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deltaRpkm: an R package for a rapid detection of differential gene presence between related bacterial genomes. | LitMetric

AI Article Synopsis

  • Comparative genomics has evolved tools for analyzing genomes, but these methods can be computationally heavy, especially with large datasets typical in surveillance and outbreak detection.
  • The deltaRpkm R package was developed to quickly evaluate differential gene presence between two groups of closely related genomes by calculating RPKM values and identifying genes significantly present in one group.
  • DeltaRpkm is unique as it simplifies the analysis of gene presence in large genomic datasets, making it easier to identify genes linked to specific clinical features, including non-coding genes.

Article Abstract

Background: Comparative genomics has seen the development of many software performing the clustering, polymorphism and gene content analysis of genomes at different phylogenetic levels (isolates, species). These tools rely on de novo assembly and/or multiple alignments that can be computationally intensive for large datasets. With a large number of similar genomes in particular, e.g., in surveillance and outbreak detection, assembling each genome can become a redundant and expensive step in the identification of genes potentially involved in a given clinical feature.

Results: We have developed deltaRpkm, an R package that performs a rapid differential gene presence evaluation between two large groups of closely related genomes. Starting from a standard gene count table, deltaRpkm computes the RPKM per gene per sample, then the inter-group δRPKM values, the corresponding median δRPKM (m) for each gene and the global standard deviation value of m (s). Genes with m >  = 2 ∗ s (standard deviation s of all the m values) are considered as "differentially present" in the reference genome group. Our simple yet effective method of differential RPKM has been successfully applied in a recent study published by our group (N = 225 genomes of Listeria monocytogenes) (Aguilar-Bultet et al. Front Cell Infect Microbiol 8:20, 2018).

Conclusions: To our knowledge, deltaRpkm is the first tool to propose a straightforward inter-group differential gene presence analysis with large datasets of related genomes, including non-coding genes, and to output directly a list of genes potentially involved in a phenotype.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889214PMC
http://dx.doi.org/10.1186/s12859-019-3234-2DOI Listing

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