Spark is a discovery tool intended to help you explore the patterns in your genome-wide data. While genome browsers offer a powerful means to integrate diverse data types, their view is inherently limited to individual genomic loci and it can be difficult to obtain a global overview of the predominant data patterns. To address this need, we developed Spark, which enables interactive data clustering and visualization, and serves as a complement to genome browsing.
Cydney B. Nielsen, Hamid Younesy, Henriette O’Geen, Xiaoqin Xu, Andrew R. Jackson, Aleksandar Milosavljevic, Ting Wang, Joseph F. Costello, Martin Hirst, Peggy J. Farnham, Steven J.M. Jones. Spark: A navigational paradigm for genomic data exploration. Genome Research. 2012 Nov;22(11):2262-9.
StructHDP is a program for automatically inferring the population structure and number of clusters from a sample of admixed genotype data. It extends the model used by Structure to allow for a potentially infinite number of populations and then chooses the number of populations that best explain the data.
The Network Notif Clustering Toolbox is a Matlab/Octave toolbox for clustering topological network motifs in large-scale, integrated networks. The clustering algorithm is based on rigorous mathematical results and has been validated on an integrated yeast interaction network.
TiCoNE (Time Course Network Enricher) is a tool for the combined analysis of time series expression data together with biological networks.It will find time patterns emerging in the expression data and check for network modules enriched with genes of similar expression behavior over time.
CABRA is a web tool , which enables a rapid BLAST search in a variety of updated reference proteomes, and provides a new way to functionally evaluate the results by the subsequent clustering of the hits and annotation of the clusters.
MCODE is a Cytoscape plugin that finds clusters (highly interconnected regions) in a network. Clusters mean different things in different types of networks. For instance, clusters in a protein-protein interaction network are often protein complexes and parts of pathways, while clusters in a protein similarity network represent protein families.
CAGEScan-Clustering creates transcript assemblies from CAGEScan derived Transcription Start Site (TSS) associated reads paired with randomly primed readsm, grouping them on the basis of the common location of TSS reads.