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Package: iCellR | ||
Type: Package | ||
Title: Analyzing High-Throughput Single Cell Sequencing Data | ||
Version: 1.6.4 | ||
Version: 1.6.5 | ||
Authors@R: c( | ||
person(given = 'Alireza', family = 'Khodadadi-Jamayran',role = c('aut','cre'), email = '[email protected]', comment = c(ORCID = '0000-0003-2495-7504')), | ||
person(given = 'Joseph', family = 'Pucella',role = c('aut','ctb'), comment = c(ORCID = '0000-0003-0875-8046')), | ||
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@@ -27,7 +27,7 @@ RoxygenNote: 7.1.1 | |
BugReports: https://github.com/rezakj/iCellR/issues | ||
URL: https://github.com/rezakj/iCellR | ||
NeedsCompilation: yes | ||
Packaged: 2021-06-07 15:57:39 UTC; khodaa01 | ||
Packaged: 2021-10-07 18:26:50 UTC; khodaa01 | ||
Author: Alireza Khodadadi-Jamayran [aut, cre] | ||
(<https://orcid.org/0000-0003-2495-7504>), | ||
Joseph Pucella [aut, ctb] (<https://orcid.org/0000-0003-0875-8046>), | ||
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@@ -13,17 +13,6 @@ | |
#' @param filter.by.gene A character vector of gene names to be filtered by thier expression. If more then one gene is defined it would be OR not AND. | ||
#' @param filter.by.gene.exp.min Minimum gene expression to be filtered by the genes set in filter.by.gene, default = 1. | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' demo.obj <- cell.filter(demo.obj, | ||
#' min.mito = 0, | ||
#' max.mito = 0.05 , | ||
#' min.genes = 100, | ||
#' max.genes = 2500, | ||
#' min.umis = 0, | ||
#' max.umis = Inf) | ||
#' | ||
#' message([email protected]) | ||
#' | ||
#' @export | ||
cell.filter <- function (x = NULL, | ||
min.mito = 0, | ||
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@@ -3,11 +3,6 @@ | |
#' This function takes an object of class iCellR and scales the normalized data. | ||
#' @param x An object of class iCellR. | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' my.obj <- data.scale(demo.obj) | ||
#' | ||
#' head([email protected])[1:5] | ||
#' | ||
#' @export | ||
data.scale <- function (x = NULL) { | ||
if ("iCellR" != class(x)[1]) { | ||
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#' @param which.data Choose from "raw.data" or "main.data", default = "raw.data". | ||
#' @param each.cond If TRUE each condition will be calculated, default = FALSE. | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' demo.obj <- gene.stats(demo.obj, which.data = "main.data") | ||
#' head([email protected]) | ||
#' | ||
#' @export | ||
gene.stats <- function (x = NULL, | ||
which.data = "raw.data", | ||
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#' @param interactive If set to TRUE an interactive HTML file will be created, default = TRUE. | ||
#' @param out.name If "interactive" is set to TRUE, the out put name for HTML, default = "plot". | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' make.gene.model(demo.obj, | ||
#' dispersion.limit = 1.5, | ||
#' base.mean.rank = 500, | ||
#' no.mito.model = TRUE, | ||
#' mark.mito = TRUE, | ||
#' interactive = FALSE, | ||
#' my.out.put = "plot", | ||
#' out.name = "gene.model") | ||
#' | ||
#' demo.obj <- make.gene.model(demo.obj, | ||
#' dispersion.limit = 1.5, | ||
#' base.mean.rank = 500, | ||
#' no.mito.model = TRUE, | ||
#' mark.mito = TRUE, | ||
#' interactive = FALSE, | ||
#' out.name = "gene.model") | ||
#' | ||
#' head([email protected]) | ||
#' | ||
#' @import ggrepel | ||
#' @export | ||
make.gene.model <- function (x = NULL, | ||
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#' @param gene.list A charactor vector of genes to be used for PCA. If "clust.method" is set to "gene.model", default = "my_model_genes.txt". | ||
#' @param scale.data If TRUE the data will be scaled (log2 + plus.log.value), default = TRUE. | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' demo.obj <- run.pca(demo.obj, method = "gene.model", gene.list = [email protected]) | ||
#' | ||
#' head([email protected])[1:5] | ||
#' | ||
#' @export | ||
run.pca <- function (x = NULL, | ||
data.type = "main", | ||
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@@ -6,12 +6,6 @@ | |
#' @param top.pos Number of top positive marker genes to be taken from each PC, default = 15. | ||
#' @param top.neg Number of top negative marker genes to be taken from each PC, default = 5. | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' | ||
#' demo.obj <- find.dim.genes(demo.obj, dims = 1:10,top.pos = 20, top.neg = 20) | ||
#' | ||
#' head([email protected]) | ||
#' | ||
#' @export | ||
find.dim.genes <- function (x = NULL, | ||
dims = 1:10, | ||
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#' @param min.clust minimum number of clusters, default = 2. | ||
#' @param dims PCA dimentions to be use for clustering, default = 1:10. | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' demo.obj <- run.clustering(demo.obj, | ||
#' clust.method = "kmeans", | ||
#' dist.method = "euclidean", | ||
#' index.method = "silhouette", | ||
#' max.clust = 2, | ||
#' min.clust = 2, | ||
#' dims = 1:10) | ||
#' | ||
#' head([email protected]) | ||
#' | ||
#' @import NbClust | ||
#' @export | ||
run.clustering <- function (x = NULL, | ||
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#' @param eta numeric; Learning rate (default: 200.0) | ||
#' @param exaggeration_factor numeric; Exaggeration factor used to multiply the P matrix in the first part of the optimization (default: 12.0) | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' demo.obj <- run.pc.tsne(demo.obj, dims = 1:10,perplexity = 20) | ||
#' | ||
#' head([email protected])[1:5] | ||
#' | ||
#' @import Rtsne | ||
#' @export | ||
run.pc.tsne <- function (x = NULL, | ||
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@@ -286,10 +286,6 @@ | |
#' @param verbose If \code{TRUE}, log details to the console. | ||
#' | ||
#' @return An object of class iCellR. | ||
#' @examples | ||
#' demo.obj <- run.umap(demo.obj, dims = 1:10) | ||
#' head([email protected]) | ||
#' | ||
#' @import uwot | ||
#' @export | ||
run.umap <- function (x = NULL, | ||
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