-14):
-
 * Fix a bug in celdaHeatmap
 
 # celda v1.0.1 (2019-05-09):
-
 * Default seed setting to maintain reproducibility
 
 # celda v0.99.34 (2019-04-23):
-
 * Minor changes to the vignettes
 
 # celda v0.99.23 (2019-04-10):
-
 * Remove pheatmap import
 
 # celda v0.99.22 (2019-04-09):
-
 * Package celda, for bi-clustering of single-cell 'omics data.
 
 # celda v0.99.8 (2019-03-11):
-
 * Second submission to Bioconductor
 
 # celda v0.99.0 (2018-05-15):
-
 * First submission to Bioconductor

R/celda_C.R

@@ -188,7 +188,7 @@ setMethod("celda_C",
         verbose = TRUE) {
 
         # Convert to sparse matrix
-        x <- methods::as(x, "dgCMatrix")
+        x <- methods::as(x, "CsparseMatrix")
 
         ls <- list()
         ls[[useAssay]] <- x

R/celda_CG.R

@@ -222,7 +222,7 @@ setMethod("celda_CG",
         verbose = TRUE) {
 
         # Convert to sparse matrix
-        x <- methods::as(x, "dgCMatrix")
+        x <- methods::as(x, "CsparseMatrix")
 
         ls <- list()
         ls[[useAssay]] <- x

R/celda_G.R

@@ -172,7 +172,7 @@ setMethod("celda_G",
         verbose = TRUE) {
 
         # Convert to sparse matrix
-        x <- methods::as(x, "dgCMatrix")
+        x <- methods::as(x, "CsparseMatrix")
 
         ls <- list()
         ls[[useAssay]] <- x

R/celda_functions.R

@@ -162,9 +162,9 @@ recodeClusterZ <- function(sce, from, to, altExpName = "featureSubset") {
         stop("Provided 'sce' argument does not have a 'celda_cell_cluster'",
             " column in 'colData(altExp(sce, altExpName))'")
     }
-    new.clusters <- plyr::mapvalues(celdaClusters(sce,
-                                                  altExpName = altExpName),
-                                    from, to)
+    z <- as.integer(celdaClusters(sce, altExpName = altExpName))
+    new.clusters <- plyr::mapvalues(z,
+                                    from = from, to = to)
     new.clusters <- factor(new.clusters, levels =
                              sort(as.numeric(unique(new.clusters))))
 
@@ -181,8 +181,12 @@ recodeClusterZ <- function(sce, from, to, altExpName = "featureSubset") {
     if (is.null(celdaClusters(celdaMod)$z)) {
         stop("Provided celdaMod argument does not have a z attribute")
     }
-    celdaMod@clusters$z <- plyr::mapvalues(celdaClusters(celdaMod)$z,
-        from, to)
+    z <- as.integer(celdaClusters(celdaMod)$z)
+    new.clusters <- plyr::mapvalues(z, from = from, to = to)
+    new.clusters <- factor(new.clusters, levels =
+                             sort(as.numeric(unique(new.clusters))))
+
+    celdaMod@clusters$z <- new.clusters
     return(celdaMod)
 }
 
@@ -215,14 +219,12 @@ recodeClusterY <- function(sce, from, to, altExpName = "featureSubset") {
         stop("Provided 'sce' argument does not have a 'celda_feature_module'",
             " column in 'rowData(altExp(sce, altExpName))'")
     }
-    new.clusters <- plyr::mapvalues(celdaModules(sce,
-                                                  altExpName = altExpName),
-                                  from, to)
+    y <- as.integer(celdaModules(sce, altExpName = altExpName))
+    new.clusters <- plyr::mapvalues(y, from = from, to = to)
     new.clusters <- factor(new.clusters, levels =
                              sort(as.numeric(unique(new.clusters))))
-
-    celdaModules(sce, altExpName = altExpName) <- plyr::mapvalues(
-        celdaModules(sce, altExpName = altExpName), from, to)
+
+    celdaModules(sce, altExpName = altExpName) <- new.clusters
     return(sce)
 }
 
