MethylCoder: software pipeline for bisulfite-treated sequences

MOTIVATION: MethylCoder is a software program that generates per-base methylation data given a set of bisulfite-treated reads. It provides the option to use either of two existing short-read aligners, each with different strengths. It accounts for soft-masked alignments and overlapping paired-end reads. MethylCoder outputs data in text and binary formats in addition to the final alignment in SAM format, so that common high-throughput sequencing tools can be used on the resulting output. It is more flexible than existing software and competitive in terms of speed and memory use. AVAILABILITY: MethylCoder requires only a python interpreter and a C compiler to run. Extensive documentation and the full source code are available under the MIT license at: https://github.com/brentp/methylcode. CONTACT: bpederse@gmail.com.     

The antibiotic R&D pipeline: an update

There is an urgent need for new antibacterials to target emerging multidrug-resistant bacteria. The need for such agents is rising while the efforts in antibacterial research have declined dramatically in the past few decades with the result of only four compounds belonging to new chemical classes being approved for clinical use. The main reasons that led to this critical situation are shortly described. A renewed interest in the research of new effective antimicrobials is nonetheless delivering compounds deriving mainly from modification of existing drugs, yet new chemical classes are appearing. Because many of these activities have started relatively recently, we should expect a long period before new antibiotics are added to the medical armamentarium.     

PseudoPipe: an automated pseudogene identification pipeline

MOTIVATION: Mammalian genomes contain many 'genomic fossils' i.e. pseudogenes. These are disabled copies of functional genes that have been retained in the genome by gene duplication or retrotransposition events. Pseudogenes are important resources in understanding the evolutionary history of genes and genomes. RESULTS: We have developed a homology-based computational pipeline ('PseudoPipe') that can search a mammalian genome and identify pseudogene sequences in a comprehensive and consistent manner. The key steps in the pipeline involve using BLAST to rapidly cross-reference potential "parent" proteins against the intergenic regions of the genome and then processing the resulting "raw hits" -- i.e. eliminating redundant ones, clustering together neighbors, and associating and aligning clusters with a unique parent. Finally, pseudogenes are classified based on a combination of criteria including homology, intron-exon structure, and existence of stop codons and frameshifts.     

Q & A: Alexander Varshavsky

Alexander Varshavsky is Smits Professor of Cell Biology at the California Institute of Technology. He moved to Caltech in 1992, after 15 years at the MIT's Department of Biology. He was born and educated in Russia, and was 30 at the time of his emigration to the U.S. in 1977. In Russia, and for a while at MIT, he studied the structure and replication of chromosomes. Over the last 24 years, the work of his laboratory focused on the ubiquitin system and closely related fields. He is a member of the U.S. National Academy of Sciences, and has received the Gairdner Award, the Lasker Award, the General Motors Sloan Prize, the Wolf Prize, the Horwitz Prize, and the Wilson Medal.     

Q & A: the Snyderome

Michael Snyder answers Genome Biology's questions on the human and professional stories underlying his Snyderome integrative omics project.