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<img src="inst/www/eisaR.png" align="right" alt="" width="120" /> # `eisaR`: Exon-Intron Split Analysis (EISA) in R <br> ## Overview Exon-intron split analysis (`EISA`) uses ordinary RNA-seq data to measure changes in mature RNA and pre-mRNA reads across different experimental conditions to quantify transcriptional and post-transcriptional regulation of gene expression. For details see Gaidatzis et al., Nat Biotechnol 2015. doi: 10.1038/nbt.3269. `eisaR` implements the major steps of EISA in R. In addition, it contains functionality for extracting spliced and unspliced transcript sequences, as well as intron sequences (with similar options as the [BUSpaRse]( package), from an annotated genome. These sequences can be indexed and used, e.g., for quantification in preparation for RNA velocity estimation. Developed by: - [Michael Stadler]( - Dimos Gaidatzis - [Lukas Burger]( - [Charlotte Soneson]( Also a big "thank you" for contributions to: - [Federico Marini]( ## Installation To install `eisaR` from Bioconductor, you will need at least R 4.0 and Bioconductor 3.11, which is available on April 28, 2020. Then use the following within R (see also [eisaR download page]( ``` # BiocManager is needed to install Bioconductor packages if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") # Install eisaR BiocManager::install("eisaR") ``` ## Functionality All you need is RNA-seq data from at least two conditions (e.g. wildtype and mutant). The `eisaR` package contains convenience functions to facilitate the steps in an exon-intron split analysis, which consists of: 1. preparing the annotation (exonic and gene body coordinate ranges) 2. quantifying RNA-seq alignments in exons and introns 3. calculating and comparing exonic and intronic changes across conditions 4. visualizing the results For the steps 1. and 2. above, this `eisaR` vignette makes use of Bioconductor annotation and the [QuasR]( package. It is also possible to obtain count tables for exons and introns using some other pipeline or approach, and directly start with step 3. ## Reference `EISA` has been described in: "Analysis of intronic and exonic reads in RNA-seq data characterizes transcriptional and post-transcriptional regulation." Gaidatzis D., Burger L., Florescu M. and Stadler, M.B. *Nat Biotechnol.* **2015**; 33(7):722-9. [PubMed: 26098447](, [doi: 10.1038/nbt.3269]( The functionality for extracting spliced and unspliced transcript sequences, as well as intron sequences, for use in RNA velocity analysis, has been described in: "Preprocessing choices affect RNA velocity results for droplet scRNA-seq data." Soneson C., Srivastava A., Patro R. and Stadler, M.B. *PLoS Comput Biol* **2021**; 17(1):e1008585. [PubMed: 33428615](, [doi: 10.1371/journal.pcbi.1008585]( ## Software status | Platforms | OS | R CMD check | Coverage | |:----------------:|:----------------:|:----------------:|:----------------:| | GitHub Actions | Linux/Windows/macOS | [![R build status](]( | [![ coverage status](]( | | Bioc ([_devel_]( | Multiple | [![Bioconductor-devel Build Status](]( | [![ coverage status](]( | | Bioc ([_release_]( | Multiple | [![Bioconductor-release Build Status](]( | [![ coverage status](]( |