Config Files (Parameter Files)

Cellsnake can be configured using a config file. The config file is in YAML format.

The use can specify the config file to use with the –configfile option. If no config file is specified, cellsnake will use the default parameters.

It is recommended to use the default config file as a template and modify it to your needs. You can download the default one here: https://raw.githubusercontent.com/sinanugur/cellsnake/main/config.yaml

#example usage with a config file
cellsnake standard data --configfile config.yaml

The default config file looks like this. This is modified for human samples.

#These are also default settings of a Cellsnake run without any configfile
#basic paramaters
min_cells: 3 #seurat defaults, recommended
min_features: 200 #seurat defaults, recommended, nFeature_RNA
max_features: Inf #seurat default, nFeature_RNA, 5000 can be a good cutoff
max_molecules: Inf #seurat default, nCount_RNA, to filter potential doublets, doublet filtering is already default, so keep this Inf
min_molecules: 0 #seurat default, nCount_RNA, min_features usually handles this so keep it 0


percent_mt: 10 #Mitochondrial genes maximum percentage (0-100), default 10, you can use "auto"
percent_rp: 0 #Ribosomal genes minimum percentage (0-100), default no filtering
highly_variable_features: 2000 #seurat defaults, recommended
variable_selection_method: "vst" #seurat defaults, recommended

#plotting paramaters
min_percentage_to_plot: 2 #only plot clusters with more than 2% of cells, still all of them visible on HTMLs and on plots if labels are True
show_labels: T #show labels on plots

#doublet filtering, True:T or False:F
doublet_filter: T #this may fail on some samples

#clustering and normalization paramaters
normalization_method: "LogNormalize"
scale_factor: 10000
resolution: "0.8" #seurat default

#Differential expression paramaters
logfc_threshold: 0.25
test_use: "wilcox"
marker_plots_per_cluster_n: 20 #plot summary marker plots for top markers
umap_markers_plot: True
tsne_markers_plot: False

#enrichment paramaters
mapping: "org.Hs.eg.db" #you may install others from Bioconductor, this is for human
organism: "hsa" #alternatives https://www.genome.jp/kegg/catalog/org_list.html

#SingleR reference
singler_ref: "BlueprintEncodeData" # https://bioconductor.org/packages/release/data/experiment/vignettes/celldex/inst/doc/userguide.html#1_Overview
singler_granulation: "label.main" #label.main or label.fine

#celltypist
celltypist_model: "Immune_All_Low.pkl" #refer to Celltypist for another model

#krakendb settings
kraken_db_folder:
taxa: "genus" # available options "domain", "kingdom", "phylum", "class", "order", "family", "genus", "species"
microbiome_min_cells: 1
microbiome_min_features: 3
confidence: 0.05 #see kraken2 manual
min_hit_groups: 4 #see kraken2 manual

#cellchat
species: "human" #human or mouse is accepted, http://www.cellchat.org/cellchatdb/

#integration params
dims: 30
reduction: "cca"

Changing the organism to mouse

You can change the organism and mapping to use it for other species.

For example, for mouse you can change these parameters:

species: "mouse"
mapping: "org.Mm.eg.db"
organism: "mmu"
singler_ref: "MouseRNAseqData"