Abstract

The PANTHER classification system ( http://www.pantherdb.org ) is a comprehensive system that combines genomes, gene function classifications, pathways and statistical analysis tools to enable biologists to analyze large-scale genome-wide experimental data. The current system (PANTHER v.14.0) covers 131 complete genomes organized into gene families and subfamilies; evolutionary relationships between genes are represented in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models (HMMs)). The families and subfamilies are annotated with Gene Ontology (GO) terms, and sequences are assigned to PANTHER pathways. A suite of tools has been built to allow users to browse and query gene functions and analyze large-scale experimental data with a number of statistical tests. PANTHER is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. Since the protocol for using this tool (v.8.0) was originally published in 2013, there have been substantial improvements and updates in the areas of data quality, data coverage, statistical algorithms and user experience. This Protocol Update provides detailed instructions on how to analyze genome-wide experimental data in the PANTHER classification system.

Keywords

GenomeComputer scienceProtocol (science)Phylogenetic treeComputational biologyData miningFunction (biology)GenomicsBiologyGeneGenetics

MeSH Terms

AnimalsDatabasesGeneticGene OntologyGenesGenomicsGenotypeHumansMolecular Sequence AnnotationPhylogenySoftwareStatistics as Topic

Affiliated Institutions

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Publication Info

Year
2019
Type
article
Volume
14
Issue
3
Pages
703-721
Citations
1490
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

1490
OpenAlex
117
Influential

Cite This

Huaiyu Mi, Anushya Muruganujan, Xiaosong Huang et al. (2019). Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nature Protocols , 14 (3) , 703-721. https://doi.org/10.1038/s41596-019-0128-8

Identifiers

DOI
10.1038/s41596-019-0128-8
PMID
30804569
PMCID
PMC6519457

Data Quality

Data completeness: 90%