Softberry Releases 80 Free Bioinformatics Programs for Immediate Download by Academic Users. MOUNT KISCO, N.Y. –(BUSINESS WIRE)–Softberry, Inc. announces release of a comprehensive set of biomedical research-oriented software applications for academic users to install and run locally on a limited basis. The programs, already cited in thousands of scientific publications, are available for Linux and Mac OS platforms and focus primarily on genomic and proteomic research. They include tools for analysis of next generation sequencing data: Accurate spliced alignment of RNA-Seq data to a reference genome (ReadsMap), de novo assembly of transcriptome reads into RNA transcripts (TransSeq), genome assembly (OligoZip) and a software package for SNP analysis (SNP-Toolbox). Another group of programs facilitates analysis of genomic sequences: alignment of genomes, bacterial and eukaryotic promoter prediction, discovery of functional/regulatory motifs, splice sites identification and gene prediction.
About Softberry. Featured RNA-Seq Jobs. Internship Available – Product Development – RNA-Seq. Intern Product Development Job Location: Austin, TX The successful candidate will support product development activities for gene expression analysis through next generation sequencing (NGS). The candidate will be required to plan, execute, and clearly document experiments in support of RNA-Seq technology development. Candidates should have a solid educational background in molecular biology or biochemistry as well as some laboratory experience working with nucleic acid isolation and purification. Experience with RT-PCR, siRNA, nucleic acid amplification, or next generation sequencing is a plus. Candidate should be detail-oriented, self-motivated, and display an eagerness to learn. Throughout the course of the internship, the candidate will be trained in nucleic acid sample preparation and extraction techniques from different biological matrices, PCR, nucleic acid characterization, and library preparation for NGS, and .
Typical LocationsAustin, TX Job ID: 12987BR. Genetic screens – RNA-seq into the toolkit. Pacific Biosciences Posts Q4, FY2012 Revenue Decline – Expects 2013 Uptick. Master thesis – Bioinformatics – RNA-Seq analysis. Development of a RNA-seq analysis pipeline for bacterial transcriptomics Introduction/framework ** Recent developments in new high-throughput technologies have revolutionized molecular biology. This technological progress has led to an explosive growth of the biological information (e.g. via DNA sequencing, RNA microarrays, proteomics), creating new opportunities in the field of bioinformatics in order to computationally deal with the dramatic increase of data.
More specifically, the recent availability of next-generation sequencing (NGS) methods has opened up new horizons at the level of gene expression analysis. Where initially NGS applications were mainly focussing on the sequencing of genomic DNA, this technology is now finding its way to be used in transcriptomics studies i.e. However, these high-throughput sequencing methods produce a massive amount of data. Objectives of the project **
Featured RNA-Seq Job – Computational Biologist. The Opportunity: The Morgridge Institute for Research seeks a Computational Biologist to provide bioinformatics support to researchers studying gene expression, epigenomics, proteomics and transcriptional regulation in embryonic stem cells and their differentiated derivatives. This position is part of the bioinformatics team within stem cell pioneer James Thomson’s Regenerative Biology Laboratory of the Morgridge Institute for Research. The following are core responsibilities of this position: Candidate Requirements: We are seeking candidates who have a master’s degree (or a bachelor’s degree plus equivalent experience and education) in computer science, mathematics, bioinformatics, or biological sciences, Ph.D is preferred.
The Organization: The Morgridge Institute for Research benefits the University of Wisconsin–Madison and the citizens of Wisconsin by advancing breakthrough biomedical discoveries to solve important global health challenges and by educating the public about science. Hello from a new RNAseq user. SEQanswers Home. Bioinformatics challenges in de novo transcriptome assembly using short read sequences in the absence of a reference genome sequence. Pacific Biosciences’ Software Upgrade Enhances De Novo Genome Assembly, Variant Calling and cDNA Transcript Analysis. MENLO PARK, Calif., Jan. 29, 2013 (GLOBE NEWSWIRE) — Pacific Biosciences of California, Inc. (Nasdaq:PACB) provider of the PacBio® RS High Resolution Genetic Analyzer, today announced it is releasing a new software upgrade that provides higher quality genome assemblies with near perfect base level accuracy in addition to other key features.
