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README.md
# **factR v.1** ## Functional Annotation of Custom Transcriptomes in R <!-- badges: start --> [![R build status](https://github.com/fursham-h/factR/workflows/R-CMD-check/badge.svg)](https://github.com/fursham-h/factR/actions) [![Codecov test coverage](https://github.com/fursham-h/factR/workflows/test-coverage/badge.svg)](https://github.com/fursham-h/factR/actions) [![Codecov test coverage](https://codecov.io/gh/fursham-h/factR/branch/master/graph/badge.svg)](https://app.codecov.io/gh/fursham-h/factR?branch=master) <!-- badges: end --> ## General workflow <p align="center"> <img src="man/figures/factR_workflow.png" width="450"/> </p> *factR* is a robust and easy-to-use R package with tools to process custom-assembled transcriptomes (GTF). Below are *factR*'s key functions: * Core features 1. Construct transcript coding (CDS) information using a reference-guided process 2. Predict protein domains on coding transcripts 3. Predict sensitivity of coding transcripts to Nonsense-mediated decay * Supporting features 1. Match chromosome levels of query GTF/object to reference annotation 2. Match gene_id and gene_names of query GTF to reference annotation 3. Plot transcripts from GTF GRanges object using *wiggleplotr* 4. Subset new transcripts from custom transcriptome ## How to install The latest stable version can be installed directly from [Bioconductor](): ```r if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install("factR") ``` Alternatively, you may install the development version of *factR* using devtools: ```r # install.packages("devtools") devtools::install_github("fursham-h/factR") ``` ## Getting started See our [quickstart guide](https://fursham-h.github.io/factR/articles/quickstart.html) or our [full vignette](https://fursham-h.github.io/factR/articles/factR.html) on how to get started ## Acknowledgements We thank [Kaur Alasoo](https://github.com/kauralasoo) for sharing code resources for *wiggleplotr* and for valuable discussions on the design of the package. ## Citing factR Please cite the following references if you use factR: 1. Fursham Hamid, Kaur Alasoo, Jaak Vilo, Eugene Makeyev (2022); Functional annotation of custom transcriptomes; Methods in Molecular Biology 2. [Fursham Hamid (2022); Functional Annotation of Custom Transcriptomes; Bioconductor](https://bioconductor.org/packages/devel/bioc/html/factR.html )