Merge pull request #38 from spriyansh/main

CPU Core Setting, logo, website, patchwork to ggpubr

.gitignore

@@ -8,4 +8,5 @@ inst/doc
 /doc/
 /Meta/
 .Rbuildignore
-test_dev
+test_dev
+docs

DESCRIPTION

@@ -30,7 +30,7 @@ Suggests:
     BiocStyle,
     ComplexUpset,
     UpSetR,
-    patchwork
+    ggpubr
 Config/testthat/edition: 3
 URL: https://github.com/BioBam/scMaSigPro/
 biocViews: Clustering, Regression, TimeCourse, DifferentialExpression,

R/plotIntersect.R

@@ -7,7 +7,7 @@
 #' @importFrom S4Vectors isEmpty
 #' @importFrom RColorConesa colorConesa
 #' @importFrom utils packageVersion
-#' 
+#'
 #' @param scmpObj An object of class \code{\link{ScMaSigPro}}.
 #' @param min_intersection_size Minimal number of observations in an intersection
 #' for it to be included.

R/sc.p.vector.R

@@ -25,6 +25,8 @@
 #' @param max_it Maximum number of iterations to fit the model.
 #' @param parallel Use forking process to run parallelly. (Default is FALSE)
 #' (Currently, Windows is not supported)
+#' @param n_cores Explicitly specify the number of cores to use for parallel model
+#' fitting. (Default is inferred from the system using availableCores()-2)
 #' @param verbose Print detailed output in the console. (Default is TRUE)
 #'
 #' @return An object of class \code{\link{ScMaSigPro}}, with updated `Profile`
@@ -48,6 +50,7 @@ sc.p.vector <- function(scmpObj, p_value = 0.05, mt_correction = "BH",
                         verbose = TRUE,
                         offset = TRUE,
                         parallel = FALSE,
+                        n_cores = availableCores() - 2,
                         log_offset = FALSE,
                         max_it = 100,
                         link = "log") {
@@ -106,12 +109,6 @@ sc.p.vector <- function(scmpObj, p_value = 0.05, mt_correction = "BH",
   p <- dim(dis)[2]
   sc.p.vector <- vector(mode = "numeric", length = g)
 
-  if (parallel == FALSE) {
-    if (verbose) {
-      pb <- txtProgressBar(min = 0, max = g, style = 3)
-    }
-  }
-
   # Calculate  offset
   if (offset) {
     dat <- dat + 1
@@ -130,13 +127,21 @@ sc.p.vector <- function(scmpObj, p_value = 0.05, mt_correction = "BH",
       numCores <- 1
       warning("Currently, we only support sequential processing on windows based systems...")
     } else {
-      numCores <- availableCores() - 1
+      n_cores <- as.integer(n_cores)
+      # Check Required Cores
+      assert_that(n_cores <= availableCores(),
+        msg = paste("Number of cores requested is invalid. This session has access to", as.integer(availableCores()), "cores only.")
+      )
+      numCores <- n_cores
     }
     if (verbose) {
       message(paste("Running with", numCores, "cores..."))
     }
   } else {
     numCores <- 1
+    if (verbose) {
+      pb <- txtProgressBar(min = 0, max = g, style = 3)
+    }
   }
 
   # Check for weight usage

R/sc.t.fit.R

@@ -22,6 +22,8 @@
 #' @param max_it Maximum number of iterations to fit the model.
 #' @param parallel Use forking process to run parallelly. (Default is FALSE)
 #' (Currently, Windows is not supported)
+#' @param n_cores Explicitly specify the number of cores to use for parallel model
+#' fitting. (Default is inferred from the system using availableCores()-2)
 #' @param verbose Print detailed output in the console. (Default is TRUE)
 #'
 #' @return An object of class \code{\link{ScMaSigPro}}, with updated `Estimate`
@@ -47,6 +49,7 @@ sc.t.fit <- function(scmpObj,
                      offset = scmpObj@Parameters@offset,
                      verbose = TRUE,
                      parallel = FALSE,
+                     n_cores = availableCores() - 2,
                      log_offset = scmpObj@Parameters@log_offset,
                      max_it = scmpObj@Parameters@max_it,
                      link = scmpObj@Parameters@link) {
@@ -137,7 +140,12 @@ sc.t.fit <- function(scmpObj,
       numCores <- 1
       warning("Currently, we only support sequential processing on windows based systems...")
     } else {
-      numCores <- availableCores() - 1
+      n_cores <- as.integer(n_cores)
+      # Check Required Cores
+      assert_that(n_cores <= availableCores(),
+        msg = paste("Number of cores requested is invalid. This session has access to", as.integer(availableCores()), "cores only.")
+      )
+      numCores <- n_cores
     }
     if (verbose) {
       message(paste("Running with", numCores, "cores..."))

