Estimation of alternative splicing isoform frequencies from RNA-Seq data
This algorithm, referred to as IsoEM, is based on disambiguating of information provided by the distribution of insert sizes generated during sequencing library preparation, and takes advantage of base quality scores, strand and read pairing information when available. The open source Java implementation of IsoEM is freely available at http://dna.engr.uconn.edu/software/IsoEM/
BMC Genomics reports the transcriptome sequencing of two new species: Alfalfa and Guppy
Alfalfa, (Medicago sativa [L.] sativa), a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. [abstract]
The guppy (Poecilia reticulata) transcriptome, assembled do novo using 454 sequence reads, is presented and the authors evaluate potential uses of this transcriptome, including detection of sex-specific transcripts and deployment as a reference for gene expression analysis in guppies and a related species. Guppies have been model organisms in ecology, evolutionary biology, and animal behaviour for over 100 years. An annotated transcriptome and other genomic tools will facilitate understanding the genetic and molecular bases of adaptation and variation in a vertebrate species with a uniquely well known natural history. [abstract]
Integromics and Ingenuity expand their co-operation with the integration of a fourth Integromics product to Ingenuity¹s IPA
The SeqSolve analysis software, exclusively designed for Next Generation Sequencing (NGS), performs tertiary level analysis of RNA-seq data at the gene and transcript level for biologically relevant results. Integromics has already integrated three solutions with Ingenuity’s IPA: Integromics Biomarker Discovery(R) for microarray data analysis, RealTime StatMiner(R) for the analysis of qPCR data as well as OmicsHub(R) Proteomics for the analysis and storage of proteomics data.