Introduction | Background | Dataset | Preprocessing | Create an object | Normalize and scale data | Find zones with different transcriptional profiles | Correlation analysis | Dimensionality reduction analysis | Clustering analysis | Analyze peak genes | Find peak genes | Find co-regulated genes | Plot expression traces of genes | Modify plots | Session Information
Package: tomoda 1.23.0
Wendao Liu
tomoda: Tomo-seq data analysis
This package provides many easy-to-use methods to analyze and visualize tomo-seq data. The tomo-seq technique is based on cryosectioning of tissue and performing RNA-seq on consecutive sections. (Reference: Kruse F, Junker JP, van Oudenaarden A, Bakkers J. Tomo-seq: A method to obtain genome-wide expression data with spatial resolution. Methods Cell Biol. 2016;135:299-307. doi:10.1016/bs.mcb.2016.01.006) The main purpose of the package is to find zones with similar transcriptional profiles and spatially expressed genes in a tomo-seq sample. Several visulization functions are available to create easy-to-modify plots.
Authors:
tomoda_1.23.0.tar.gz
tomoda_1.23.0.zip(r-4.7)tomoda_1.23.0.zip(r-4.6)tomoda_1.23.0.zip(r-4.5)
tomoda_1.23.0.tgz(r-4.6-any)tomoda_1.23.0.tgz(r-4.5-any)
tomoda_1.23.0.tar.gz(r-4.7-any)tomoda_1.23.0.tar.gz(r-4.6-any)
tomoda_1.23.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tomoda/json (API)
| # Install 'tomoda' in R: |
| install.packages('tomoda', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/liuwd15/tomoda/issues
Datasets:
- zh.data - A raw read count matrix of zebrafish injured heart.
On BioConductor:tomoda-1.23.0(bioc 3.24)tomoda-1.22.0(bioc 3.23)
geneexpressionsequencingrnaseqtranscriptomicsspatialclusteringvisualization
Last updated from:96ce4ba71e. Checks:1 NOTE, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 188 | ||
| linux-devel-x86_64 | OK | 389 | ||
| source / vignettes | OK | 269 | ||
| linux-release-x86_64 | OK | 430 | ||
| macos-release-arm64 | OK | 227 | ||
| macos-oldrel-arm64 | OK | 337 | ||
| windows-devel | OK | 319 | ||
| windows-release | OK | 314 | ||
| windows-oldrel | OK | 347 | ||
| wasm-release | OK | 163 |
Exports:corHeatmapcreateTomoembedPlotexpHeatmapfindPeakfindPeakGenegeneCorHeatmapgeneEmbedPlothierarchClustkmeansClustlinePlotnormalizeTomorunPCArunTSNErunUMAPscaleTomotomoMatrixtomoSummarizedExperiment
Dependencies:abindaskpassBiobaseBiocGenericsclicpp11DelayedArrayfarvergenericsGenomicRangesggplot2ggrepelgluegtablehereIRangesisobandjsonlitelabelinglatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsopensslplyrpngR6rappdirsRColorBrewerRcppRcppEigenRcppTOMLreshape2reticulaterlangrprojrootRSpectraRtsneS4ArraysS4VectorsS7scalesSeqinfoSparseArraystringistringrSummarizedExperimentsysumapvctrsviridisLitewithrXVector
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Correlation heatmap of sections | corHeatmap |
| Create an object representing tomo-seq data | createTomo createTomo,matrix-method createTomo,missing-method createTomo,SummarizedExperiment-method |
| Embedding plot for sections | embedPlot |
| Expression heatmap | expHeatmap |
| Find peak in a vector | findPeak |
| Find peak genes | findPeakGene |
| Correlation heatmap of genes | geneCorHeatmap |
| Embedding plot for genes | geneEmbedPlot |
| Hierarchical clustering across sections | hierarchClust |
| K-Means clustering across sections | kmeansClust |
| Line plot for expression traces | linePlot |
| Normalize data | normalizeTomo |
| Perform PCA | runPCA |
| Perform TSNE | runTSNE |
| Perform UMAP | runUMAP |
| Scale data | scaleTomo |
| Create an object from matrix | tomoMatrix |
| Create an object from SummarizedExperiment | tomoSummarizedExperiment |
| A raw read count matrix of zebrafish injured heart. | zh.data |