Update examples, fix global variable warnings.

.github/workflows/check-bioc.yaml

@@ -305,7 +305,7 @@ jobs:
 
       - name: Upload check results
         if: failure()
-        uses: actions/upload-artifact@devel
+        uses: actions/upload-artifact@master
         with:
           name: ${{ runner.os }}-biocversion-RELEASE_3_18-r-4.3-results
           path: check

DESCRIPTION

@@ -39,7 +39,8 @@ Imports:
     mixtools,
     sparseMatrixStats,
     stats,
-    tidyr
+    tidyr,
+    utils
 Suggests: 
     BiocStyle,
     dbscan,

NAMESPACE

@@ -20,3 +20,7 @@ import(graphics)
 import(methods)
 import(stats)
 importClassesFrom(Matrix,dgCMatrix)
+importFrom(SummarizedExperiment,SummarizedExperiment)
+importFrom(SummarizedExperiment,assay)
+importFrom(utils,globalVariables)
+importFrom(utils,stack)

R/AllGenerics.R

@@ -91,14 +91,16 @@ setGeneric(
 #' @param data an expression object, can be matrix or SummarizedExperiment
 #' @param slot a character, specify which slot to use when data is se object,
 #'             optional, default 'score'
+#' @param suffix a character, specify the name suffix to save score when
+#'               features is a named list
 #'
 #' @return A vector of overall score for each sample
 #'
 #' @include score.R
 #' @export
 #'
 #' @examples
-#' data <- matrix(rnorm(100), 10, dimnames = list(seq_len(3)))
+#' data <- matrix(rnorm(100), 10, dimnames = list(seq_len(10)))
 #' gs_score(data, features = seq_len(3))
 setGeneric(
   "gs_score",

R/plot.R

@@ -175,3 +175,5 @@ score_barplot <- function(top_markers, column = ".dot", f_list, n = 30) {
     theme_classic()
 }
 
+utils::globalVariables(c("Group", "Score", "x", "Scores", "Comp",
+                         "..density..", "stack", "values", "ind", "Type"))

R/score.R

@@ -57,7 +57,9 @@ idf_iae_methods <- function() {
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' cal_score_init(data, label = sample(c("A", "B"), 10, replace = TRUE))
+#' label <- sample(c("A", "B"), 10, replace = TRUE)
+#' smartid:::cal_score_init(data, par.idf = list(label = label),
+#'                          par.iae = list(label = label))
 cal_score_init <- function(expr, tf = c("logtf", "tf"),
                            idf = "prob", iae = "prob",
                            par.idf = NULL, par.iae = NULL) {

R/smartid-package.R

@@ -2,6 +2,8 @@
 #' @import methods
 #' @import stats
 #' @import graphics
+#' @importFrom SummarizedExperiment SummarizedExperiment assay
+#' @importFrom utils globalVariables stack
 #' @importClassesFrom Matrix dgCMatrix
 NULL
 

R/tf_idf_iae_wrappers.R

@@ -12,7 +12,7 @@
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' tf(data)
+#' smartid:::tf(data)
 tf <- function(expr, log = FALSE) {
   t.f <- sweep(expr, 2, colSums(expr, na.rm = TRUE) + 0.01, FUN = "/")
   if(log) {
@@ -40,7 +40,7 @@ tf <- function(expr, log = FALSE) {
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' idf(data)
+#' smartid:::idf(data)
 idf <- function(expr, features = NULL, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
   n_obs <- ncol(expr)  ## number of total obs
@@ -65,7 +65,7 @@ idf <- function(expr, features = NULL, thres = 0) {
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' idf_m(data)
+#' smartid:::idf_m(data)
 idf_m <- function(expr, features = NULL, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
   n_obs <- ncol(expr)  ## number of total obs
@@ -95,7 +95,7 @@ idf_m <- function(expr, features = NULL, thres = 0) {
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' idf_sd(data)
+#' smartid:::idf_sd(data)
 idf_sd <- function(expr, features = NULL, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
   n_obs <- ncol(expr)  ## number of total obs
@@ -120,8 +120,9 @@ idf_sd <- function(expr, features = NULL, thres = 0) {
 #' @return a matrix of IDF score
 #'
 #' @examples
+#' set.seed(123)
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' idf_hdb(data)
+#' smartid:::idf_hdb(data)
 idf_hdb <- function(expr, features = NULL, multi = TRUE,
                     thres = 0, minPts = 2, ...) {
   if(is.null(features)) features <- seq_len(nrow(expr))
@@ -159,7 +160,7 @@ idf_hdb <- function(expr, features = NULL, multi = TRUE,
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' idf_rf(data, label = sample(c("A", "B"), 10, replace = TRUE))
+#' smartid:::idf_rf(data, label = sample(c("A", "B"), 10, replace = TRUE))
 idf_rf <- function(expr, features = NULL, label,
                    multi = TRUE, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
@@ -202,7 +203,7 @@ idf_rf <- function(expr, features = NULL, label,
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' idf_prob(data, label = sample(c("A", "B"), 10, replace = TRUE))
+#' smartid:::idf_prob(data, label = sample(c("A", "B"), 10, replace = TRUE))
 idf_prob <- function(expr, features = NULL, label,
                      multi = TRUE, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
@@ -246,7 +247,7 @@ idf_prob <- function(expr, features = NULL, label,
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' idf_igm(data, label = sample(c("A", "B"), 10, replace = TRUE))
+#' smartid:::idf_igm(data, label = sample(c("A", "B"), 10, replace = TRUE))
 idf_igm <- function(expr, features = NULL, label, lambda = 7, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
 
