VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis.

BACKGROUND: RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. RESULTS: Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. CONCLUSIONS: VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.

BACKGROUND: The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. RESULTS: CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CONCLUSIONS: CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.

Thermal reactionomes reveal divergent responses to thermal extremes in warm and cool-climate ant species.

BACKGROUND: The distributions of species and their responses to climate change are in part determined by their thermal tolerances. However, little is known about how thermal tolerance evolves. To test whether evolutionary extension of thermal limits is accomplished through enhanced cellular stress response (enhanced response), constitutively elevated expression of protective genes (genetic assimilation) or a shift from damage resistance to passive mechanisms of thermal stability (tolerance), we conducted an analysis of the reactionome: the reaction norm for all genes in an organism's transcriptome measured across an experimental gradient. We characterized thermal reactionomes of two common ant species in the eastern U.S, the northern cool-climate Aphaenogaster picea and the southern warm-climate Aphaenogaster carolinensis, across 12 temperatures that spanned their entire thermal breadth. RESULTS: We found that at least 2 % of all genes changed expression with temperature. The majority of upregulation was specific to exposure to low temperatures. The cool-adapted A. picea induced expression of more genes in response to extreme temperatures than did A. carolinensis, consistent with the enhanced response hypothesis. In contrast, under high temperatures the warm-adapted A. carolinensis downregulated many of the genes upregulated in A. picea, and required more extreme temperatures to induce down-regulation in gene expression, consistent with the tolerance hypothesis. We found no evidence for a trade-off between constitutive and inducible gene expression as predicted by the genetic assimilation hypothesis. CONCLUSIONS: These results suggest that increases in upper thermal limits may require an evolutionary shift in response mechanism away from damage repair toward tolerance and prevention.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

BACKGROUND: Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. RESULTS: We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. CONCLUSION: The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Advanced biofilm analysis in streams receiving organic deicer runoff.

Prolific heterotrophic biofilm growth is a common occurrence in airport receiving streams containing deicers and anti-icers, which are composed of low-molecular weight organic compounds. This study investigated biofilm spatiotemporal patterns and responses to concurrent and antecedent (i.e., preceding biofilm sampling) environmental conditions at stream sites upstream and downstream from Milwaukee Mitchell International Airport in Milwaukee, Wisconsin, during two deicing seasons (2009-2010; 2010-2011). Biofilm abundance and community composition were investigated along spatial and temporal gradients using field surveys and microarray analyses, respectively. Given the recognized role of Sphaerotilus in organically enriched environments, additional analyses were pursued to specifically characterize its abundance: a consensus sthA sequence was determined via comparison of whole metagenome sequences with a previously identified sthA sequence, the primers developed for this gene were used to characterize relative Sphaerotilus abundance using quantitative real-time PCR, and a Sphaerotilus strain was isolated to validate the determined sthA sequence. Results indicated that biofilm abundance was stimulated by elevated antecedent chemical oxygen demand concentrations, a surrogate for deicer concentrations, with minimal biofilm volumes observed when antecedent chemical oxygen demand concentrations remained below 48 mg/L. Biofilms were composed of diverse communities (including sheathed bacterium Thiothrix) whose composition appeared to shift in relation to antecedent temperature and chemical oxygen demand. The relative abundance of sthA correlated most strongly with heterotrophic biofilm volume (positive) and dissolved oxygen (negative), indicating that Sphaerotilus was likely a consistent biofilm member and thrived under low oxygen conditions. Additional investigations identified the isolate as a new strain of Sphaerotilus montanus (strain KMKE) able to use deicer components as carbon sources and found that stream dissolved oxygen concentrations related inversely to biofilm volume as well as to antecedent temperature and chemical oxygen demand. The airport setting provides insight into potential consequences of widescale adoption of organic deicers for roadway deicing.

Automating Installation of the Integrating Biology and the Bedside (i2b2) Platform.

Informatics for Integrating Biology and the Bedside (i2b2) is an open source clinical data analytics platform used at more than 150 institutions for querying patient data. An i2b2 installation (called hive) comprises several i2b2 cells that provide different functionalities. Given the complex architecture of i2b2 installation, creating a working installation of the platform is challenging for new users. This is despite the availability of extensive documentation for i2b2 and access to a large and active mailing list community of i2b2 users. To address this problem, we have created an automated installation package, called i2b2-quickstart, which automatically downloads the latest i2b2 source code and dependencies, and compiles and configures the i2b2 cells to create a functional i2b2 hive installation. This package will serve as a convenient starting point and reference implementation that will facilitate researchers in the installation and exploration of the i2b2 platform.