Package Recipe 'bioconductor-busparse'

recipe bioconductor-busparse

kallisto | bustools R utilities

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/BUSpaRse.html
License:: BSD_2_clause + file LICENSE
Recipe:: /bioconductor-busparse/meta.yaml

The kallisto | bustools pipeline is a fast and modular set of tools to convert single cell RNA-seq reads in fastq files into gene count or transcript compatibility counts (TCC) matrices for downstream analysis. Central to this pipeline is the barcode, UMI, and set (BUS) file format. This package serves the following purposes: First, this package allows users to manipulate BUS format files as data frames in R and then convert them into gene count or TCC matrices. Furthermore, since R and Rcpp code is easier to handle than pure C++ code, users are encouraged to tweak the source code of this package to experiment with new uses of BUS format and different ways to convert the BUS file into gene count matrix. Second, this package can conveniently generate files required to generate gene count matrices for spliced and unspliced transcripts for RNA velocity. Here biotypes can be filtered and scaffolds and haplotypes can be removed, and the filtered transcriptome can be extracted and written to disk. Third, this package implements utility functions to get transcripts and associated genes required to convert BUS files to gene count matrices, to write the transcript to gene information in the format required by bustools, and to read output of bustools into R as sparses matrices.

package bioconductor-busparse¶

Versions:

1.24.0-0, 1.20.0-0, 1.16.0-0, 1.14.1-0, 1.12.0-1, 1.12.0-0, 1.8.0-2, 1.8.0-1, 1.8.0-0,

1.24.0-0, 1.20.0-0, 1.16.0-0, 1.14.1-0, 1.12.0-1, 1.12.0-0, 1.8.0-2, 1.8.0-1, 1.8.0-0, 1.5.3-0, 1.4.2-0, 1.4.0-0, 1.2.1-0, 1.0.0-0

Depends:

on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-annotationdbi >=1.72.0,<1.73.0a0
on bioconductor-annotationfilter >=1.34.0,<1.35.0
on bioconductor-annotationfilter >=1.34.0,<1.35.0a0
on bioconductor-annotationhub >=4.0.0,<4.1.0
on bioconductor-annotationhub >=4.0.0,<4.1.0a0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0a0
on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-biomart >=2.66.0,<2.67.0a0
on bioconductor-biostrings >=2.78.0,<2.79.0
on bioconductor-biostrings >=2.78.0,<2.79.0a0
on bioconductor-bsgenome >=1.78.0,<1.79.0
on bioconductor-bsgenome >=1.78.0,<1.79.0a0
on bioconductor-ensembldb >=2.34.0,<2.35.0
on bioconductor-ensembldb >=2.34.0,<2.35.0a0
on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomeinfodb >=1.46.2,<1.47.0a0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0a0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.1,<1.63.0a0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-iranges >=2.44.0,<2.45.0a0
on bioconductor-plyranges >=1.30.0,<1.31.0
on bioconductor-plyranges >=1.30.1,<1.31.0a0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-bh
on r-dplyr
on r-ggplot2
on r-lifecycle
on r-magrittr
on r-matrix
on r-rcpp
on r-rcpparmadillo
on r-rcppprogress
on r-stringr
on r-tibble
on r-tidyr
on r-zeallot

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-busparse

to add into an existing workspace instead, run:

pixi add bioconductor-busparse

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-busparse

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-busparse

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-busparse:<tag>

(see bioconductor-busparse/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-busparse/README.html)