@@ -235,8 +237,13 @@ recodeClusterY <- function(sce, from, to, altExpName = "featureSubset") {
     if (is.null(celdaClusters(celdaMod)$y)) {
         stop("Provided celdaMod argument does not have a y attribute")
     }
-    celdaMod@clusters$y <- plyr::mapvalues(celdaClusters(celdaMod)$y,
-        from, to)
+    y <- as.integer(celdaClusters(celdaMod)$y)
+
+    new.clusters <- plyr::mapvalues(y, from = from, to = to)
+    new.clusters <- factor(new.clusters, levels =
+                             sort(as.numeric(unique(new.clusters))))
+
+    celdaMod@clusters$y <- new.clusters
     return(celdaMod)
 }
 

R/decon.R

@@ -493,11 +493,11 @@ setMethod(
         append = TRUE,
         verbose = verbose
       )
-      countsBat <- methods::as(countsBat, "dgCMatrix")
+      countsBat <- methods::as(countsBat, "CsparseMatrix")
     }
     if (!is.null(bgBat)) {
       if (!inherits(bgBat, "dgCMatrix")) {
-        bgBat <- methods::as(bgBat, "dgCMatrix")
+        bgBat <- methods::as(bgBat, "CsparseMatrix")
       }
     }
 

R/factorizeMatrix.R

@@ -152,8 +152,8 @@ setMethod("factorizeMatrix", signature(x = "ANY", celdaMod = "celda_CG"),
         counts <- .processCounts(x)
         compareCountMatrix(counts, celdaMod)
 
-        z <- celdaClusters(celdaMod)$z
-        y <- celdaClusters(celdaMod)$y
+        z <- as.integer(celdaClusters(celdaMod)$z)
+        y <- as.integer(celdaClusters(celdaMod)$y)
         # Sometimes, fewer clusters get returned by celda_C/G
         # Taking the max(z)/max(y) rather than
         # the original K/L will prevent errors
@@ -318,7 +318,7 @@ setMethod("factorizeMatrix", signature(x = "ANY", celdaMod = "celda_C"),
         counts <- .processCounts(x)
         compareCountMatrix(counts, celdaMod)
 
-        z <- celdaClusters(celdaMod)$z
+        z <- as.integer(celdaClusters(celdaMod)$z)
         # Sometimes, fewer clusters get returned by celda_C
         # Taking the max(z) rather than the
         # original K will prevent errors
@@ -430,7 +430,7 @@ setMethod("factorizeMatrix", signature(x = "ANY", celdaMod = "celda_G"),
         counts <- .processCounts(x)
         compareCountMatrix(counts, celdaMod)
 
-        y <- celdaClusters(celdaMod)$y
+        y <- as.integer(celdaClusters(celdaMod)$y)
         # Sometimes, fewer clusters get returned by celda_G
         # Taking the max(y) rather than the original
         # L will prevent errors

R/loglikelihood.R

@@ -85,7 +85,7 @@ setMethod("logLikelihood", signature(x = "SingleCellExperiment"),
 setMethod("logLikelihood", signature(x = "matrix", celdaMod = "celda_C"),
     function(x, celdaMod) {
         sampleLabel <- sampleLabel(celdaMod)
-        z <- celdaClusters(celdaMod)$z
+        z <- as.integer(celdaClusters(celdaMod)$z)
         K <- params(celdaMod)$K
         alpha <- params(celdaMod)$alpha
         beta <- params(celdaMod)$beta
@@ -105,7 +105,7 @@ setMethod("logLikelihood", signature(x = "matrix", celdaMod = "celda_C"),
 #' @export
 setMethod("logLikelihood", signature(x = "matrix", celdaMod = "celda_G"),
     function(x, celdaMod) {
-        y <- celdaClusters(celdaMod)$y
+        y <- as.integer(celdaClusters(celdaMod)$y)
         L <- params(celdaMod)$L
         beta <- params(celdaMod)$beta
         delta <- params(celdaMod)$delta
@@ -127,8 +127,8 @@ setMethod("logLikelihood", signature(x = "matrix", celdaMod = "celda_G"),
 setMethod("logLikelihood", signature(x = "matrix", celdaMod = "celda_CG"),
     function(x, celdaMod) {
         sampleLabel <- sampleLabel(celdaMod)
-        z <- celdaClusters(celdaMod)$z
-        y <- celdaClusters(celdaMod)$y
+        z <- as.integer(celdaClusters(celdaMod)$z)
+        y <- as.integer(celdaClusters(celdaMod)$y)
         K <- params(celdaMod)$K
         L <- params(celdaMod)$L
         alpha <- params(celdaMod)$alpha