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easybio

easybio provides a comprehensive toolkit for single-cell RNA-seq annotation using the CellMarker2.0 database. It streamlines the process of assigning biological labels in scRNA-seq data, integrating seamlessly with tools like Seurat. While the package includes additional bioinformatics workflows, such as handling TCGA and GEO datasets, differential expression analysis, and enrichment analysis visualization, for details specifically on the single-cell annotation functionality, please refer to the bioRxiv preprint.

Download and Usage

You can install the development version of easybio from GitHub with:

devtools::install("person-c/easybio", build_vignettes = TRUE)

To know how to use this package, please see the wiki or run:

vignette(topic = "example-bulk-rna-seq-workflow", package = 'easybio')
vignette(topic = "example-single-cell-annotation", package = "easybio")

To learn the difference between development version and CRAN version, see NEWS

Citation

If you use the single-cell annotation functionality from easybio, consider cite:

Wei, Cui. (2024). easybio: an R Package for Single-Cell Annotation with CellMarker2.0. bioRxiv. https://doi.org/10.1101/2024.09.14.609619

C. Hu, T. Li, Y. Xu, X. Zhang, F. Li, J. Bai, J. Chen, W. Jiang, K. Yang, Q. Ou, X. Li, P. Wang, Y. Zhang, CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data, Nucleic Acids Research 51 (D1) (2022) D870–D876. doi:10.1093/nar/gkac947. https://doi.org/10.1093/nar/gkac947

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Version

Install

install.packages('easybio')

Monthly Downloads

309

Version

1.1.0

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Maintainer

Wei Cui

Last Published

September 16th, 2024

Functions in easybio (1.1.0)

limmaFit

Fit a Linear Model for RNA-seq data using limma
prepare_tcga

Prepare TCGA Data for Analysis
setSavedir

Set a Directory for Saving Files
workIn

Perform Operations in a Specified Directory and Return to the Original Directory
theme_publication

Custom ggplot2 Theme for Academic Publications
split_matrix

Split a Matrix into Smaller Submatrices by Column
plotPossibleCell

Plot Possible Cell Distribution Based on matchCellMarker2() Results
tuneParameters

Optimize Resolution and Gene Number Parameters for Cell Type Annotation
uniprot_id_map

Map UniProt IDs to Other Identifiers
plotRank

Visualization of GSEA Rank Statistics
plotSeuratDot

Create Dot Plots for Markers from check_marker
plotVolcano

Plot Volcano Plot for Differentially Expressed Genes
list2dt

Convert a List with Vector Values to a Long Data.table
prepare_geo

Download and Process GEO Data
check_marker

Verify Markers for Specific Clusters Using matchCellMarker
dprocess_dgeList

Filter Low-Expressed Genes and Normalize DGEList Data
get_attr

Retrieve Attributes from an R Object
groupStat

Perform Summary Analysis by Group Using Regular Expressions
finsert

Insert Specific Values into a Character Vector at Defined Positions
dgeList

Construct a DGEList Object
groupStatI

Perform Summary Analysis by Group Using an Index
get_marker

Retrieve Markers for Specific Cells from cellMarker2
CHOL_DEGs

Example DEGs data from Limma-Voom workflow for TCGA-CHOL project
Artist

Visualization Artist for Custom Plots
matchCellMarker2

Match Markers with cellMarker2 Dataset
plotMarkerDistribution

Plot Distribution of a Marker Across Tissues and Cell Types
plotGSEA

Visualization of GSEA Result from fgsea::fgsea()
plotORA

Visualization of ORA Test Results
list2graph

Convert a Named List into a Graph Based on Overlap
pbmc.markers

Example marker data from Seurat::FindAllMarkers()
setcolnames

Rename Column Names of a Data Frame or Matrix
plotEnrichment2

Plot Enrichment for a Specific Pathway in fgsea
setrownames

Rename Row Names of a Data Frame or Matrix