MetaDEGalaxy: Galaxy workflow for differential abundance analysis of 16s metagenomic data.

Metagenomic sequencing is an increasingly common tool in environmental and biomedical sciences yet analysis workflows remain immature relative to other field such as DNASeq and RNASeq analysis pipelines.  While software for detailing the composition of microbial communities using 16S rRNA marker genes is constantly improving, increasingly researchers are interested in identifying changes exhibited within microbial communities under differing environmental conditions. In order to gain maximum value from metagenomic sequence data we must improve the existing analysis environment by providing accessible and scalable computational workflows able to generate reproducible results. Here we describe a complete end-to-end open-source metagenomics workflow running within Galaxy for 16S differential abundance analysis. The workflow accepts 454 or Illumina sequence data (either overlapping or non-overlapping paired end reads) and outputs lists of the operational taxonomic unit (OTUs) exhibiting the greatest change under differing conditions. A range of analysis steps and graphing options are available giving users a high-level of control over their data and analyses. Additionally, users are able to input complex sample-specific metadata information which can be incorporated into differential analysis and used for grouping / colouring within graphs.  Detailed tutorials containing sample data and existing workflows are available for three different input types: overlapping and non-overlapping read pairs as well as for pre-generated Biological Observation Matrix (BIOM) files. Using the Galaxy platform we developed MetaDEGalaxy, a complete metagenomics differential abundance analysis workflow. MetaDEGalaxy is designed for bench scientists working with 16S data who are interested in comparative metagenomics.  MetaDEGalaxy builds on momentum within the wider Galaxy metagenomics community with the hope that more tools will be added as existing methods mature.

SRA Down Under: Cache and Analysis Platform for Infectious Disease.

SRA, NCBI's Sequence Read Archive, is a valuable resource holding a near definitive collection of the world's collective sequenced reads for academic purposes. Increasingly, these reads are being used for both basic research and clinical investigations. When time is a critical factor in analysis, such as during bacterial outbreaks, the geographical separation between Australia and the offshore NCBI SRA servers can result in significant delays that may have adverse clinical outcomes. To address this, Queensland Genomics commissioned a pilot program for the establishment of a local Australian SRA Cache. Utilizing the hosting capabilities of the NeCTAR Research Cloud, QRIScloud's HTC infrastructure and the MeDiCI data fabric as a storage solution, and the software stack of Cromwell for workflow management, PostgreSQL database for sample and job metadata, and a coordinator Python Flask application, a local cache of seventeen bacterial species was established. Furthermore, the workflow capabilities of Cromwell were leveraged to provide analysis solutions for cached sample data, including quality control and taxonomic profiling, and individual and multiple sample analysis. Moving forward to a broader rollout of increased bacterial species, it was found that the initial storage estimation did not keep up with the exponential increase sequencing reads uploaded to NCBI SRA, which while highlighting the increasing availability and importance in modern research, will need to be addressed.

Running Genomic Analyses in the Cloud.

Genomic testing is rapidly moving into healthcare practice. However it comes with informatics challenges that the healthcare system has not previously faced - the raw data can be hundreds of gigabytes per test, the compute demands can be thousands of CPU hours, and the test can reveal deeply private health-srelated information that can have implications for anyone related to the person tested. While not a panacea, cloud computing has particular properties that can ameliorate some of these difficulties. This paper presents some of the key lessons learned while deploying a set of genomic analyses on cloud computing for Queensland Genomics.

Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia.

EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distributed national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia's capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas-Tools, Data, Standards, Platforms, Compute and Training-are described in this article.

ArachnoServer 3.0: an online resource for automated discovery, analysis and annotation of spider toxins.

Summary: ArachnoServer is a manually curated database that consolidates information on the sequence, structure, function and pharmacology of spider-venom toxins. Although spider venoms are complex chemical arsenals, the primary constituents are small disulfide-bridged peptides that target neuronal ion channels and receptors. Due to their high potency and selectivity, these peptides have been developed as pharmacological tools, bioinsecticides and drug leads. A new version of ArachnoServer (v3.0) has been developed that includes a bioinformatics pipeline for automated detection and analysis of peptide toxin transcripts in assembled venom-gland transcriptomes. ArachnoServer v3.0 was updated with the latest sequence, structure and functional data, the search-by-mass feature has been enhanced, and toxin cards provide additional information about each mature toxin. Availability and implementation: http://arachnoserver.org. Contact: support@arachnoserver.org. Supplementary information: Supplementary data are available at Bioinformatics online.

ArachnoServer 2.0, an updated online resource for spider toxin sequences and structures.

ArachnoServer (www.arachnoserver.org) is a manually curated database providing information on the sequence, structure and biological activity of protein toxins from spider venoms. These proteins are of interest to a wide range of biologists due to their diverse applications in medicine, neuroscience, pharmacology, drug discovery and agriculture. ArachnoServer currently manages 1078 protein sequences, 759 nucleic acid sequences and 56 protein structures. Key features of ArachnoServer include a molecular target ontology designed specifically for venom toxins, current and historic taxonomic information and a powerful advanced search interface. The following significant improvements have been implemented in version 2.0: (i) the average and monoisotopic molecular masses of both the reduced and oxidized form of each mature toxin are provided; (ii) the advanced search feature now enables searches on the basis of toxin mass, external database accession numbers and publication date in ArachnoServer; (iii) toxins can now be browsed on the basis of their phyletic specificity; (iv) rapid BLAST searches based on the mature toxin sequence can be performed directly from the toxin card; (v) private silos can be requested from research groups engaged in venoms-based research, enabling them to easily manage and securely store data during the process of toxin discovery; and (vi) a detailed user manual is now available.