Templates with revision indicates that the components or processes have undergone comprehensive parameterization and testing.
Templates with revision indicates that the components or processes are currently being tested. There is some test data available, but there are parameters that need to be set up manually within the code.
Templates with revision indicates that the components or processes are not fully tested. There is no test data available, parameters need to be set up manually within the code, and specific code changes are required based on the data used.
Read main page to know how to collaborate with us.
Make sure there is a valid project name, and modify information.R
with the right information for your project. You can use this file with any other Rmd to include the project/analysis information.
- Set the working directory to this file level. We recommend to use Projects in Rstudio.
- Use
install_dependencies.R
to install all packages used in these reports.
cellranger
outputs are in your output directory under results/cellranger
.
pre-process-w-cellranger.md
contains step by step guidelines on how to run cellranger.
Then, the scripts/seurat_init.R
script contains all the pieces to go from cellranger output to Seurat obj. It is assuming a mouse genome. Alternatively, if you have an especially large single cell dataset, you may wish to construct a Seurat object where the counts matrix remains stored on-disk and is not loaded into R memory. The scripts/seurat_ondisk.R
script can assist with this.
The Rmd that helps to visualize ATAC metrics is
01_quality_assessment/scATAC_QC.Rmd
.
Currently we are working on deploying a shiny app to inspect the single cell object and find the best cut-offs for filtering. The Rmd that helps to visualize the before and after is
01_quality_assessment/scRNA_QC.Rmd
.
02_integration/norm_integration.rmd
is a template with guidelines on how to work with multiple samples. It compares log2norm vs SCT, work with SCT by samples to remove batch biases better, provide options for integration between CCA and Harmony. As last step, it contains cell type clustering and visualization to help decide the best parameters.
Read full documentation at 02_differential_expression/README.md.
-
pseudobulk approach:
02_differential_expression/scRNA_pseudobulk.Rmd
is a template that performs pseudobulk differential expression analysis using DESeq2. -
MAST - single cell approach:
02_differential_expression/scRNA_MAST.Rmd
is a template to visualize differentially expressed genes (DEG) results generated from MAST analysis. ## Compositional Analysis
04_compositional/propeller.Rmd
and 04_compositional/sscomp.Rmd
are templates to run compositional analysis with two different methods. comp.png
is an example of sccomp.Rmd
analysis.