MOTIVATION: Although the set of currently known viruses has been steadily expanding, only a tiny fraction of the Earth's virome has been sequenced so far. Shotgun metagenomic sequencing provides an opportunity to reveal novel viruses but faces the computational challenge of identifying viral genomes that are often difficult to detect in metagenomic assemblies. RESULTS: We describe a MetaviralSPAdes tool for identifying viral genomes in metagenomic assembly graphs that is based on analyzing variations in the coverage depth between viruses and bacterial chromosomes. We benchmarked MetaviralSPAdes on diverse metagenomic datasets, verified our predictions using a set of virus-specific Hidden Markov Models and demonstrated that it improves on the state-of-the-art viral identification pipelines. AVAILABILITY AND IMPLEMENTATION: Metaviral SPAdes includes ViralAssembly, ViralVerify and ViralComplete modules that are available as standalone packages: https://github.com/ablab/spades/tree/metaviral_publication, https://github.com/ablab/viralVerify/ and https://github.com/ablab/viralComplete/. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Illumina paired-end reads are often used for 16S analysis in metagenomic studies. Since DNA fragment size is usually smaller than the sum of lengths of paired reads, reads can be merged for downstream analysis. In spite of development of several tools for merging of paired-end reads, poor quality at the 3' ends within the overlapping region prevents the accurate combining of significant portion of read pairs. Recently CD-HIT-OTU-Miseq was presented as a new approach for 16S analysis using the paired-end reads, it completely avoids the reads merging process due to separate clustering of paired reads. CD-HIT-OTU-Miseq is a set of tools which are supposed to be successively launched by auxiliary shell scripts. This launch mode is not suitable for processing of big amounts of data generated in modern omics experiments. To solve this issue we created CDSnake - Snakemake pipeline utilizing CD-HIT tools for easier consecutive launch of CD-HIT-OTU-Miseq tools for complete processing of paired end reads in metagenomic studies. Usage of pipeline make 16S analysis easier due to one-command launch and helps to yield reproducible results. RESULTS: We benchmarked our pipeline against two commonly used pipelines for OTU retrieval, incorporated into popular workflow for microbiome analysis, QIIME2 - DADA2 and deblur. Three mock datasets having highly overlapping paired-end 2 × 250 bp reads were used for benchmarking - Balanced, HMP, and Extreme. CDSnake outputted less OTUs than DADA2 and deblur. However, on Balanced and HMP datasets number of OTUs outputted by CDSnake was closer to real number of strains which were used for mock community generation, than those outputted by DADA2 and deblur. Though generally slower than other pipelines, CDSnake outputted higher total counts, preserving more information from raw data. Inheriting this properties from original CD-HIT-OTU-MiSeq utilities, CDSnake made their usage handier due to simple scalability, easier automated runs and other Snakemake benefits. CONCLUSIONS: We developed Snakemake pipeline for OTU-MiSeq utilities, which simplified and automated data analysis. Benchmarking showed that this approach is capable to outperform popular tools in certain conditions.

An amendment to this paper has been published and can be accessed via the original article.

BACKGROUND: De novo RNA-Seq assembly is a powerful method for analysing transcriptomes when the reference genome is not available or poorly annotated. However, due to the short length of Illumina reads it is usually impossible to reconstruct complete sequences of complex genes and alternative isoforms. Recently emerged possibility to generate long RNA reads, such as PacBio and Oxford Nanopores, may dramatically improve the assembly quality, and thus the consecutive analysis. While reference-based tools for analysing long RNA reads were recently developed, there is no established pipeline for de novo assembly of such data. RESULTS: In this work we present a novel method that allows to perform high-quality de novo transcriptome assemblies by combining accuracy and reliability of short reads with exon structure information carried out from long error-prone reads. The algorithm is designed by incorporating existing hybridSPAdes approach into rnaSPAdes pipeline and adapting it for transcriptomic data. CONCLUSION: To evaluate the benefit of using long RNA reads we selected several datasets containing both Illumina and Iso-seq or Oxford Nanopore Technologies (ONT) reads. Using an existing quality assessment software, we show that hybrid assemblies performed with rnaSPAdes contain more full-length genes and alternative isoforms comparing to the case when only short-read data is used.

