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May
30
Queensland Centre for Medical Genomics Adopts Illumina Sequencing for Australian ICGC Program
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SAN DIEGO–(BUSINESS WIRE)–Illumina (NASDAQ:ILMN) today announced that the Queensland Centre for Medical Genomics (QCMG), home of Australia’s International Cancer Genomics Consortium program, has established Illumina technology as its core sequencing platform in an expanded facility. The QCMG will replace their fleet of SOLiD/5500 systems with three Illumina HiSeq 2500 systems. This new partnership began in April. (read more…)
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May
29
RNA-Seq to Study Epigenetics of Obesity
Filed Under Press Release | 1 Comment
from the Houston Chronicle
Hangzhou, China (PRWEB) May 29, 2012 – In a new study published online in Nature Communications, researchers from Sichuan Agricultural University and LC Sciences report the miRNAome in porcine adipose and muscle tissues. The report provides a valuable epigenomic source for obesity prediction and prevention and furthers the development of pig as a model organism for human obesity research.
Scientists now know that the genetic code alone isn’t responsible for adult phenotype or even the offspring of these adults. Epigenetics refers to changes in gene expression affecting phenotype that don’t involve changes to the DNA nucleotide sequence itself, and yet are heritable. DNA methylation, histone modification and microRNA (miRNA) expression are examples of epigenetic mechanisms that have recently been identified as important regulators of gene expression in many biological systems.
Obesity is a huge problem worldwide. Recently, the World Health Organization reported that obesity levels doubled in every region of the world between 1980 and 2008, spurring rates of non-communicable diseases such as diabetes and cancer that now account for almost two out of three deaths globally. It has become evident that epigenetic factors, such as DNA methylation and miRNA expression, have essential roles in obesity development. (read more…)
- Li, M. et al. (2012)An atlas of DNA methylomes in porcine adipose and muscle tissues. Nat Commun[Epub ahead of print]. [abstract]
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May
29
RNA-Seq Differential Expression — RNA-Seq Course v1.0 – UC Davis
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May
25
RNA-Seq Study Design calculator
Filed Under Other Tools | Leave a Comment
The purpose of this calculator is to assist with RNA-Seq study design, in particular with the determination of the number of samples required to ensure sufficient statistical power. In general, a paired design will ensure greater power, but at increased cost per biological replicate.
http://voila.prognosysbio.com/studydesigncalc
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May
24
The Emergence of lncRNA
Filed Under Information | 3 Comments
lncRNA Database
Most (~75%) of the catalogued lncRNAs are from mammals, for which more transcriptomic data is available and which have been more intensively studied, but lncRNAs from vertebrates to single-celled eukaryotes have been included. In addition, lncRNAdb has links to the UCSC Genome Browser for visualization and NRED (ncRNA Expression Database) for expression information from a variety of sources.
Macro lncRNAs: A new layer of cis-regulatory information in the mammalian genome.
Guenzl P, Barlow D.
RNA Biol. 2012 Jun 1;9(6). [Epub ahead of print]
Long Noncoding RNA: Its Physiological and Pathological Roles.
Yan B, Wang Z.
DNA Cell Biol. 2012 May 21. [Epub ahead of print]
Regulatory long non-coding RNA and its functions.
Huang Y, Liu N, Wang JP, Wang YQ, Yu XL, Wang ZB, Cheng XC, Zou Q.
J Physiol Biochem. 2012 Apr 26. [Epub ahead of print]
Emerging functional and mechanistic paradigms of mammalian long non-coding RNAs.
Moran VA, Perera RJ, Khalil AM.
Nucleic Acids Res. 2012 Apr 5. [Epub ahead of print]
Exploring long non-coding RNAs through sequencing.
Atkinson SR, Marguerat S, Bähler J.
Semin Cell Dev Biol. 2012 Apr;23(2):200-5. Epub 2011 Dec 20.
The Emergence of lncRNAs in Cancer Biology.
Prensner JR, Chinnaiyan AM.
Cancer Discov. 2011 Oct;1(5):391-407.
Long noncoding RNAs and human disease.
Wapinski O, Chang HY.
Trends Cell Biol. 2011 Jun;21(6):354-61. Epub 2011 May 6.