The software upgrade extends the range of projects that uniquely benefit from the company’s Single Molecule, Real-Time (SMRT®) DNA Sequencing method, and will be available to customers for download on January 31st. SMRT Analysis 1.4 includes a new hierarchical de novo genome assembly process (HGAP), which allows researchers to assemble entire microbial and fungal genomes solely using PacBio long reads. As a result, users can generate better assemblies with a single library preparation and fewer SMRT® Cells than previous approaches that also required short-read sequencing technologies or circular consensus sequencing. About Pacific Biosciences. High-Grade Serous Ovarian Adenocarcinoma Transcriptome Sequencing. Genome-Wide Discovery of Small RNAs in Mycobacterium tuberculosis. Scientists at Raffaele Scientific Institute, Italy report a genome-wide characterization of sRNAs in M. tuberculosis integrating experimental and computational analyses.
Global RNA-seq analysis of exponentially growing cultures of M. tuberculosis H37Rv had previously identified 1373 sRNA species. In the present report they show that 258 (19%) of these were also identified by microarray expression. This set included 22 intergenic sRNAs, 84 sRNAs mapping within 5′/3′ UTRs, and 152 antisense sRNAs. Analysis of promoter and terminator consensus sequences identified sigma A promoter consensus sequences for 121 sRNAs (47%), terminator consensus motifs for 22 sRNAs (8.5%), and both motifs for 35 sRNAs (14%). Additionally, the researchers used a computational approach utilizing functional enrichment to identify the pathways targeted by sRNA regulation.
Expression profiles of mRNAs and lncRNAs from RNA-Seq data across 22 human tissues. Analysis of RNA-Seq Data with R/Bioconductor. Next-Generation Sequencing vs. Microarrays. From genengnews.com – by Shawn C. Baker, Ph.D, CSO BlueSEQ (www.blueseq.com)- Reprinted with permission from Genetic Engineering & Biotechnology News (GEN) With recent advancements and a radical decline in sequencing costs, the popularity of next generation sequencing (NGS) has skyrocketed. As costs become less prohibitive and methods become simpler and more widespread, researchers are choosing NGS over microarrays for more of their genomic applications.
Rising maturity in NGS systems and ancillary protocols such as library preparation and data analysis tools have certainly contributed to the increasing popularity among the research community. As outlined in a previous article (GEN Sep 1, 2012; Vol. 32, No. 15), NGS technologies have made great strides both economically and technically, and are gaining in popularity since first appearing on the scene less than a decade ago. Microarrays’ Proven Track Record Time to Make The Switch? Conclusion. RNAmapper – RNA-Seq based mapping and candidate identification of mutations from forward genetic screens. Forward genetic screens have elucidated molecular pathways required for innumerable aspects of life, however identifying the causal mutations from such screens has long been the bottleneck in the process, particularly in vertebrates. Now, researchers at Fred Hutchinson Cancer Research Center have developed an RNA-seq based approach that identifies both the region of the genome linked to a mutation and candidate lesions that may be causal for the phenotype of interest.
They show that their method successfully identifies zebrafish mutations that cause nonsense or missense changes to codons, alter transcript splicing, or alter gene expression levels. Furthermore, they have developed an online accessible or downloadable bioinformatics pipeline allowing for easy implementation of all steps of the method. Overall, they show that RNA-seq is a fast, reliable, and cost effective method to map and identify mutations that will greatly facilitate the power of forward genetics in vertebrate models. LenzLab / RNA-seq-scripts – a collection of small scripts built by the Lenz lab to make RNA sequencing tasks more efficient. PARSES – A Pipeline for Analysis of RNA-Seq. Roche introduces new GS FLX+ software for improved long-read sequencing performance.
