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+
dplyr
tidyr
tibble
ggplot2
ggradar
ggprism
ggrepel
future
parallel
enrichR
ComplexHeatmap
-
Other
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-0.0.3.tar.gz
(19.6 kB
view hashes)
Built Distribution
immunopipe-0.0.3-py3-none-any.whl
(21.2 kB
view hashes)
Close
Hashes for immunopipe-0.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c4c3fe028e6dbb7d3596cd38b19900e5a3ca417012f41f9d848a235616c87410 |
|
MD5 | 0b5d9becd7021529a77b36fa0ccac404 |
|
BLAKE2b-256 | 8ff6bd42a55ace95696d237897345ccb6121870414a7218debbd1ccd77f7d154 |