Glossary

Here we explain some of the terminology related to Cellsnake and Seurat.

RDS (R Data Serialization) files are a common format for saving R objects in RStudio, and they allow you to preserve the state of an object between R sessions. Cellsnake generated RDS files for later use, you can access them under analyses folder.

ClusTree plot ClusTree package allows you to produce clustering trees, a visualisation for interrogating clusterings as resolution increases. Please refer their publication for more details. You can access this plot under technicals.

nFeature_RNA is the number of genes detected in each cell. You can access this plot under technicals.

nCount_RNA is the total number of molecules detected within a cell. You can access this plot under technicals.

mt.percent Mitochondrial RNA percentage. We use “^[Mm][Tt]-” regex pattern to detect MT genes. Higher percentage of MT genes may suggest dead cells.

rp.percent Ribosomal RNA percentage. We use “(?i)(^RP[SL])” regex pattern to detect ribosomal genes. Usually no filtering required for ribosomal genes.

min_cells Features detected at least this many cells. For example a gene detected only in 2 cells may not be important. We use 3 as a default value.

min_features Cells at least this many features. For example a cell express only 50 genes might be a dead cell. We use 200 as a default value.

Snakemake Snakemake is a workflow managament tool to design bioinformatics pipelines. Cellsnake contains a Snakemake workflow based on mostly Seurat which is an R based single-cell analysis tool.

SingleR It is an R package for annotation of single-cell RNA-seq data. plot_annotations predicted using SingleR package. You can also access additional plots under singler directory related to annotation.