@@ -284,7 +285,7 @@ idf_igm <- function(expr, features = NULL, label, lambda = 7, thres = 0) {
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' iae(data)
+#' smartid:::iae(data)
 iae <- function(expr, features = NULL, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
   n_obs <- ncol(expr)  ## number of total obs
@@ -311,7 +312,7 @@ iae <- function(expr, features = NULL, thres = 0) {
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' iae_m(data)
+#' smartid:::iae_m(data)
 iae_m <- function(expr, features = NULL, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
   n_obs <- ncol(expr)  ## number of total obs
@@ -342,7 +343,7 @@ iae_m <- function(expr, features = NULL, thres = 0) {
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' iae_sd(data)
+#' smartid:::iae_sd(data)
 iae_sd <- function(expr, features = NULL, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
   n_obs <- ncol(expr)  ## number of obs
@@ -369,8 +370,9 @@ iae_sd <- function(expr, features = NULL, thres = 0) {
 #' @return a matrix of IAE score
 #'
 #' @examples
+#' set.seed(123)
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' iae_hdb(data)
+#' smartid:::iae_hdb(data)
 iae_hdb <- function(expr, features = NULL, multi = TRUE,
                     thres = 0, minPts = 2, ...) {
   if(is.null(features)) features <- seq_len(nrow(expr))
@@ -420,7 +422,7 @@ iae_hdb <- function(expr, features = NULL, multi = TRUE,
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' iae_rf(data, label = sample(c("A", "B"), 10, replace = TRUE))
+#' smartid:::iae_rf(data, label = sample(c("A", "B"), 10, replace = TRUE))
 iae_rf <- function(expr, features = NULL, label,
                    multi = TRUE, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
@@ -463,7 +465,7 @@ iae_rf <- function(expr, features = NULL, label,
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' iae_prob(data, label = sample(c("A", "B"), 10, replace = TRUE))
+#' smartid:::iae_prob(data, label = sample(c("A", "B"), 10, replace = TRUE))
 iae_prob <- function(expr, features = NULL, label,
                      multi = TRUE, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
@@ -506,7 +508,7 @@ iae_prob <- function(expr, features = NULL, label,
 #'
 #' @examples
 #' data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
-#' iae_igm(data, label = sample(c("A", "B"), 10, replace = TRUE))
+#' smartid:::iae_igm(data, label = sample(c("A", "B"), 10, replace = TRUE))
 iae_igm <- function(expr, features = NULL, label, lambda = 7, thres = 0) {
   if(is.null(features)) features <- seq_len(nrow(expr))
 

R/top_markers.R

@@ -2,7 +2,7 @@
 #'
 #' @inheritParams top_markers_abs
 #' @inheritParams top_markers_glm
-#' @param use_glm logical, if to use [stats::glm()] to compute group mean score,
+#' @param use.glm logical, if to use [stats::glm()] to compute group mean score,
 #'                if TRUE, also compute mean score difference as output
 #' @param ... params for [top_markers_abs()] or [top_markers_glm()]
 #'
@@ -190,3 +190,4 @@ softmax <- function(x, tau = 1) {
 ## tanh: [-1, 1], similar to sigmoid, no need to sum 1
 tanh <- function(x) 2 / (1 + exp(-2*x)) - 1
 
+utils::globalVariables(c(".dot", "Scores"))