Bioconductor is a free, open source and open development software project which provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the statistical R programming language, but does contain contributions in other programming languages.
The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results.
Key Features
- Provides access to powerful statistical and graphical methods for the analysis of genomic data. Analysis packages address workflows for analysis of:
- Oligonucleotide arrays.
- Sequence analysis.
- Flow cytometry.
- Other high-throughput genomic data.
- Each Bioconductor package contains one or more vignettes, documents that provide a textual, task-oriented description of the package’s functionality.
- Provides software for associating microarray and other genomic data in real time with biological metadata from web databases such as GenBank, Entrez genes and PubMed.
- Analysis of differentially expressed genes:
- LIMMA.
- cDNA Arrays.
- Affy Arrays.
- RankProd.
- SAM.
- R/maanova.
- Digital Gene Expression.
- LIMMA.
- Dual Color Array packages.
- Gene Ontologies:
- General.
- GOHyperGAII.
- GSEA.
GoTools and goCluster.
- KEGG pathway analysis.
- Motif identification in promoter regions.
- Protein structure analysis.
- MS data analysis.
- Genome-Wide Association Studies (GWAS).
- Uses R to add a raft of functionality.
Website: www.bioconductor.org
Support:
Developer: Vince Carey, Marc Carlson, Sean Davis, Robert Gentleman, Nishant Gopalakrishnan, Wolfgang Huber and many others
License: Artistic License 2.0
Bioconductor is written in R. Learn R with our recommended free books and free tutorials.
Related Software
| Bioinformatics Tools | |
|---|---|
| Bioconductor | Analysis and comprehension of high-throughput genomic data |
| Biopython | Tools for biological computation written in Python |
| UGENE | Set of integrated bioinformatics software |
| BioPerl | Perl tools for computational molecular biology |
| GROMACS | Versatile package to perform molecular dynamics |
| IGV | High-performance visualization genome browser tool |
| GATK | Genomic analysis toolkit focused on variant discovery |
| BioJava | Provides Java tools for processing biological data |
| InterMine | Integrate biological data sources |
| bedtools | Powerful toolset for genome arithmetic |
| EMBOSS | The European Molecular Biology Open Software Suite |
| BLAST | Algorithm for comparing primary biological sequence information |
| Galaxy | Web-based platform for data-intensive computational research |
| minimap2 | Versatile sequence alignment program |
| Jalview | Multiple sequence alignment editing, visualisation and analysis |
| samtools | Manipulate next-generation sequencing data |
| BCFtools | Variant calling and manipulating files in the Variant Call Format |
| FastQC | Quality control tool for high throughput sequence data |
| SPAdes | Versatile toolkit for assembling and analysing sequencing data |
| GenomeTools | Collection of bioinformatics tools |
| AliView | Alignment viewer and editor |
| mothur | Analyze microbial communities |
| Bandage | Visualising de novo assembly graphs |
| cramino | BAM/CRAM quality evaluation |
| abPOA | Adaptive banded Partial Order Alignment |
| Taverna Workbench | For designing and executing bioinformatics workflows |
| geWorkbench | Software platform for integrated genomic data analysis |
| Bioclipse | Rich-client platform chemistry and biology workbench |
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