BANKSY is a method for clustering spatial transcriptomic data by augmenting the transcriptomic profile of each cell with an average of the transcriptomes of its spatial neighbors.
Combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data.
Scalable correlation-based feature selection method for accurately clustering single-cell data.
RCA (Reference Component Analysis) is a computational approach for robust cell type annotation of single cell RNA sequencing data (scRNAseq). It is developed by the Prabhakar lab at the Genome Institute of Singapore (GIS). The original version of RCA is published in Nature Genetics (doi: 10.1038/ng.3818, Li et al., 2017).
Dfilter is a generalized signal detection tool for analyzing next-gen massively-parallel sequencing data by using ROC-AUC maximizing linear filter. Hence it is an ideal tool for detecting peaks in tag-profile of ChIP-seq, DNase-seq, FAIRE-seq, ATAC-seq, MNase-seq, RIP-seq, CLIP-seq, ChIP-exo, Sono-seq etc.
TACO, or Transcription factor Association from Complex Overrepresentation, is a program for motif complex analysis in regulatory genomic sequences. It takes as input any genome-wide set of regulatory elements and predicts cell-type–specific transcription factor dimers based on enrichment of their motif complexes. This is the first tool of such kind that can accommodate motif complexes composed of overlapping motifs, which are a characteristic feature of many known transcription factor dimers.