SUMMARY: Sequencing of transposon insertion libraries is used to determine the relative fitness of individual mutants at a large scale. However, there is a lack of tools for specifically analyzing data from such experiments with paired sample designs. Here, we introduce CAFE-Coefficient-based Analysis of Fitness by read Enrichment-a software package that can analyze data from paired transposon mutant sequencing experiments, generate fitness coefficients for each gene and condition and perform appropriate statistical testing on these fitness coefficients. AVAILABILITY AND IMPLEMENTATION: CAFE is implemented in Perl and R. The source code is freely available for download under the MIT License from https://github.com/bengtssonpalme/cafe and http://microbiology.se/software/cafe/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Motivation: Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, no genetic marker gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. This has led to the adoption of a range of genetic markers for DNA metabarcoding. While many taxonomic classification software tools can be re-trained on these genetic markers, they are often designed with assumptions that impair their utility on genes other than the SSU and LSU rRNA. Here, we present an update to Metaxa2 that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data. Results: We evaluated the Metaxa2 Database Builder on 11 commonly used barcoding regions and found that while there are wide differences in performance between different genetic markers, our software performs satisfactorily provided that the input taxonomy and sequence data are of high quality. Availability and implementation: Freely available on the web as part of the Metaxa2 package at http://microbiology.se/software/metaxa2/. Supplementary information: Supplementary data are available at Bioinformatics online.

With decreasing costs of generating DNA sequence data, genome and metagenome projects have become accessible to a wider scientific community. However, to extract meaningful information and visualize the data remain challenging. We here introduce FARAO, a highly scalable software for organization, visualization and integration of annotation and read coverage data that can also combine output data from several bioinformatics tools. The capabilities of FARAO can greatly aid analyses of genomic and metagenomic datasets. AVAILABILITY AND IMPLEMENTATION: FARAO is implemented in Perl and is supported under Unix-like operative systems, including Linux and macOS. The Perl source code is freely available for download under the MIT License from http://microbiology.se/software/farao/ CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.