Analysis of adaptive immune receptor repertoires (2016) course slides and notes.
Cloning this repository
This repository contains large sequence and tabular files stored using Git-LFS, which can be installed from here.
lfs subcommand is installed, the repository can be cloned as follows.
git lfs clone https://github.com/antibodyome/aairr16
You will need to have the following installed on your computer:
- Python 3
Entrez Direct, or EDirect, allows programmatic access to NCBI. It is available for download from ftp://ftp.ncbi.nlm.nih.gov/entrez/entrezdirect/.
The SRA Toolkit from NCBI allows downloading of datasets from NCBI SRA to FASTQ files stored locally. It can be downloaded from https://github.com/ncbi/sra-tools/wiki/Downloads.
IgBLAST compares reassorted BCR/TCR sequences against a germline database using a modified version of BLAST. It is available from ftp://ftp.ncbi.nih.gov/blast/executables/igblast/release/.
vdjtools analyses CDR3 regions, and is well suited for TCR analyses. Installation instructions can be found at http://vdjtools-doc.readthedocs.io/en/latest/install.html.
dnapars from the phylip suite of programs is used for inference of lineage trees in the R library alakazam. It can be downloaded from http://evolution.genetics.washington.edu/phylip.html, but is also available from package managers.
This course makes heavy use of Jupyter notebooks. You will need to install Jupyter e.g.
pip3 install notebook
The slides make use of the RISE extension:
pip3 install RISE jupyter-nbextension install rise --py --sys-prefix jupyter-nbextension enable rise --py --sys-prefix
--sys-prefix can be replaced by
--system depending on the type of installation desired.
Depending on taste, you may prefer to use a bash kernel for some tasks.
pip3 install bash_kernel python3 -m bash_kernel.install
In addition, the following packages are required (and can be installed using
Whilst not a package, but rather a set of Python scripts, @williamdlees TRIgS will be used as a simple interface to analyse immunoglobulin sequences:
In addition, an R kernel for Jupyter is also required. In R:
install.packages(c('repr', 'IRdisplay', 'crayon', 'pbdZMQ', 'devtools')) devtools::install_github('IRkernel/IRkernel') IRkernel::installspec() # to register the kernel in the current R installation