MOTIVATION: Plasmids are stably maintained extra-chromosomal genetic elements that replicate independently from the host cell's chromosomes. Although plasmids harbor biomedically important genes, (such as genes involved in virulence and antibiotics resistance), there is a shortage of specialized software tools for extracting and assembling plasmid data from whole genome sequencing projects. RESULTS: We present the plasmidSPAdes algorithm and software tool for assembling plasmids from whole genome sequencing data and benchmark its performance on a diverse set of bacterial genomes. AVAILABILITY AND IMPLEMENTATION: plasmidSPAdes is publicly available at http://spades.bioinf.spbau.ru/plasmidSPAdes/ CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

UNLABELLED: Ability to generate large RNA-Seq datasets created a demand for both de novo and reference-based transcriptome assemblers. However, while many transcriptome assemblers are now available, there is still no unified quality assessment tool for RNA-Seq assemblies. We present rnaQUAST-a tool for evaluating RNA-Seq assembly quality and benchmarking transcriptome assemblers using reference genome and gene database. rnaQUAST calculates various metrics that demonstrate completeness and correctness levels of the assembled transcripts, and outputs them in a user-friendly report. AVAILABILITY AND IMPLEMENTATION: rnaQUAST is implemented in Python and is freely available at http://bioinf.spbau.ru/en/rnaquast CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: The analysis of concentrations of circulating antibodies in serum (antibody repertoire) is a fundamental, yet poorly studied, problem in immunoinformatics. The two current approaches to the analysis of antibody repertoires [next generation sequencing (NGS) and mass spectrometry (MS)] present difficult computational challenges since antibodies are not directly encoded in the germline but are extensively diversified by somatic recombination and hypermutations. Therefore, the protein database required for the interpretation of spectra from circulating antibodies is custom for each individual. Although such a database can be constructed via NGS, the reads generated by NGS are error-prone and even a single nucleotide error precludes identification of a peptide by the standard proteomics tools. Here, we present the IgRepertoireConstructor algorithm that performs error-correction of immunosequencing reads and uses mass spectra to validate the constructed antibody repertoires. AVAILABILITY AND IMPLEMENTATION: IgRepertoireConstructor is open source and freely available as a C++ and Python program running on all Unix-compatible platforms. The source code is available from http://bioinf.spbau.ru/igtools. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The recent introduction of next-generation sequencing technologies to antibody studies have resulted in a growing number of immunoinformatics tools for antibody repertoire analysis. However, benchmarking these newly emerging tools remains problematic since the gold standard datasets that are needed to validate these tools are typically not available. RESULTS: Since simulating antibody repertoires is often the only feasible way to benchmark new immunoinformatics tools, we developed the IgSimulator tool that addresses various complications in generating realistic antibody repertoires. IgSimulator's code has modular structure and can be easily adapted to new requirements to simulation. AVAILABILITY AND IMPLEMENTATION: IgSimulator is open source and freely available as a C++ and Python program running on all Unix-compatible platforms. The source code is available from yana-safonova.github.io/ig_simulator. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Next-generation sequencing (NGS) technologies have raised a challenging de novo genome assembly problem that is further amplified in recently emerged single-cell sequencing projects. While various NGS assemblers can use information from several libraries of read-pairs, most of them were originally developed for a single library and do not fully benefit from multiple libraries. Moreover, most assemblers assume uniform read coverage, condition that does not hold for single-cell projects where utilization of read-pairs is even more challenging. We have developed an exSPAnder algorithm that accurately resolves repeats in the case of both single and multiple libraries of read-pairs in both standard and single-cell assembly projects. AVAILABILITY AND IMPLEMENTATION: http://bioinf.spbau.ru/en/spades