Single Cell analysis tools

1. Scanpy [ python ]

- Github : https://github.com/theislab/scanpy

- Paper : https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1382-0

- Tutorial

: https://scanpy.readthedocs.io/en/stable/tutorials.html

: https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/scrna-scanpy-pbmc3k/tutorial.html

 

# https://docs.conda.io/en/latest/miniconda.html
cd DOWNLOAD_DIR
chmod +x Miniconda3-latest-VERSION.sh
./Miniconda3-latest-VERSION.sh

conda install seaborn scikit-learn statsmodels numba pytables
conda install -c conda-forge python-igraph leidenalg

pip3 install scanpy

 

 

2. Seurat [ R ]

- Home : https://satijalab.org/seurat/

- Github : https://github.com/satijalab/seurat

- Paper : https://doi.org/10.1016/j.cell.2021.04.048

- Tutorial : https://satijalab.org/seurat/articles/pbmc3k_tutorial.html

 

sudo apt-get install gfortran libcurl4-openssl-dev libssl-dev libxml2-dev cmake liblapack-dev libblas-dev libboost-dev libpng-dev build-essential libcurl4-gnutls-dev

# tutorial_data
wget https://s3-us-west-2.amazonaws.com/10x.files/samples/cell/pbmc3k/pbmc3k_filtered_gene_bc_matrices.tar.gz

install.packages("usethis")
install.packages("devtools")
devtools::install_github("thomasp85/patchwork")
install.packages("Seurat")

- Patchwork : https://github.com/thomasp85/patchwork

 

 

 

 

3. SCDE [ R ]

- Home : http://hms-dbmi.github.io/scde/index.html

- Tutorial : http://hms-dbmi.github.io/scde/tutorials.html

 

 

wget https://github.com/hms-dbmi/scde/archive/1.99.1.tar.gz

R CMD INSTALL 1.9.1.tar.gz

require(devtools)
devtools::install_version('flexmix', '2.3-13')
devtools::install_github('hms-dbmi/scde', build_vignettes = FALSE)

 

 

4. scvi-tools [ python ]

- Github : https://github.com/YosefLab/scvi-tools

 

 

pip3 install scvi-tools

 

 

 

For Trajectories and Velocity estimation,

 

Monocle3

 

destiny

 

Wishbone

 

PAGA

 

Velocyto

 

scVelo [ python ]

: RNA velocity generalized through dynamical modeling

- Homepage : https://scvelo.readthedocs.io/

- Github : https://github.com/theislab/scvelo/discussions

- Paper : Generalizing RNA velocity to transient cell states through dynamical modeling, https://www.nature.com/articles/s41587-020-0591-3

pip3 install scvelo

 

 

Data

- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE96583

 

 

 

Reference

- The triumphs and limitations of computational methods for scRNA-seq, https://www.nature.com/articles/s41592-021-01171-x, http://pklab.med.harvard.edu/peterk/review2020/

- Training program, https://hbctraining.github.io/main/

- Analysis of single cell RNA-seq data, https://www.singlecellcourse.org/

- Bioinformatics Training, https://training.csx.cam.ac.uk/bioinformatics/search