Bioconductor 3.23 wrap-up
bioconductor
R
My wrap-up of the Bioconductor 3.23 release
The Bioconductor 3.23 release was a couple of weeks ago. Here is my wrap-up of new packages and updates. This is only the things I found interesting based on the release notes and they don’t come with any particular recommendations. If there is something else you are interested in have a look at the full release notes here.
My packages
{anndataR}
- Add initial support for reading and writing Zarr stores. This was a major effort from members of the community.
- Improvements to chunking when writing H5AD files
- Improvements to performance when reading sparse matrices
- Improved warnings and error handling
- Improved tests, documentation and CI
{splatter}
- Replace deprecated functions from {scuttle} with equivalents in {scrapper}
- Deprecate the MFA simulation functions now that the {mfa} package is deprecated
- Minor maintenance updates
{zellkonverter}
- Minor updates to tests and documentation
New packages
- {BatChef} - benchmark batch correction methods for scRNA-seq data and help pick an appropriate one
- {Battlefield} - low-level utilities for working with spatial transcriptomics regions, interfaces and layers
- {betterChromVAR} - faster chromVAR-style inference of TF activity for bulk and single-cell ATAC-seq
- {CellMentor} - supervised dimensionality reduction that tries to preserve known cell-type structure
- {DenoIST} - removes neighbourhood contamination from image-based spatial transcriptomics data
- {dominatR} - visualises feature dominance using concepts from physics
- {GraphExperiment} - extends
SingleCellExperimentwith infrastructure for storing feature-level networks - {hammers} - utilities package for scRNA-seq analysis using both
SeuratandSingleCellExperiment - {jvecfor} - faster nearest-neighbour search for large single-cell datasets with drop-in replacements for common Bioconductor workflows
- {RankMap} - fast reference-based cell type annotation for single-cell and spatial transcriptomics data
- {scConform} - cell type annotation with conformal prediction intervals and uncertainty quantification
- {scECODA} - workflow for analysing cell type proportions as compositional data
- {scLang} - developer-facing helpers for writing scRNA-seq packages that work with both Seurat and
SingleCellExperiment - {scPassport} - stores a persistent metadata passport inside
SeuratandSingleCellExperimentobjects - {scTypeEval} - tools for evaluating cell type assignments with limited ground truth data
- {SpatialArtifacts} - quality control for identifying spatial artifacts in Visium and Visium HD data
- {SpNeigh} - neighbourhood-aware spatial transcriptomics analysis including boundary detection and spatial differential expression
- {tidyprint} - tidier print methods for
SummarizedExperimentobjects - {VISTA} - wraps differential expression workflows and visualisation in a
SummarizedExperiment-based container - {ZarrArray} -
DelayedArray-backed infrastructure for working with Zarr datasets in R
Updates
- {DropletUtils} -
downsampleReads()now uses the faster downsampling algorithm from {scuttle} - {edgeR} - new
DGEListFromTximport()andDGEListFromTximeta()helpers plus asampleWeights()function - {limma} -
voom()gains offset support andtopTableF()is now finally removed - {Rarr} - major updates including moving the
DelayedArraybackend into the new {ZarrArray} package and improved Zarr v3 support - {Rhdf5lib} - build updates and an update to HDF5 1.14.6
- {rhdf5} - updated to HDF5 1.14.6 and various fixes and improvements
- {scran} - deprecates several functions in favour of {scrapper} and fixes overflow bugs
- {scrapper} - multiple updates to several functions, continues the migration of functionality out of {scran} and {scuttle}
- {scuttle} - faster
downsampleMatrix()andsummarizeAssayByGroup(), more deprecations in favour ofscrapper - {SingleCellExperiment} - improved warnings for named assay getters and setters
- {tximeta} - matching updates for {edgeR}’s new
DGEListFromTximeta()workflow - {tximport} - vignette updates around the new {edgeR} integration
NoteAI Disclaimer
AI was used to research and draft this post. It did a reasonable job on matching the style of previous posts but it missed several packages I had to tell it to add later. Overall, it was moderately successful.