We support boolean queries, use +,-,<,>,~,* to alter the weighting of terms
Software R package to help disambiguate transcriptome samples by automating differential expression, then gene set enrichment, and finally N-dimensional projection to quantify in which ways each sample is like either treatment group.
Software R package is implementation Quantitative Set Analysis for Gene Expression method. Used to provide faster, more accurate, and easier to understand test for gene expression studies.
Software library of core preprocessing routines.
Software R package as molecular informatics toolkit with integration of bioinformatics and chemoinformatics tools for drug discovery.
Software R package providing PCA methods for incomplete data. Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and conventional SVD PCA. Cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation.
Software R package as interface to the graph algorithms contained in the BOOST library.
Software R package to assess quality of NanoString mRNA gene expression data, to identify outlier probes and outlier samples. Provides different background subtraction and normalization approaches for this data. It outputs suggestions for flagging samples/probes and easily sharable html quality control output.
Software toolkit of high level functions for DNA motif scanning and enrichment analysis built upon Biostrings. Used for PWM enrichment analysis of already known PWMs. Also implements high-level functions for PWM scanning and visualisation.
Software R package has two functions. One reads Affymetrix chip description file and creates hash table environment containing location/probe set membership mapping. The other creates package that automatically loads that environment.
Software R package provides set of flexible functions to evaluate and visualize multitude of mutational patterns in base substitution catalogues of e.g. healthy samples, tumour samples, or DNA-repair deficient cells.
Software R package to determine features that are differentially abundant between two or more groups of multiple samples. Used to address the effects of both normalization and under-sampling of microbial communities on disease association detection and testing of feature correlations.
Software R package to harmonize data management of multiple experimental assays performed on overlapping set of specimens.Provides user experience by extending concepts from SummarizedExperiment, supporting open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.
Software R pacakage for multidimensional data integration to identify pathogenic perturbations to biological systems. Used for integrating multidimensional omics disease associations, functional genomics, canonical pathways and gene-gene interaction networks to generate mechanistic hypotheses. Includes Marker set enrichment analysis and Weighted Key Driver Analysis parts.
Software R package for imputation for microarray data.
Software R package implements filtering procedure for replicated transcriptome sequencing data based on global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions.
Software R package provides set of annotation maps describing entire Gene Ontology assembled using data from GO.
Software R package that implements some simple capabilities for representing and manipulating hypergraphs.
Software R package to perform live annotation queries to Ensembl and UCSC and translates this to e.g. gene/transcript structures in viewports of the grid graphics package.
Software R package provides some basic functions for filtering genes.
Software R package for analysis of GRO-seq data. Used for identifying unannotated and cell type-specific transcription units from global run-on sequencing data