First high-throughput sequencing platform to deliver one million reads with read lengths of up to 1000 bp and beyond. Roche announced today the launch and immediate availability of a new software package (v2.8) that significantly improves long-read shotgun sequencing performance on its GS FLX+ System. This system is the first high-throughput sequencing platform to deliver one million reads with accuracy and length that are comparable to traditional Sanger-based methods. The improvements will allow researchers to discover more novel complex genetic variants and uncover the hidden biology in difficult-to-sequence regions of genomes, transcriptomes, and metagenomic samples. The GS FLX+ System and software will be presented today at the American Society for Human Genetics Annual Meeting in San Francisco.
“We have experienced excellent results in our laboratory using the latest GS FLX+ software. About Roche. RNA-Seq Interest Over Time. Presentation – Introduction to RNA-Seq. Bioinformatics – Next Gen Sequencing – Virtual Issue. Bioinformatics has published a Next-Gen Sequencing “Virtual Issue” covering all the sequencing tools that appeared in the journal. We have listed those described as applicable to RNA-Seq. Statistical Inferences for Isoform Expression in RNA-Seq. Hui Jiang and Wing Wong Bioinformatics (2009) 25: 1026–1032 Full Text A toolkit for analysing large-scale plant small RNA datasets Simon Moxon et al. Bioinformatics (2008) 24: 2252-2253 Full Text TopHat: discovering splice junctions with RNA-Seq Cole Trapnell et al. RNA-MATE: A recursive mapping strategy for high-throughput RNA-sequencing data Nicole Cloonan et al. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data Likun Wang et al.
Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data. Supersplat–spliced RNA-seq alignment Douglas Bryant Jnr. et al. RNA-Seq gene expression estimation with read mapping uncertainty Bo Li et al. RNA-Seq Blog – Poll Results. GEN | Genetic Engineering & Biotechnology News - Biotech from Bench to Business. New Methods for HLA typing from RNA-Seq Data. The Human Leukocyte Antigen (HLA) is key to many aspects of human physiology and medicine. All current sequence-based HLA typing methodologies are targeted approaches requiring the amplification of specific HLA gene segments.
Whole genome, exome and transcriptome shotgun sequencing can generate prodigious data but due to the complexity of HLA loci these data have not been immediately informative regarding HLA genotype. Now, two groups have developed new methods for HLA typing from RNA-Seq sequence reads: Scientists at TRON (Translational Oncology at the University Medical Center of the Johannes Gutenberg University, Germany) have developed a new method, seq2HLA, for obtaining an individual’s HLA class I and II type and expression using standard NGS RNA-Seq data1. They have applied seq2HLA to 50 CEU HapMap individuals previously HLA-typed, yielding 100% specificity and 94% sensitivity at a p-value of 0.1 for 2-digit HLA types. USC Team to Use Patch-Clamp, RNA-seq to Study Gene Expression Variability in Single Neurons.
RNA-Seq data release for 1000 genomes samples. Pacific Biosciences Delivers Enhanced DNA Sequencing Chemistry and Software to Help Solve Complex Genetic Problems. Average Read Lengths of 5,000 Bases and Reads as Long as 20,000; PacBio Hosting Workshop at ASHG Annual Meeting MENLO PARK, Calif., Nov. 6, 2012 (GLOBE NEWSWIRE) — Pacific Biosciences of California, Inc. (Nasdaq:PACB) provider of the PacBio® RS High Resolution Genetic Analyzer, today announced the latest enhancements to its DNA sequencing system, the XL release featuring new chemistry and software for extraordinarily long read lengths that average 5,000 bases. Pacific Biosciences’ Single Molecule, Real-Time (SMRT®) sequencing generates reads an order of magnitude longer than other leading DNA sequencing technologies. With the latest advance, the average read length increases 67 percent from 3,000 to 5,000 bases, with some reads as long as 20,000 bases.
