HiTRACE-Web: an online tool for robust analysis of high-throughput capillary electrophoresis

To facilitate the analysis of large-scale high-throughput capillary electrophoresis data, we previously proposed a suite of efficient analysis software named HiTRACE (High Throughput Robust Analysis of Capillary Electrophoresis). HiTRACE has been used extensively for quantitating data from RNA and DNA structure mapping experiments, including mutate-and-map contact inference, chromatin footprinting, the EteRNA RNA design project and other high-throughput applications. However, HiTRACE is based on a suite of command-line MATLAB scripts that requires nontrivial efforts to learn, use, and extend. Here we present HiTRACE-Web, an online version of HiTRACE that includes standard features previously available in the command-line version as well as additional features such as automated band annotation and flexible adjustment of annotations, all via a user-friendly environment. By making use of parallelization, the on-line workflow is also faster than software implementations available to most users on their local computers. Free access: http://hitrace.or

Applications and Challenges of Real-time Mobile DNA Analysis

The DNA sequencing is the process of identifying the exact order of nucleotides within a given DNA molecule. The new portable and relatively inexpensive DNA sequencers, such as Oxford Nanopore MinION, have the potential to move DNA sequencing outside of laboratory, leading to faster and more accessible DNA-based diagnostics. However, portable DNA sequencing and analysis are challenging for mobile systems, owing to high data throughputs and computationally intensive processing performed in environments with unreliable connectivity and power. In this paper, we provide an analysis of the challenges that mobile systems and mobile computing must address to maximize the potential of portable DNA sequencing, and in situ DNA analysis. We explain the DNA sequencing process and highlight the main differences between traditional and portable DNA sequencing in the context of the actual and envisioned applications. We look at the identified challenges from the perspective of both algorithms and systems design, showing the need for careful co-design

Rapid, solid-phase based automated analysis of chromatin structure and transcription factor occupancy in living eukaryotic cells

Transcription factors, chromatin components and chromatin modification activities are involved in many diseases including cancer. However, the means by which alterations in these factors influence the epigenotype of specific cell types is poorly understood. One problem that limits progress is that regulatory regions of eukaryotic genes sometimes extend over large regions of DNA. To improve chromatin structure–function analysis over such large regions, we have developed an automated, relatively simple procedure that uses magnetic beads and a capillary sequencer for ligation-mediated-PCR (LM-PCR). We show that the procedure can be used for the rapid examination of chromatin fine-structure, nucleosome positioning as well as changes in transcription factor binding-site occupancy during cellular differentiation

Circlator: automated circularization of genome assemblies using long sequencing reads

The assembly of DNA sequence data is undergoing a renaissance thanks to emerging technologies capable of producing reads tens of kilobases long. Assembling complete bacterial and small eukaryotic genomes is now possible, but the final step of circularizing sequences remains unsolved. Here we present Circlator, the first tool to automate assembly circularization and produce accurate linear representations of circular sequences. Using Pacific Biosciences and Oxford Nanopore data, Circlator correctly circularized 26 of 27 circularizable sequences, comprising 11 chromosomes and 12 plasmids from bacteria, the apicoplast and mitochondrion of Plasmodium falciparum and a human mitochondrion. Circlator is available at http://sanger-pathogens.github.io/circlator/

Wheat rusts never sleep but neither do sequencers: will pathogenomics transform the way plant diseases are managed?

Field pathogenomics adds highly informative data to surveillance surveys by enabling rapid evaluation of pathogen variability, population structure and host genotype

Computational Strategies for Scalable Genomics Analysis.

The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications

DNA sequencing: bench to bedside and beyond†

Fifteen years elapsed between the discovery of the double helix (1953) and the first DNA sequencing (1968). Modern DNA sequencing began in 1977, with development of the chemical method of Maxam and Gilbert and the dideoxy method of Sanger, Nicklen and Coulson, and with the first complete DNA sequence (phage ϕX174), which demonstrated that sequence could give profound insights into genetic organization. Incremental improvements allowed sequencing of molecules >200 kb (human cytomegalovirus) leading to an avalanche of data that demanded computational analysis and spawned the field of bioinformatics. The US Human Genome Project spurred sequencing activity. By 1992 the first ‘sequencing factory’ was established, and others soon followed. The first complete cellular genome sequences, from bacteria, appeared in 1995 and other eubacterial, archaebacterial and eukaryotic genomes were soon sequenced. Competition between the public Human Genome Project and Celera Genomics produced working drafts of the human genome sequence, published in 2001, but refinement and analysis of the human genome sequence will continue for the foreseeable future. New ‘massively parallel’ sequencing methods are greatly increasing sequencing capacity, but further innovations are needed to achieve the ‘thousand dollar genome’ that many feel is prerequisite to personalized genomic medicine. These advances will also allow new approaches to a variety of problems in biology, evolution and the environment