Other packages > Find by keyword >

iCellR  

Analyzing High-Throughput Single Cell Sequencing Data
View on CRAN: Click here


Download and install iCellR package within the R console
Install from CRAN:
install.packages("iCellR")

Install from Github:
library("remotes")
install_github("cran/iCellR")

Install by package version:
library("remotes")
install_version("iCellR", "1.7.0")



Attach the package and use:
library("iCellR")
Maintained by
Alireza Khodadadi-Jamayran
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-02
Latest Update: 2025-09-03
Description:
A toolkit that allows scientists to work with data from single cell sequencing technologies such as scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST). Single (i) Cell R package ('iCellR') provides unprecedented flexibility at every step of the analysis pipeline, including normalization, clustering, dimensionality reduction, imputation, visualization, and so on. Users can design both unsupervised and supervised models to best suit their research. In addition, the toolkit provides 2D and 3D interactive visualizations, differential expression analysis, filters based on cells, genes and clusters, data merging, normalizing for dropouts, data imputation methods, correcting for batch differences, pathway analysis, tools to find marker genes for clusters and conditions, predict cell types and pseudotime analysis. See Khodadadi-Jamayran, et al (2020) and Khodadadi-Jamayran, et al (2020) for more details.
How to cite:
Alireza Khodadadi-Jamayran (2019). iCellR: Analyzing High-Throughput Single Cell Sequencing Data. R package version 1.7.0, https://cran.r-project.org/web/packages/iCellR. Accessed 06 Jun. 2026.
Previous versions and publish date:
1.0.0 (2019-08-02 12:50), 1.1.2 (2019-09-10 21:20), 1.1.4 (2019-09-26 19:30), 1.2.0 (2019-10-15 07:20), 1.2.2 (2019-10-22 23:00), 1.2.5 (2019-11-04 23:00), 1.2.7 (2019-12-04 20:50), 1.2.9 (2020-01-17 00:10), 1.3.0 (2020-01-24 22:50), 1.3.1 (2020-02-26 13:50), 1.3.3 (2020-03-14 18:00), 1.4.0 (2020-04-03 16:10), 1.4.5 (2020-04-10 09:20), 1.5.0 (2020-05-08 10:40), 1.5.1 (2020-06-17 11:40), 1.5.4 (2020-07-03 18:30), 1.5.5 (2020-07-16 23:20), 1.5.8 (2020-10-09 06:40), 1.5.9 (2021-01-21 06:30), 1.6.0 (2021-01-30 07:00), 1.6.1 (2021-03-04 06:20), 1.6.4 (2021-04-27 19:10), 1.6.5 (2021-10-09 17:00), 1.6.7 (2024-01-29 21:20)
Other packages that cited iCellR R package
View iCellR citation profile
Other R packages that iCellR depends, imports, suggests or enhances
Complete documentation for iCellR
Functions, R codes and Examples using the iCellR R package
Some associated functions: Rphenograph . add.10x.image . add.adt . add.vdj . adt.rna.merge . bubble.gg.plot . capture.image.10x . cc . cell.cycle . cell.filter . cell.gating . cell.type.pred . change.clust . clono.plot . clust.avg.exp . clust.cond.info . clust.ord . clust.rm . clust.stats.plot . cluster.plot . data.aggregation . data.scale . down.sample . find.dim.genes . findMarkers . find_neighbors . g2m.phase . gate.to.clust . gene.plot . gene.stats . gg.cor . heatmap.gg.plot . hto.anno . i.score . iba . iclust . load.h5 . load10x . make.bed . make.gene.model . makej . myImp . norm.adt . norm.data . opt.pcs.plot . prep.vdj . pseudotime.knetl . pseudotime . pseudotime.tree . qc.stats . run.anchor . run.cca . run.clustering . run.diff.exp . run.diffusion.map . run.impute . run.knetl . run.mnn . run.pc.tsne . run.pca . run.phenograph . run.tsne . run.umap . s.phase . spatial.plot . stats.plot . top.markers . vdj.stats . volcano.ma.plot . 
Some associated R codes: F0001.R . F0002.R . F0003.R . F0004.R . F0005.R . F0006.R . F0007.R . F0008.R . F0009.R . F0010.R . F0011.R . F0012.R . F0013.R . F0014.R . F0015.R . F0016.R . F0017.R . F0018.R . F0019.R . F0020.R . F0021.R . F0022.R . F0023.R . F0024.R . F0025.R . F0026.R . F0027.R . F0028.R . F0029.R . F0030.R . F0031.R . F0032.R . F0033.R . F0034.R . F0035.R . F0036.R . F0037.R . F0038.R . F0039.R . F0040.R . F0041.R . F0042.R . F0043.R . F0044.R . F0045.R . F0046.R . F0047.R . F0048.R . F0049.R . F0050.R . F0051.R . F0052.R . F0053.R . F0054.R . F0055.R . F0057.R . F0058.R . F0059.R . F0060.R . F0061.R . F0062.R . F0063.R . F0064.R . F0065.R . F0066.R . F0067.R . F0068.R . F0069.R . F0070.R . F0071.R . F0072.R . F0100.R . RcppExports.R .  Full iCellR package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

BALLI  
Expression RNA-Seq Data Analysis Based on Linear Mixed Model
Analysis of gene expression RNA-seq data using Bartlett-Adjusted Likelihood-based LInear model (BALL ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
IAPWS95  
Thermophysical Properties of Water and Steam
An implementation of the International Association for the Properties of Water (IAPWS) Formulation ...
Download / Learn more Package Citations See dependency  
odbc  
Connect to ODBC Compatible Databases (using the DBI Interface)
A DBI-compatible interface to ODBC databases. ...
Download / Learn more Package Citations See dependency  
worrrd  
Generate Wordsearch and Crossword Puzzles
Generate wordsearch and crossword puzzles using custom lists of words (and clues).Make them easy or ...
Download / Learn more Package Citations See dependency  
rwavelet  
Wavelet Analysis
Perform wavelet analysis (orthogonal,translation invariant, tensorial, 1-2-3d transforms, thresholdi ...
Download / Learn more Package Citations See dependency  

27,268

R Packages

233,548

Dependencies

72,820

Author Associations

27,205

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA