<p align="center"> <img src="man/figures/README_seqCAT_logo.png" width="400", alt="seqCAT"/> </p> ## Overview [![Anaconda Cloud version][1]][2] [![License: MIT][3]][4] [![Build status][5]][6] [![Coverage Status][7]][8] The High Throughput Sequencing Cell Authentication Toolkit (**seqCAT**) is an R-package for authenticating, evaluating and characterisation of cells using *single nucleotide variants* (SNVs) from sequencing data. Its input data should be on the form of [VCF files][9], *i.e.* output from variant callers such as the [Genome Analysis ToolKit][10] and annotated with software such as [SnpEff][11]. ## Installation The `seqCAT` package is available on both [Bioconductor][12] and here on GitHub. You can install the latest, stable version from Bioconductor like so: ```r # install.packages("BiocManager") BiocManager::install("seqCAT") ``` If you are interested in the development version of `seqCAT`, you can install it from GitHub: ```r # install.packages("devtools") devtools::install_github("fasterius/seqCAT") ``` You may also install `seqCAT` using [Conda][13]: ```bash conda install -c bioconda bioconductor-seqcat ``` To list the versions of `seqCAT` available on Conda, you can use the `search` functionality: ```bash conda search -c bioconda bioconductor-seqcat ``` ## Usage The general workflow of `seqCAT` consists of three steps: 1. Creation of SNV profiles 2. Comparisons of SNV profiles 3. Evaluation of profile comparisons ```r # Load the package library("seqCAT") # Path to the example VCF file vcf <- system.file("extdata", "example.vcf.gz", package = "seqCAT") # Create SNV profiles hct116 <- create_profile(vcf, "HCT116") hke3 <- create_profile(vcf, "HKE3") rko <- create_profile(vcf, "RKO") # Compare all profiles to each other profiles <- list(hct116, hke3, rko) comparisons <- compare_many(profiles) # Create an heatmap of comparisons and their similarity scores plot_heatmap(comparisons[[1]]) ``` <p align="center"> <img src="man/figures/README_example_1.png", alt="Example heatmap"/> </p> For more detailed instructions on how to use `seqCAT`, please see the [vignette][14]. ## Citation If you are using `seqCAT` to analyse your data, please cite the following article: > **seqCAT: a Bioconductor R-package for variant analysis of high throughput** > **sequencing data** > <br/> Fasterius E. and Al-Khalili Szigyarto C. > <br/> *F1000Research* (2018), 7:1466 > <br/> https://f1000research.com/articles/7-1466 ## License The `seqCAT` package is released with a MIT licence and is a free software: you may redistribute and/or modify it under the terms of the license. For more information, please see the `LICENCE` file. [1]: https://anaconda.org/bioconda/bioconductor-seqcat/badges/version.svg [2]: https://anaconda.org/bioconda/bioconductor-seqcat [3]: https://img.shields.io/badge/License-MIT-blue.svg [4]: https://opensource.org/licenses/MIT [5]: https://travis-ci.org/fasterius/seqCAT.svg?branch=master [6]: https://travis-ci.org/fasterius/seqCAT [7]: https://coveralls.io/repos/github/fasterius/seqCAT/badge.svg?branch=master [8]: https://coveralls.io/github/fasterius/seqCAT?branch=master [9]: http://www.internationalgenome.org/wiki/Analysis/variant-call-format [10]: https://software.broadinstitute.org/gatk/ [11]: http://snpeff.sourceforge.net/ [12]: https://bioconductor.org/packages/release/bioc/html/seqCAT.html [13]: https://conda.io/en/latest/ [14]: https://bioconductor.org/packages/release/bioc/vignettes/seqCAT/inst/doc/seqCAT.html