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May
23
2nd Next Generation Sequencing
Boston, MA – May 30th – 31st
GTC’s 2nd Next Generation Sequencing Conference is a 2-day meeting that will bring together leading technology and diagnostic companies, national laboratories and academic institutions from across the globe to discuss applications of NGS platforms, novel sequencing strategies, developments in nanopore and single molecule sequencing and the implementation of NGS in the clinical space. (read more…)
Next Generation Sequencing
Prague – June 12th – 13th
Informa Life Sciences – Our Next Generation Sequencing conference provides you with the opportunity to hear the latest and most exciting developments in NGS technological advances (including 3rd and 4th generation platforms), sample preparation strategies for difficult samples, and how research, drug/diagnostic discovery and development are utilising next generation sequencing. (read more…)
Next-Gen Sequencing Applications & Translational Technologies Summit
San Francisco, CA – August 6th – 8th
ibc Life Sciences – How are others leveraging the power of next-generation sequencing in everyday research, and for clinical and diagnostic applications? Are you looking to accelerate your discovery and development efforts using translational technologies? (read more…)
NGX: Applying Next-Generation Sequencing
Providence, RI – Aug 13th – 15th
Cambridge Healthtech Institute’s NGX: Applying Next-Generation Sequencing investigates the expanding applications of NGS. Learn from experienced researchers from large sequencing centers, core laboratories, and specialized groups as they share their practical knowledge, real-world experiences and solutions. (read more…)
Next- Generation Sequencing Summit
London, September 17th – 18th
SMi – A data interpretation and analytical perspective. Identifying potential therapeutic drug targets and validating their suitability is a complex process involving numerous experimental platforms, including DNA sequence analysis. (read more…)
Beyond the Genome 2012
Boston, MA – September 27th 29th
Genome Medicine and Genome Biology – The aim of the conference is to discuss next-generation sequencing and other new technologies, informatic tools, and how these are being used to identify common and rare disease-causing mutations in the research laboratory and toward the clinic. Themes will include cancer genomics from discovery sequencing to genome guided therapy, epigenomic technologies and applications, and inherited disease beyond the candidate gene approach. There will also be an informatics workshop. (read more…)
Next Generation Sequencing Congress
London – November 15th-16th
Oxford Global – 2 day conference showcasing cutting edge next generation sequencing platforms, technologies, applications and computational tools for the analysis of NGS sequencing data. (read more…)
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May
23
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May
22
OSA – A fast and accurate alignment tool for RNA-Seq
Filed Under Unspliced Mapping Tools | Leave a Comment
Accurately mapping RNA-Seq reads to the reference genome is a critical step for performing downstream analysis such as transcript assembly, isoform detection and quantification. Many tools have been developed, however, given the huge size of the next generation sequencing (NGS) datasets and the complexity of the transcriptome, RNA-Seq read mapping remains a challenge with the ever-increasing amount of data.
OSA (Omicsoft Sequence Aligner) is a fast and accurate alignment tool for RNA-Seq data. Benchmarked with existing methods, OSA improves mapping speed 4-10 fold with better sensitivity and less false positives.
Availability: OSA can be downloaded from http://omicsoft.com/osa. It is free to academic users. OSA has been tested extensively on Linux, Mac OS X and Windows platforms.
- Hu J, Ge H, Newman M, Liu K. (2012) OSA: A fast and accurate alignment tool for RNA-Seq. Bioinformatics [Epub ahead of print]. [abstract]
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May
21
Accurately and comprehensively mapping millions of relatively short reads to a reference genome sequence can require not only specialized software, but also more structured and automated procedures to manage, analyze, and visualize the data. Additionally, the computational hardware required to efficiently process and store the data can be a necessary and often-overlooked component of a research plan.
Researchers at the University of Missouri Informatics Research Core discuss several aspects of the computational analysis of RNA-Seq, including file management and data quality control, analysis, and visualization. They provide a framework for a standard nomenclature system that can facilitate automation and the ability to track data provenance.
Additionally, they provide a general workflow of the computational analysis of RNA-Aeq and a downloadable package of scripts to automate the processing available at:
http://ircf.rnet.missouri.edu:8000/tech/illumina/dna_sequencing/rnaseq/tophat_pipeline/toolkit
- Givan SA, Bottoms CA, Spollen WG. (2012) Computational Analysis of RNA-seq. Methods Mol Biol 883, 201-19. [abstract]
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May
21
CVRD-Galaxy integrates RNA-Seq methods into a novel Galaxy workflow
Filed Under Analysis Pipelines | Leave a Comment
Liu Bo and Ravi Madduri from the University of Chicago’s Computational Institute, under the guidance of Ian Foster, have increased the analysis capabilities available within the CVRG version of Galaxy. Based upon requirements gathered from members of the NHLBI-funded Progenitor Cell Biology Consortium, Bo and Ravi added the following RNA-Seq tools: Tophat, Cufflinks and its sister applications (cuffcompare, cuffmerge and cuffdiff), and cummeRbund. Following the deployment, Bo and Ravi integrated these tools into an analysis workflow, extending a workflow designed by Benjamin King at Mount Desert Island Biological Laboratory. The workflow gets data from a Globus Online endpoint and processes them with Tophat, Cufflinks and cummeRbund, resulting in a plot produced by cummeRbund. These tools and this workflow are available in the CVRG-Galaxy, running on Amazon EC2, under a research grant from Amazon. CVRG-Galaxy is available through the CVRG Portal.
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May
18
Blog Maintenance
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Welcome back to the RNA-Seq Blog. Due to blog maintenance there was a short outage today, but we are back!
