Code used to generate interactive t-SNE plots using RNA-Seq counts data.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
To get started, you'll want to have Python 3 and R 3.6.1.
conda create -n itsne-dev \
-c conda-forge \
-c bioconda \
r-base=3.6.1 \
python=3.7 \
logzero \
numpy \
pandas \
scikit-learn \
bioconductor-biocinstaller \
bioconductor-sva \
bioconductor-deseq2 \
r-tsne r-getopt r-plotly r-optparse r-rtsne r-pracma r-data.table -y
conda activate itsne-devAlternatively, you can install the anaconda dependencies directly from the environment.yml file.
conda env create -f environment.ymlFirst, the author recommends you run the following command line script to ensure all R packages are loaded before your first run:
Rscript scripts/itsne-normalize-matrix.RFrom here, you can install the python package:
python3 setup.py installDownload the relevant gene model:
curl ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_31/gencode.v31.annotation.gtf.gz -o gencode.v31.annotation.gtf.gzAnd try out the script:
itsne-main counts/* \
-b reference/gene.excludelist.tsv \
-c reference/covariates.tsv \
-g gencode.v31.annotation.gtf.gz \
-o tsne.htmlNo tests currently exist. If and when tests are added, the authors will fill in this section.
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
We use SemVer for versioning. For the versions available, see the tags on this repository.
This project is licensed under the MIT License - see the LICENSE.md file for details