README.md

@@ -1,8 +1,9 @@
-# ScMaSigPro
+<img src="man/figures/logo.png" alt="scMaSigPro Logo" width="17%"/>
 
-Implementation of MaSigPro for scRNA-Seq Data
+### Implementation of MaSigPro for scRNA-Seq Data.
 
- [![R-CMD-Check](https://github.com/BioBam/scMaSigPro/actions/workflows/r.yml/badge.svg?branch=main)](https://github.com/BioBam/scMaSigPro/actions/workflows/r.yml)   [![test-coverage](https://github.com/BioBam/scMaSigPro/actions/workflows/test-coverage.yaml/badge.svg?branch=main)](https://github.com/BioBam/scMaSigPro/actions/workflows/test-coverage.yaml)
+[![R-CMD-Check](https://github.com/BioBam/scMaSigPro/actions/workflows/r.yml/badge.svg?branch=main)](https://github.com/BioBam/scMaSigPro/actions/workflows/r.yml)
+[![test-coverage](https://github.com/BioBam/scMaSigPro/actions/workflows/test-coverage.yaml/badge.svg?branch=main)](https://github.com/BioBam/scMaSigPro/actions/workflows/test-coverage.yaml)
 
 ---
 

_pkgdown.yml

@@ -0,0 +1,5 @@
+url: https://github.com/BioBam/scMaSigPro
+logo: man/figures/logo.png
+template:
+  bootstrap: 5
+

vignettes/Basic-Workflow.Rmd

@@ -319,7 +319,7 @@ By setting the vars parameter to "groups", the function will add genes with
 $R^2$ >= 0.7 to the object. To explore the number of genes per group, we will 
 make an upset plot:
 ```{r, "uspet",eval=TRUE, echo=TRUE, fig.width=8, fig.height=6}
-plotIntersect(scmp_ob, package = "ComplexUpset")
+plotIntersect(scmp_ob, package = "UpSetR")
 ```
 
 Here, we observe that 23 genes belong to both Path2vsPath1 and Path1, indicating
@@ -333,7 +333,10 @@ FigureA <- plotTrend(scmp_ob, "Gene9", logs = TRUE, logType = "log")
 FigureB <- plotTrend(scmp_ob, "Gene95", logs = TRUE, logType = "log")
 FigureC <- plotTrend(scmp_ob, "Gene10", logs = TRUE, logType = "log")
 FigureD <- plotTrend(scmp_ob, "Gene92", logs = TRUE, logType = "log")
-(FigureA + FigureB) / (FigureC + FigureD)
+ggpubr::ggarrange(FigureA, FigureB, FigureC, FigureD,
+  ncol = 2, nrow = 2,
+  labels = c("A", "B", "C", "D")
+)
 ```
 
 These plots illustrate the gene expression trends for selected genes, providing

vignettes/scMaSigPro-Class.Rmd

@@ -246,7 +246,9 @@ for (i in rownames(head(pTime_up, 4))) {
 }
 
 # Plot combined
-(pTime_up.plots[[1]] + pTime_up.plots[[2]]) / (pTime_up.plots[[3]] + pTime_up.plots[[4]])
+ggpubr::ggarrange(pTime_up.plots[[1]], pTime_up.plots[[2]], pTime_up.plots[[3]], pTime_up.plots[[4]],
+  ncol = 2, nrow = 2, labels = c("A", "B", "C", "D")
+)
 ```
 
 ```{r, "Pseudotime_path"}
@@ -272,7 +274,7 @@ for (i in rownames(head(pTime_path_up, 4))) {
 }
 
 # Plot combined
-(pTime_path_up.plots[[1]] + pTime_path_up.plots[[2]]) / (pTime_path_up.plots[[3]] + pTime_path_up.plots[[4]])
+ggpubr::ggarrange(pTime_path_up.plots[[1]], pTime_path_up.plots[[2]], pTime_path_up.plots[[3]], pTime_path_up.plots[[4]], ncol = 2, nrow = 2, labels = c("A", "B", "C", "D"))
 ```
 
 ```{r, echo=FALSE}