BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of transcriptomes, arising as a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data and uncover relevant biological information. A diversity of tools has been developed to address the multiple aspects of scRNA-seq data analysis. However, an easy-to-use web application capable of conducting all critical steps of scRNA-seq data analysis is still lacking. We present Asc-Seurat, a feature-rich workbench, providing an user-friendly and easy-to-install web application encapsulating tools for an all-encompassing and fluid scRNA-seq data analysis. Asc-Seurat implements functions from the Seurat package for quality control, clustering, and genes differential expression. In addition, Asc-Seurat provides a pseudotime module containing dozens of models for the trajectory inference and a functional annotation module that allows recovering gene annotation and detecting gene ontology enriched terms. We showcase Asc-Seurat's capabilities by analyzing a peripheral blood mononuclear cell dataset. CONCLUSIONS: Asc-Seurat is a comprehensive workbench providing an accessible graphical interface for scRNA-seq analysis by biologists. Asc-Seurat significantly reduces the time and effort required to analyze and interpret the information in scRNA-seq datasets.

The Peer-to-Peer (P2P) model is currently being used for applications that demand great amount of time and space resources, taking advantage of idle and geographically distributed machines. Bioinformatics is a field that requires large amount of computational resources. In this context, we propose a P2P model that executes a particular bioinformatics application, named BLAST. This is a method for comparing two biological sequences at a time. But it requires a great amount of computation, since it compares a big file containing thousands of sequences that are being investigated and a very large database containing millions of biological sequences. We describe in detail the architecture of our framework, and present experiments using real biological data, that were executed on machines available in three institutions of Brazil - University of Brasilia, Catholic University of Brasilia and Embrapa/Genetic Resources and Biotechnology. The obtained results, when comparing the execution of BLAST in this P2P framework and its execution in the best machine of the three institutions, show that our P2P model can efficiently run other bioinformatics applications.

SUMMARY: A web-based application to analyze protein amino acids conservation-Consensus Sequence (ConSSeq) is presented. ConSSeq graphically represents information about amino acid conservation based on sequence alignments reported in homology-derived structures of proteins. Beyond the relative entropy for each position in the alignment, ConSSeq also presents the consensus sequence and information about the amino acids, which are predominant at each position of the alignment. ConSSeq is part of the STING Millennium Suite and is implemented as a Java Applet. AVAILABILITY: http://sms.cbi.cnptia.embrapa.br/SMS/STINGm/consseq/, http://trantor.bioc.columbia.edu/SMS/STINGm/consseq/, http://mirrors.rcsb.org//SMS/STINGm/consseq/, http://www.es.embnet.org/SMS/STINGm/consseq/ and http://www.ar.embnet.org/SMS/STINGm/consseq/