A pipeline for integrative analysis for scTCR- and scRNA-seq data
Project description
immunopipe
Integrative analysis for scTCR- and scRNA-seq data
Requirements & Installation
-
python
:3.7+
- Other python depedencies should be installed via
pip install -U immunopipe
- Other python depedencies should be installed via
-
R
immunarch
(v0.6.7+
),Seurat
(v4.0+
),scImpute
,scran
,scater
dplyr
,tidyr
,tibble
,ggplot2
,ggradar
,ggprism
,ggrepel
,reshape2
ComplexHeatmap
,RColorBrewer
future
,parallel
,gtools
enrichR
-
Other
-
Checking requirements
pip install -U pipen-cli-require pipen require immunopipe.pipeline:pipeline <pipeline arguments>
Running as a container
Using docker:
docker run -w /workdir -v .:/workdir -it justold/immunopipe:dev
Using singularity:
singularity run -w \ # need it to be writable
-H /home/immunopipe_user \ # required, used to init conda
--pwd /workdir -B .:/workdir \ # Could use other directory instead of "."
# --contain: don't map host filesystem
# --cleanenv: recommended, to avoid other host's environment variables to be used
# For example, $CONDA_PREFIX to affect host's conda environment
--contain --cleanenv \
docker://justold/immunopipe:dev
# The mount your data directory to /mnt, which will make startup faster
# For example
# -B .:/workdir,/path/to/data:/mnt
# Where /path/to/data is the data directory containing the data files
# You may also want to bind other directories (i.e. /tmp)
# -B <other bindings>,/tmp
# Or you can pull the image first by:
singularity pull --force --dir images/ docker://justold/immunopipe:dev
# Then you can replace "docker://justold/immunopipe:dev" with "images/immunopipe.sif"
Modules
- Basic TCR data analysis using
immunarch
- Clone Residency analysis if you have paired samples (i.e. Tumor vs Normal)
- V-J usage, the frequency of various V-J junctions in circos-style plots
- Clustering cells and configurale arguments to separate T and non-T cells
- Clustering T cell, markers for each cluster and enrichment analysis for the markers
- Radar plots to show the composition of cells for clusters
- Markers finder for selected groups of cells
- Expression investigation of genes of interest for selected groups of cells
- UMAPs
- Metabolic landscape analysis (Ref: Xiao, Zhengtao, Ziwei Dai, and Jason W. Locasale. "Metabolic landscape of the tumor microenvironment at single cell resolution." Nature communications 10.1 (2019): 1-12.)
Documentaion
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
immunopipe-0.1.0.tar.gz
(24.9 kB
view hashes)
Built Distribution
immunopipe-0.1.0-py3-none-any.whl
(27.6 kB
view hashes)
Close
Hashes for immunopipe-0.1.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6b21121662f018e7200a7501a10a4a373a9a12867be02a2e788e20c3b63372b1 |
|
MD5 | bfff58454ba49008990275926ff847b8 |
|
BLAKE2b-256 | 9c9167eded47117c23a45a9bf2d4295b1ee292588520c8783ca6c61532d923e9 |