https://github.com/bioconductor-source/seqcat
Science Score: 13.0%
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Low similarity (16.0%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: bioconductor-source
- License: other
- Language: R
- Default Branch: devel
- Size: 4.28 MB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Overview
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, i.e. output from variant callers such as the Genome Analysis ToolKit and annotated with software such as SnpEff.
Installation
The seqCAT package is available on both Bioconductor 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:
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 <- createprofile(vcf, "HCT116") hke3 <- createprofile(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
plotheatmap(comparisons[1])
```
<img src="man/figures/README
For more detailed instructions on how to use seqCAT, please see the
vignette.
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
Fasterius E. and Al-Khalili Szigyarto C.
F1000Research (2018), 7:1466
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.
Owner
- Name: (WIP DEV) Bioconductor Packages
- Login: bioconductor-source
- Kind: organization
- Email: maintainer@bioconductor.org
- Website: https://bioconductor.org
- Repositories: 1
- Profile: https://github.com/bioconductor-source
Source code for packages accepted into Bioconductor
GitHub Events
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Dependencies
- GenomicRanges >= 1.26.4 depends
- R >= 3.6 depends
- VariantAnnotation >= 1.20.3 depends
- GenomeInfoDb >= 1.13.4 imports
- IRanges >= 2.8.2 imports
- S4Vectors >= 0.12.2 imports
- SummarizedExperiment >= 1.4.0 imports
- dplyr >= 0.5.0 imports
- ggplot2 >= 2.2.1 imports
- grid >= 3.5.0 imports
- methods * imports
- rlang * imports
- rtracklayer * imports
- scales >= 0.4.1 imports
- stats * imports
- tidyr >= 0.6.1 imports
- utils * imports
- BiocManager * suggests
- BiocStyle * suggests
- knitr * suggests
- rmarkdown * suggests
- testthat * suggests