An easy-to-use application for microarray, RNA-Seq and metabolomics analysis. For splicing sensitive platforms (RNA-Seq or Affymetrix Exon, Gene and Junction arrays), AltAnalyze will assess alternative exon (known and novel) expression along protein isoforms, domain composition and microRNA targeting. In addition to splicing-sensitive platforms, AltAnalyze provides comprehensive methods for the analysis of other data (RMA summarization, batch-effect removal, QC, statistics, annotation, clustering, network creation, lineage characterization, alternative exon visualization, gene-set enrichment and more).
Permits to compare, validate and substantiate cell type transcriptional profiles across scRNA-seq datasets. MetaNeighbor can readily identify cells of the same type across datasets, without relying on specific knowledge of marker genes. The tool returns a performance score for each gene set and task that is the mean area under the receiver operator characteristic curve (AUROC) across all folds of cross-dataset validation.
Allows to make unsupervised projection of single cells from an scRNA-seq experiment. scmap is easy to combine with other computational scRNA-seq methods. It is very fast, using 1,000 features taking only around twenty seconds to map 40,000 cells. Its run-time can be further improved since the centroids and features for each cluster can be pre-computed, and stored in memory, even for a very large atlas.
Provides essential tools for users to read in single-cell regolome data (ChIP-seq, ATAC-seq, DNase-seq) and summarize into different types of features. SCRAT also allows users to visualize the features, cluster samples and identify key features.
Allows exploration of single-cell next-gene sequencing data. SeqGeq permits the discovery of sub-populations, differentially expressed genes and allows the creation of publishable figures with an easy-to-use interface. It can serve to identify population’s relationships as well as examine and construct gene sets.
Assists in cell type identification. ACTION provides a method to detect key marker genes for each cell type, as well as transcription factors that are responsible for mediating the observed expression of these markers. It is a program for: (1) identifying cell types, (2) characterizing their functional identity, and (3) uncovering underlying regulatory factors from single-cell expression datasets.
Finds similar cells based on their expression patterns. CellFishing.jl is a cell search method that employs locality-sensitive hashing (LSH) and an indexing technique of bit vectors to narrow down candidates of similar cells. The software creates a search database of reference cells from a matrix of transcriptome expression profiles of scRNA-seq experiments, and then searches the database for cells with an expression pattern similar to the query cells. It considers rare cell types and is robust in response to differences between batches, species, and protocols.