Package: LRcell 1.13.0
Wenjing Ma
LRcell: Differential cell type change analysis using Logistic/linear Regression
The goal of LRcell is to identify specific sub-cell types that drives the changes observed in a bulk RNA-seq differential gene expression experiment. To achieve this, LRcell utilizes sets of cell marker genes acquired from single-cell RNA-sequencing (scRNA-seq) as indicators for various cell types in the tissue of interest. Next, for each cell type, using its marker genes as indicators, we apply Logistic Regression on the complete set of genes with differential expression p-values to calculate a cell-type significance p-value. Finally, these p-values are compared to predict which one(s) are likely to be responsible for the differential gene expression pattern observed in the bulk RNA-seq experiments. LRcell is inspired by the LRpath[@sartor2009lrpath] algorithm developed by Sartor et al., originally designed for pathway/gene set enrichment analysis. LRcell contains three major components: LRcell analysis, plot generation and marker gene selection. All modules in this package are written in R. This package also provides marker genes in the Prefrontal Cortex (pFC) human brain region, human PBMC and nine mouse brain regions (Frontal Cortex, Cerebellum, Globus Pallidus, Hippocampus, Entopeduncular, Posterior Cortex, Striatum, Substantia Nigra and Thalamus).
Authors:
LRcell_1.13.0.tar.gz
LRcell_1.13.0.zip(r-4.5)LRcell_1.13.0.zip(r-4.4)LRcell_1.13.0.zip(r-4.3)
LRcell_1.13.0.tgz(r-4.4-any)LRcell_1.13.0.tgz(r-4.3-any)
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LRcell.pdf |LRcell.html✨
LRcell/json (API)
NEWS
| # Install 'LRcell' in R: |
| install.packages('LRcell', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/marvinquiet/lrcell/issues
- example_LRcell_res - An example output of LRcell using data example_gene_pvals and mouse_FC_marker_genes.
- example_gene_pvals - Example gene_pvals named vector from mouse experiment.
- mouse_FC_marker_genes - Example marker genes from mouse FC brain region.
- mouse_celltypes - Mapping between subclusters and cell types in Mouse Brain
On BioConductor:LRcell-1.13.0(bioc 3.20)LRcell-1.12.0(bioc 3.19)
Last updated 2 months agofrom:7922d2dc6d
Exports:get_markergenesLRcellLRcell_gene_enriched_scoresLRcellCoreplot_manhattan_enrichplot_marker_dist
Dependencies:AnnotationDbiAnnotationHubaskpassBHBiobaseBiocFileCacheBiocGenericsBiocManagerBiocParallelBiocVersionBiostringsbitbit64blobcachemclicodetoolscolorspacecpp11crayoncurlDBIdbplyrdplyrExperimentHubfansifarverfastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataggplot2ggrepelgluegtablehttrIRangesisobandjsonliteKEGGRESTlabelinglambda.rlatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrpngpurrrR6rappdirsRColorBrewerRcpprlangRSQLiteS4VectorsscalessnowstringistringrsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrXVectoryamlzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculate enrichment scores for each cell type in a specific gene. | enrich_posfrac_score |
| Example gene_pvals named vector from mouse experiment. | example_gene_pvals |
| An example output of LRcell using data example_gene_pvals and mouse_FC_marker_genes. | example_LRcell_res |
| Get top marker genes for each subcluster | get_markergenes |
| Cell-type enrichment analysis for preranked gene set. | LRcell |
| Find most enriched cell types in bulk DE genes by Logistic Regression | LRcell_gene_enriched_scores |
| Find most enriched cell types in bulk DE genes by Logistic Regression | LRcellCore |
| Mapping between subclusters and cell types in Mouse Brain | mouse_celltypes |
| Example marker genes from mouse FC brain region. | mouse_FC_marker_genes |
| Manhattan plot for the enrichment of cell types | plot_manhattan_enrich |
| Plot marker genes distribution on DE gene rank | plot_marker_dist |