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.

MOTIVATION: When targeted to a barcoding region, high-throughput sequencing can be used to identify species or operational taxonomical units from environmental samples, and thus to study the diversity and structure of species communities. Although there are many methods which provide confidence scores for assigning taxonomic affiliations, it is not straightforward to translate these values to unbiased probabilities. We present a probabilistic method for taxonomical classification (PROTAX) of DNA sequences. Given a pre-defined taxonomical tree structure that is partially populated by reference sequences, PROTAX decomposes the probability of one to the set of all possible outcomes. PROTAX accounts for species that are present in the taxonomy but that do not have reference sequences, the possibility of unknown taxonomical units, as well as mislabeled reference sequences. PROTAX is based on a statistical multinomial regression model, and it can utilize any kind of sequence similarity measures or the outputs of other classifiers as predictors. RESULTS: We demonstrate the performance of PROTAX by using as predictors the output from BLAST, the phylogenetic classification software TIPP, and the RDP classifier. We show that PROTAX improves the predictions of the baseline implementations of TIPP and RDP classifiers, and that it is able to combine complementary information provided by BLAST and TIPP, resulting in accurate and unbiased classifications even with very challenging cases such as 50% mislabeling of reference sequences. AVAILABILITY AND IMPLEMENTATION: Perl/R implementation of PROTAX is available at http://www.helsinki.fi/science/metapop/Software.htm CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: DivBayes is a program to estimate diversification rates from species richness and ages of a set of clades. SubT estimates diversification rates from node heights within a clade. Both programs implement Bayesian statistics and provide the ability to account for uncertainty in the ages of taxa in the underlying data, an improvement over more commonly used maximum likelihood methods. AVAILABILITY: DivBayes and SubT are released as C++ source code under the GNU GPL v. 3 software license in Supplementary information 1 and 2, respectively, and at http://web.utk.edu/~kryberg/. They have been successfully compiled on various Linux, MacOS X and Windows systems. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: During the last few years, DNA sequence analysis has become one of the primary means of taxonomic identification of species, particularly so for species that are minute or otherwise lack distinct, readily obtainable morphological characters. Although the number of sequences available for comparison in public databases such as GenBank increases exponentially, only a minuscule fraction of all organisms have been sequenced, leaving taxon sampling a momentous problem for sequence-based taxonomic identification. When querying GenBank with a set of unidentified sequences, a considerable proportion typically lack fully identified matches, forming an ever-mounting pile of sequences that the researcher will have to monitor manually in the hope that new, clarifying sequences have been submitted by other researchers. To alleviate these concerns, a project to automatically monitor select unidentified sequences in GenBank for taxonomic progress through repeated local BLAST searches was initiated. Mycorrhizal fungi--a field where species identification often is prohibitively complex--and the much used ITS locus were chosen as test bed. RESULTS: A Perl script package called emerencia is presented. On a regular basis, it downloads select sequences from GenBank, separates the identified sequences from those insufficiently identified, and performs BLAST searches between these two datasets, storing all results in an SQL database. On the accompanying web-service http://emerencia.math.chalmers.se, users can monitor the taxonomic progress of insufficiently identified sequences over time, either through active searches or by signing up for e-mail notification upon disclosure of better matches. Other search categories, such as listing all insufficiently identified sequences (and their present best fully identified matches) publication-wise, are also available. DISCUSSION: The ever-increasing use of DNA sequences for identification purposes largely falls back on the assumption that public sequence databases contain a thorough sampling of taxonomically well-annotated sequences. Taxonomy, held by some to be an old-fashioned trade, has accordingly never been more important. emerencia does not automate the taxonomic process, but it does allow researchers to focus their efforts elsewhere than countless manual BLAST runs and arduous sieving of BLAST hit lists. The emerencia system is available on an open source basis for local installation with any organism and gene group as targets.

MOTIVATION: The prevalent use of similarity searches like BLAST to identify sequences and species implicitly assumes the reference database to be of extensive sequence sampling. This is often not the case, restraining the correctness of the outcome as a basis for sequence identification. Phylogenetic inference outperforms similarity searches in retrieving correct phylogenies and consequently sequence identities, and a project was initiated to design a freely available script package for sequence identification through automated Web-based phylogenetic analysis. RESULTS: Three CGI scripts were designed to facilitate qualified sequence identification from a Web interface. Query sequences are aligned to pre-made alignments or to alignments made by ClustalW with entries retrieved from a BLAST search. The subsequent phylogenetic analysis is based on the PHYLIP package for inferring neighbor-joining and parsimony trees. The scripts are highly configurable. AVAILABILITY: A service installation and a version for local use are found at http://andromeda.botany.gu.se/galaxiewelcome.html and http://galaxie.cgb.ki.se

BACKGROUND: Research involving expressed sequence tags (ESTs) is intricately coupled to the existence of large, well-annotated sequence repositories. Comparatively complete and satisfactory annotated public sequence libraries are, however, available only for a limited range of organisms, rendering the absence of sequences and gene structure information a tangible problem for those working with taxa lacking an EST or genome sequencing project. Paralogous genes belonging to the same gene family but distinguished by derived characteristics are particularly prone to misidentification and erroneous annotation; high but incomplete levels of sequence similarity are typically difficult to interpret and have formed the basis of many unsubstantiated assumptions of orthology. In these cases, a phylogenetic study of the query sequence together with the most similar sequences in the database may be of great value to the identification process. In order to facilitate this laborious procedure, a project to employ automated phylogenetic analysis in the identification of ESTs was initiated. RESULTS: galaxieEST is an open source Perl-CGI script package designed to complement traditional similarity-based identification of EST sequences through employment of automated phylogenetic analysis. It uses a series of BLAST runs as a sieve to retrieve nucleotide and protein sequences for inclusion in neighbour joining and parsimony analyses; the output includes the BLAST output, the results of the phylogenetic analyses, and the corresponding multiple alignments. galaxieEST is available as an on-line web service for identification of fungal ESTs and for download / local installation for use with any organism group at http://galaxie.cgb.ki.se/galaxieEST.html. CONCLUSIONS: By addressing sequence relatedness in addition to similarity, galaxieEST provides an integrative view on EST origin and identity, which may prove particularly useful in cases where similarity searches return one or more pertinent, but not full, matches and additional information on the query EST is needed.