Function reference • sciCSR

Setting up dependencies

Wrapper to set up python dependencies.

prepare_sciCSR(): Prepare conda environment

scRNA-seq data processing and wrangling

Functions for basic scRNA-seq data processing wrangling, including B-cell-specific functionalities.

collapseIntoMetagenes(): Group gene counts into metagenes to minimise individual differences

normalise_dimreduce(): Normalisation and dimensionality reduction of scRNAseq gene counts

guessBarcodes(): parse the substring inside a given cell identifier which corresponds to the nucleotide barcode

repairBarcode(): Repairing cell barcodes in a list of data frames/matrices to match the Seurat object

convertSeuratToH5ad(): wrapper function to convert Seurat Object to a AnnData .h5ad file

splitAnnData(): Split AnnData object by levels in a specified meta data trait

read_loom_matrices(): read loom matrices

combineLoomFiles(): Combine velocyto loom files on multiple BAM files into one loom file

Merging Repertoire and scRNA-seq read counts

Functions for additing repertoire annotation features as metadata to gene expression count matrices.

annotatePairing(): Annotate heavy-light chain pairing

collapseBCR(): Collapse the VDJ repertoire data frames by cell barcode

AddCellMetaToVDJ(): Add cell metadata from Seurat object into VDJ data frame

combineBCR(): Add annotations from VDJ data frame into the Seurat object

CSR/SHM-based pseudotime

Functions for extracting and calculating cell pseudotime ordering using CSR and SHM information.

scanBam(): Scan reads mapped to a given genomic range

getIGHmapping(): wrapper function to scan sterile/productive IGH molecules from BAM file

getIGHreadType(): Deduce type of IGH reads

getJunctionReads(): extract reads covering splice junctions

summariseIGHreads(): cast data frame IGH counts into a matrix

mergeIgHCountsToSeurat(): merge IgH productive/sterile transcript count into Seurat Object

getCSRpotential(): score cells by their Class Switch Recombination (CSR) status

getSHM(): get somatic hypermutation level

getIsotype(): label isotypes based on productive/sterile transcript levels

RNA velocity

RNA velocity analysis in R by interfacing with python packages

mergeVelocytoWithGEX(): Combine velocyto loom data with AnnData

run_scVelo(): Calculate RNA velocity using the python scvelo workflow

Inferring transitions

Inferring transitions using CSR/SHM information or RNA velocity

fitTransitionModel(): Fit transition model on data using the python cellrank package

fitTPT(): Fit Transition Path Theory (TPT) on the cellrank transition models

compareTransitionMatrices(): Computing distances between multiple transition matrices

Data visualisation

Visualising inferred transitions

plotFluxMatrix(): Visualise flux matrix describing class-switch recombination (CSR) transitions in data

plotStationaryDistribution(): Visualise stationary distribution of isotypes in the data

plot_arrows(): Plot arrows showing transitions in the style of RNA velocity plots

Data objects

Data objects underlying sciCSR functionalities

human_definitions: Genomic coordinates of human heavy-chain immunoglobulin V, D, J, C genes

human_nmf: Isotype sterile/productive signatures trained using human single-cell B cell atlas

mouse_definitions: Genomic coordinates of mouse heavy-chain immunoglobulin V, D, J, C genes

mouse_nmf: Isotype sterile/productive signatures trained using mouse single-cell B cell atlas