ROTS R-package implements the reproducibility-optimized test statistic (ROTS) for ranking genes or proteins in terms of differential expression in two-group comparisons.
DCeN R-package implements the Dynamically Co-expressed Neighborhoods (DCeN) for ranking genes in genome-wide time-resolved gene expression profiling studies.
GeneFuncster is an easy-to-use web tool for for functional enrichment analysis for short filtered and long non-filtered gene lists. It is available for several organisms and able to provide versatile result visualization for Gene Ontology, KEGG and Reactome databases.
GWES is a web-based application that runs epistasis analysis on a powerful computer cluster.
BiclusterMiner implements an efficient biclustering approach enabling the complete identification of all biclusters while keeping the computational demands minimal and running times reasonable.
BiForce / BiForce Toolbox supports high-throughput analysis of epistasis in GWAS for either binary or quantitative traits.
PECA allows improved differential expression analysis for Affymetrix microarrays and proteomics studies and is based on Probe/peptide-level Expression Change Averages
PASI Pathway Analysis for Sample-level Information
Phosphonormalizer uses the overlap between enriched and non-enriched datasets to compensate for the bias introduced in global phosphorylation after applying median normalization.
Bioinformatics Unit currently hosts licenses for the following software:
CLC Genomics Workbench
Software for analyzing and visualizing next generation sequencing data, incorporates cutting-edge technology and algorithms, while also supporting and integrating with the rest of the typical NGS workflow. More information on the software. In order to get access, please contact asta.laiho at utu.fi.
Ingenuity Pathway Analysis (IPA)
Software for the analysis and interpretation of biological high-throughput measurement data relying on the Ingenuity Knowledge Base, a repository of expertly curated biological interactions and functional annotations created from millions of individually modeled relationships between proteins, genes, complexes, cells, tissues, drugs, and diseases. More information on the software. In order to get access, please contact ffgc (at) utu.fi.