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iCellR
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", "1.6.7")
Attach the package and use:
library("iCellR")
Maintained by
Alireza Khodadadi-Jamayran
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.iCellR . https://github.com/rezakj/iCellR/issues . https://github.com/rezakj/iCellR . iCellR citation info . iCellR results . iCellR.pdf . iCellR_1.6.7.tar.gz . iCellR_1.6.7.zip . iCellR_1.6.7.zip . iCellR_1.6.7.zip . iCellR_1.6.7.tgz . iCellR_1.6.7.tgz . iCellR_1.6.7.tgz . iCellR_1.6.7.tgz . iCellR_1.6.7.tgz . iCellR_1.6.7.tgz . iCellR archive . https://CRAN.R-project.org/package=iCellR .
First Published: 2019-08-02
Latest Update: 2021-10-09
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 1.6.7, https://cran.r-project.org/web/packages/iCellR. Accessed 01 Apr. 2025.
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)
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
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