Package: hammers 1.1.0

Andrei-Florian Stoica

hammers: Utilities for scRNA-seq data analysis

hammers is a utilities suite for scRNA-seq data analysis compatible with both Seurat and SingleCellExperiment. It provides simple tools to address tasks such as retrieving aggregate gene statistics, finding and removing rare genes, performing representation analysis, computing the center of mass for the expression of a gene of interest in low-dimensional space, and calculating silhouette and cluster-normalized silhouette.

Authors:Andrei-Florian Stoica [aut, cre]

hammers_1.1.0.tar.gz
hammers_1.1.0.zip(r-4.7)hammers_1.1.0.zip(r-4.6)hammers_1.1.0.zip(r-4.5)
hammers_1.1.0.tgz(r-4.6-any)hammers_1.1.0.tgz(r-4.5-any)
hammers_1.1.0.tar.gz(r-4.7-any)hammers_1.1.0.tar.gz(r-4.6-any)
hammers_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
hammers/json (API)

# Install 'hammers' in R:

install.packages('hammers', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/andrei-stoica26/hammers/issues

On BioConductor:hammers-1.1.0(bioc 3.24)hammers-1.0.0(bioc 3.23)

software singlecell geneexpression multiplecomparison visualization

5.41 score 1 stars 1 packages 4 scripts 25 exports 108 dependencies

Last updated from:6a2356ee43. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	265
linux-devel-x86_64	OK	424
source / vignettes	OK	428
linux-release-x86_64	OK	452
macos-release-arm64	OK	210
macos-oldrel-arm64	OK	196
windows-devel	OK	1500
windows-release	OK	1491
windows-oldrel	OK	1360
wasm-release	OK	266

Exports:addCategory addMetadataCategory addNormSilhouette centerOfMass checkGenes colCenters colsDimPlot computeSilhouette devPlot distributionPlot findRareGenes geneCellSets geneCenters genePresence genesDimPlot joinCharCombs keyvalMap normalizeSilhouette pointsDimPlot prepAlluvial pvalRiverPlot removeRareGenes repAnalysis safeMessage safeMinmax

Dependencies:abdiv abind ape base64enc Biobase BiocGenerics cachem class cli cluster codetools cpp11 data.table DelayedArray digest dotCall64 dplyr farver fastmap float future future.apply generics GenomicRanges ggalluvial ggeasy ggforce ggnewscale ggplot2 ggraph ggrepel globals glue graphlayouts gridExtra gtable henna igraph IRanges isoband jsonlite labeling lattice lazyeval lgr lifecycle listenv LISTO liver magrittr MASS Matrix MatrixExtra MatrixGenerics matrixStats memoise mlapi nlme omnibus paletteer parallelly pillar pkgconfig plyr polyclip primes prismatic progressr purrr R6 RColorBrewer Rcpp RcppArmadillo RcppEigen rematch2 reshape2 RhpcBLASctl rlang rsparse rstudioapi S4Arrays S4Vectors S7 scales scLang Seqinfo SeuratObject SingleCellExperiment sp spam SparseArray statisfactory stringi stringr SummarizedExperiment systemfonts text2vec tibble tidygraph tidyr tidyselect tweenr utf8 vctrs viridis viridisLite withr XVector

Introduction to hammers

Rendered fromhammers.Rmdusingknitr::rmarkdown

Last update: 2026-03-06
Started: 2025-09-09

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Add a categorical column to a data frame based on another column	addCategory
Add a categorical column to a Seurat metadata or SingleCellExperiment coldata	addMetadataCategory
Adds normalized silhouette column to a single-cell expression object	addNormSilhouette
Calculate the center of mass of columns	centerOfMass
Check if all genes exist in the single-cell expression object	checkGenes
Calculate the centers of mass of metadata/coldata columns	colCenters
Create a single-cell dimensionality reduction plot with added labeled points for numeric columns	colsDimPlot
Compute cluster silhouette for single-cell expression object	computeSilhouette
Saves plot or list of plots	devPlot devPlot.default devPlot.function devPlot.ggplot devPlot.list
Plot the distribution of cells across two columns	distributionPlot
Find rare genes in a Seurat or SingleCellExpression object	findRareGenes
Generates cell sets for each input gene	geneCellSets
Calculate the centers of mass of the expression of input genes	geneCenters
Extract gene presence from a Seurat or SingleCellExperiment object	genePresence
Create a single-cell dimensionality reduction plot with added labeled points for genes	genesDimPlot
Join all combinations of elements from character vectors	joinCharCombs
Create a map from keys to values	keyvalMap
Normalize silhouette by identity class for single-cell expression object	normalizeSilhouette
Create a single-cell dimensionality reduction plot with added labeled points	pointsDimPlot
Prepare dataframe for alluvial plot	prepAlluvial
Plot representation data frame	pvalRiverPlot
Remove rare genes from a Seurat or SingleCellExpression object	removeRareGenes
Find the differential representation of two Seurat or SingleCellExperiment columns	repAnalysis
Message an input if verbose is set to TRUE	safeMessage
Perform min-max normalization when possible; otherwise return a single-value vector.	safeMinmax