stPipe

Upstream pre-processing for Sequencing-Based Spatial Transcriptomics

Bioconductor version: 3.23 · Package version: 1.2.0

This package serves as an upstream pipeline for pre-processing sequencing-based spatial transcriptomics data. Functions includes FASTQ trimming, BAM file reformatting, index building, spatial barcode detection, demultiplexing, gene count matrix generation with UMI deduplication, QC, and revelant visualization. Config is an essential input for most of the functions which aims to improve reproducibility.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("stPipe")

Details

Maintainer	Yang Xu <xu.ya@wehi.edu.au>
Author	Yang Xu [aut, cre] (ORCID: <https://orcid.org/0009-0008-3274-6516>), Callum Sargeant [aut], Shian Su [aut], Luyi Tian [aut], Yunshun Chen [ctb], Matthew Ritchie [ctb, fnd]
License	GPL-3
URL	https://github.com/mritchielab/stPipe
Bug Reports	https://github.com/mritchielab/stPipe/issues/new
System Requirements	GNU make
Downloads rank	140
Source branch	RELEASE_3_23
biocViews	Clustering, DataImport, GeneExpression, GenomeAnnotation, ImmunoOncology, Preprocessing, QualityControl, RNASeq, SequenceMatching, Sequencing, SingleCell, Software, Spatial, Transcriptomics, Visualization

Documentation

stPipe: A flexible and streamlined pipeline for processing sequencing-based spatial transcriptomics data

Download

Source package

Dependencies

Depends: R (>= 4.5.0)

Imports: basilisk, data.table, DropletUtils, dplyr, ggplot2, methods, pbmcapply, reticulate, rmarkdown, Rcpp, Rhtslib, Rsubread, Rtsne, Seurat, SeuratObject, scPipe, shiny, SummarizedExperiment, SingleCellExperiment, SpatialExperiment, stats, umap, yaml

LinkingTo: Rcpp, Rhdf5lib, testthat, Rhtslib

Suggests: knitr, plotly, BiocStyle, testthat (>= 3.0.0)