The new XL release provides increased read lengths through a combination of chemistry and software. The new chemistry includes a faster polymerase that reads more bases per second. Dr. About Pacific Biosciences. Transcriptomic analysis of ‘Suli’ pear by RNA-Seq. Bud dormancy is a critical developmental process that allows perennial plants to survive unfavorable environmental conditions. Pear is one of the most important deciduous fruit trees in the world, but the mechanisms regulating bud dormancy in this species are unknown.
Because genomic information for pear is currently unavailable, transcriptome and digital gene expression data for this species would be valuable resources to better understand the molecular and biological mechanisms regulating its bud dormancy. A team led by researchers at Zhejiang University, China performed de novo transcriptome assembly and digital gene expression (DGE) profiling analyses of for ‘Suli’ pear (Pyrus pyrifolia white pear group) using the Illumina RNA-seq system. RNA-Seq generated approximately 100 M high-quality reads that were assembled into 69,393 unigenes (mean length = 853 bp), including 14,531 clusters and 34,194 singletons. The diverse applications of RNA-seq for functional genomic studies in Aspergillus fumigatus.
The deep sequencing of an mRNA population, RNA-seq, is a very successful application of next-generation sequencing technologies (NGSTs). RNA-seq takes advantage of two key NGST features: (1) samples can be mixtures of different DNA pieces, and (2) sequencing provides both qualitative and quantitative information about each DNA piece analyzed. A team led by researchers at Vanderbilt University recently used RNA-seq to study the transcriptome of Aspergillus fumigatus, a deadly human fungal pathogen.
Analysis of the RNA-seq data indicates that there are likely tens of unannotated and hundreds of novel genes in the A. fumigatus transcriptome, mostly encoding for small proteins. Inspection of transcriptome-wide variation between two isolates reveals thousands of single nucleotide polymorphisms. Rokas A, Gibbons JG, Zhou X, Beauvais A, Latgé JP. (2012) The diverse applications of RNA-seq for functional genomic studies in Aspergillus fumigatus. Transcriptomics: From Microarrays to RNA-Seq. By Josh P. Roberts at Biocompare When next-gen sequencing exploded onto the scene, it brought in its wake a host of innovations.
Among these is the deep-sequencing of RNA (RNA-Seq), which is giving unprecedented breadth and depth to our understanding of the way cells develop, regulate themselves and each other, and respond to their environment. Although the study of cellular RNA is not new, the scale on which researchers are now undertaking transcriptomic investigations and many of the questions they are now able to ask, would not have been possible with earlier technologies. The transcriptome is commonly defined as “the complete set of transcripts in a cell, and their quantity, for a specific developmental stage or physiological condition.”[1] Transcriptomics can address all or a segment of the transcriptome, from normal or diseased single cells or tissues.
Microarrays Microarrays have been the stalwarts of high-throughput, genome-wide expression investigations since the mid-1990s. Featured Job Listing – Senior Application Scientist – Ingenuity Systems. RNA-Seq Blog – Poll Results. RNA-Seq Blog Poll Results. Industry News. Fluidigm Completes C1™ Single-Cell Auto Prep System Early Access Program. RNA-Seq Analysis Survey. RNA-Seq Blog. Seqnews.net – discover and share news on next-generation sequencing, genomics and biological data analysis.
Featured Job Listing – Global Lead – NGS Core. News – Illumina Announces Sequencing Technology Innovations. Available PhD Research Project – RNA-Seq. Analysts Increase Valuations, Upgrade Illumina. Complex RNA-Seq experiment analysis with SeqMonk. Transcriptomics in the RNA-Seq Era. RNA-SEQ Workshop – Life Technologies. Combinational Usage of Next Generation Sequencing and qPCR for the analysis of tumour samples.
EBI: Next Generation Sequencing Practical Course – RNA-Seq Ensembl gene build. The Latest RNA-Seq Application – Degradome Sequencing. GitHub – Shared RNA-Seq Analysis Code. Featured Job – Senior Scientist – Pfizer. Statistics for Genomics – Introduction to RNAseq.