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May
17
Upcoming RNA-Seq Webinar
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Next-Gen Sequencing: Novel Approaches to Automated Sample Prep and Data Analysis for RNA-Seq
| Date: | Wednesday, May 30, 2012 |
| Time: | 1 p.m. Eastern, 10 a.m. Pacific, 7 p.m. Central Europe |
| Duration: | 1 hour |
Webinar Description:
Next Generation Sequencing of DNA provides direct access to genomic information that has enabled researchers to transition away from more complex systems for the interrogation of this information, to direct sequencing of genomes and exomes. More recently the cost-effectiveness and accessibility of such data through the power of next-generation sequencing is being leveraged for other applications such as RNA-Seq, that allows the characterization of the transcriptome at an unprecedented level.
In this webinar, we will present an automated platform for the high throughput processing of extracted RNA via the preparation of high-quality libraries, and describe an easy-to-use, best-practices solution for the analysis of the overwhelming mass of gene expression data generated from Next Gen Sequencing.
Speakers:
Andrew Barry
Product Marketing Manager
PerkinElmer
Hugh Arnold, PhD
Senior Applications Scientist, Geospiza
PerkinElmer
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May
17
Sequencing the Primate Transcriptome
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The Nonhuman Primate Reference Transcriptome Resource (NHPRTR) is a project that was initiated in mid 2010. The concept was to develop a NHP reference transcriptome resource consisting of Next Generation Sequence complete transcriptomes from multiple NHP species. A consortium of primate biologists, molecular biologists, and bioinformatists participate in the development and extension of the NHPRTR. The Steering Committee overseeing the collection, processing, sequencing and assemblies within the resource is composed of Michael Katze of the University of Washington (UW) and Chris Mason of Cornell University (CU) along with Gary Schroth of Illumina.
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SEQanswers – RNA Sequencing- RNAseq (SOLiD) from 18 - 200 nt June 18, 2013We are interested in small non-coding RNAs. Whomever you ask about the size range of small RNAs, you get a different answer. ;) Lets assume, small... […]GenomicIBK
- Unmapped ratio very high on mouse genome June 17, 2013Hi, My problem regards RNA-Seq data. I've downloaded public data (SAGE libs w/ 6 different samples from mouse liver ) to analyse using ArrayStudio.... […]le.nono
- RNASeq: Read length different from expected June 17, 2013Hello all, I have received paired-end reads for 40 samples. The reads are supposed to be 100bp per end. Instead, 20 of my samples are 101bp per... […]gogodidi
- How to install xgawk June 16, 2013Hi, This is Shrujan, i have a problem while running RNA Sequencing QC. It shows an error that xgawk is not found. So please help me installing... […]shrujan
- RNA Sequencing QC Error while using with Sequence_QC.sh file June 15, 2013Hi, This is Shrujan kumar Madadha, I had an error while running QC for Drosophila Yukuba fastq RNA file using Sequence_QC.sh file of FASTX... […]shrujan
- Cuffmerge related query June 12, 2013I have a query regarding what samples should be merged using cuffmerge, when you have multiple phenotypes (each with replicates). Lets say my mouse... […]ParthavJailwala
- RNAseq (SOLiD) from 18 - 200 nt June 18, 2013
- Biostar – RNA-Seq
- edgeR: very low p-value and very high variance within the group of replicates. What's my problem??I'm using edgeR in order to perform differential expression analysis from RNA-seq experiment. I have 6 samples of tumor cell, same tumor and same treatment: 3 patient with good prognosis and 3 patient with bad prognosis. I want to compare the gene expression among the two groups. I ran the edgeR pakage like follow: x […]
- Normalising tag count to RPKMHi! I was wondering if their is a way to normalise the number of reads in a region and the RPKM of the nearest gene to that region, so that a correlation could be computed. Like the following data shows number of tags in first column and RPKM in second column Tags RPKM 15 0.14619 11 0 203 0.2259 129 10.701 300 7.0772 122 2.3234 346 10.666 77 3.117 201 16.749 […]
- a simple question on RNA-Seq terminologyThis question may be very simple and basic, but I just need to confirm that I understand the differences among those terminologies in the RNA-Seq context. Suppose I have a sample called SLR, and it is sequenced on 5 lanes, so I have (among other output files) BAM files like L1_SLR, L2_SLR, L3_SLR, L5_SLR and L7_SLR.bam. Here, the letter "L" denotes […]
- FInding regions of interest with minimum coverageHi, I have a bam file of all my accepted hits (tophat output) and an gtf file with my genes of interest for which I am trying to find potential antisense transcripts. I would like to create a list - preferably one that can be visualized in a genome browser - that shows all genes that have antisense reads in the accepted hits.bam file provided that there are […]
- How to remove the intronic reads before countingI got RNASeq data in several samples. I checked the FastQC, seems the read quality are good (Hiseq 2000). But the problem is many reads are mapped to intronic region, and the regions have no any reference exons there (Refseq, ensembl, gencode). We don't know what they are. We guess the problem happend in library preparation, the concentration was low. N […]
- Which strand of the mRNA molecule does the sequencer output as a "read"?In Illumina Stranded RNA-Seq (using the dUTP method), do the final reads in the fastq files correspond to the initial molecule (that was transcribed), or to the reverse complement of the molecule? C […]
- edgeR: very low p-value and very high variance within the group of replicates. What's my problem??