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Khodadadi-Jamayran
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README.md

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# iCellR
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iCellR is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq and CITE-seq).
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Link to Comprehensive R Archive Network [(CRAN)](https://cran.r-project.org/web/packages/iCellR/index.html)
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Link to manual: [Manual](https://cran.r-project.org/web/packages/iCellR/iCellR.pdf)
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Link to Comprehensive R Archive Network [(CRAN)](https://cran.r-project.org/web/packages/iCellR/index.html). Link to manual: [Manual](https://cran.r-project.org/web/packages/iCellR/iCellR.pdf)
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Link to a video tutorial for CITE-Seq and scRNA-Seq analysis: [Video](https://vimeo.com/337822487)
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For citation please use this link (our manuscript is in preparation): https://CRAN.R-project.org/package=iCellR
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For citation please use this link (our manuscript is in preparation): https://github.com/rezakj/iCellR
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iCellR publications: [PMID 31744829](https://pubmed.ncbi.nlm.nih.gov/31744829-in-vivo-epigenetic-crispr-screen-identifies-asf1a-as-an-immunotherapeutic-target-in-kras-mutant-lung-adenocarcinoma/?from_term=alireza+khodadadi-jamayran&from_filter=years.2019-2019&from_pos=5)
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If you are using FlowJo or SeqGeq, they have made plugins for iCellR and other single cell tools: https://www.flowjo.com/exchange/#/ (list of all plugins) and https://www.flowjo.com/exchange/#/plugin/profile?id=34 (iCellR plugin)
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Tutorials: [example 1 code](https://genome.med.nyu.edu/results/external/iCellR/example1/code.txt) and [results](https://genome.med.nyu.edu/results/external/iCellR/example1/)
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iCellR Viewer (web GUI app): https://compbio.nyumc.org/icellr/
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### Single (i) Cell R package (iCellR)
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<p align="center">
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# Install phateR version 2.9
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# wget https://cran.r-project.org/src/contrib/Archive/phateR/phateR_0.2.9.tar.gz
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# install.packages('phateR/', repos = NULL, type="source")
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# or
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# library(devtools)
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# install_version("phateR", version = "0.2.9", repos = "http://cran.us.r-project.org")
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# optional
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# library(phateR)
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type = "classic",
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clust.method = "complete")
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# New pseudotime maps coming soon see plots below
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pseudotime.tree(my.obj,
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marker.genes = MyGenes,
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type = "jitter",
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clust.method = "complete")
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```
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<p align="center">
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<img src="https://github.com/rezakj/scSeqR/blob/dev/doc/pseudotime.tree_unrooted.png" width="400" />
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<img src="https://github.com/rezakj/scSeqR/blob/dev/doc/pseudotime.tree_classic.png" width="400" />
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<img src="https://github.com/rezakj/scSeqR/blob/dev/doc/pseudotime.tree_jitter.png" width="400"/>
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<img src="https://github.com/rezakj/scSeqR/blob/master/doc/12_pseudotime.png"/>
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</p>
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