• Subscribe to the RNA-Seq Blog

  
  

  
  Or subscribe by RSS Reader
  
• 6,064 feed subscribers
• 
  

• Featured Events

  

• 

• 

• Media Partners

  
  

• 

• Polls

  How long have you been involved with RNA Sequencing?

  • Just now learning about RNA-Seq
  • less 1 year
  • more than 1 year
  • more than 2 years
  • more than 3 years
  • more than 4 years
  • more than 5 years

  View Results

   Loading ...
• Search for:

• Data Analysis Tools

  Transcriptome Assembly Tools

  Expression & Quantification

  Unpliced Mapping Tools

  Splicing and Junction Mapping

  Analysis Pipelines

  Clouding Platforms

  Databases

  Other Tools

• Tag Cloud

  allele-specific expression alternative splicing bioconductor bioinformatics breast cancer broad institute chip-seq cloud computing cufflinks Data Analysis data analysis pipeline deep sequencing de novo assembly differential expression encode ensembl expression analysis galaxy gene expression high-throughput sequencing illumina ion torrent junction mapping library preparation life technologies lncrna microarray microarrays microrna mirna next-generation sequencing next-gen sequencing pacific biosciences poll results RNA-Seq rnaseq rna sequencing roche tophat transcriptome transcriptome analysis transcriptome assembly transcriptomes transcriptome sequencing transcriptomics

  WP Cumulus Flash tag cloud by Roy Tanck requires Flash Player 9 or better.

• Categories

  Select Category Advertisers Analysis Pipelines Annotation Clouding Platforms Controls Data Analysis Data Analysis Data Sets Databases Events Expression and Quantification Grants / Funding Industry News Information Jobs Library Preparation Methods News Other Tools Patents Pathway Analysis Poll Results Presentations Press Release Publications Reader Conributions Request for RNA-Seq Services Review Sequencing Protocols SNP Detection Splicing and Junction Mapping Statistical Analysis Transcriptome Assembly Tools Transcriptome Sequenced Uncategorized Unspliced Mapping Tools Web Tools Workflow
• 
  
  

• Recent Comments

  • Brian Haas on Interview – Brian Haas Manager of Genome Annotation, Outreach, Bioinformatics and Analysis Broad Institute
  • Bret on The Magic of RNA-Seq
  • Bob Copeman on RobiNA – a user-friendly, integrated software solution for RNA-Seq-based transcriptomics
  • Oz Solomon on Expression Analysis Announces 2013 Grant Program
  • Dr. Jayakishan Meher on Bioinformatics postdoctoral research fellowship available

• Popular Search Terms

  • grape
  • tirthadipa pradhan
  • rna seq analysis
  • rna-seq analysis
  • next generation sequencing ppt
  • rna seq data analysis
  • rna seq vs microarray
  • wine grapes
  • RSEM
  • mangrove

• Recent Search Terms

  • mirna ngs data analysis galaxy
  • The RNA-seq Tuxedo pipeline
  • rna seq pipeline
  • degradome sequencing
  • shrimp genome
  • rna-seq tools
  • post doc position bioinformatics 2013
  • the simple fool\s guide to population genomics via rna-seq
  • rna-seq coverage vs
  • rna sequencing protocol

• Archives

  • May 2013
  • April 2013
  • March 2013
  • February 2013
  • January 2013
  • December 2012
  • November 2012
  • October 2012
  • September 2012
  • August 2012
  • July 2012
  • June 2012
  • May 2012
  • April 2012
  • March 2012
  • February 2012
  • January 2012
  • December 2011
  • November 2011
  • October 2011
  • September 2011
  • August 2011
  • July 2011
  • June 2011
  • May 2011
  • April 2011
  • March 2011
  • February 2011
  • January 2011
  • December 2010
  • November 2010
  • October 2010
  • September 2010
  • August 2010
  • July 2010
  • June 2010
  • May 2010
  • April 2010
  • February 2010
  • January 2010
  • January 2009

Incoming search terms:

• aacr 2013 hoadley
• Auswertung Deep sequencing FPKM werten
• expression analysis illumina integrated biology grant
• integrated biology grant from expression analysis
• integrated rnaseq methylation grant 2013
• rna sequencing grants
• www rna-seqblog com expression-analysis-announces-2013-grant-program

EA’s Fourth Annual Grant Contest Co-Sponsored by Illumina, Golden Helix

DURHAM, NC – August 16, 2012 – EA, a Quintiles company, awarded RNA-Seq grants to researchers at Brigham & Women’s Hospital, Washington University in St. Louis, and Erasmus Medical College through the company’s annual grant program, which supports genomic studies with high-potential to improve human health. An independent panel of judges selected the awardees, each of whom will receive EA next-generation sequencing and bioinformatic services, Illumina next-generation sequencing products and Golden Helix tertiary data analysis solutions.

(Read the press release…)

Related Post – Expression Analysis Announces RNA-SEQ Grant Program

Incoming search terms:

• expression analysis rna seq
• grant using rnaseq protocol

DURHAM, N.C.–(BUSINESS WIRE)–EA announced it is working with Golden Helix and Illumina to offer three (3) fully-funded grants for RNA-Seq studies and data analysis to support cutting-edge projects that show promise in identifying genetic elements important to enhance the understanding of disease and improve human health. For the studies selected, Expression Analysis will perform the sequencing and provide primary and secondary data analysis; Golden Helix will provide cloud-based secondary analysis tools and storage, plus end-user tertiary analysis tools; and, Illumina will provide the products required for the study. In all cases, there is no cost to the grant recipients. Read more

Incoming search terms:

• rna seek pipeline ea
• rna sequencing grant

RNA-Seq is becoming the tool of choice for gene expression studies, as it can facilitate the investigation of phenomena beyond the reach of traditional microarrays, such as novel transcripts and isoforms, alternative splice sites, and allele-specific expression. However, this increased power comes with orders of magnitude higher complexity in terms of bioinformatics, data storage, and processing.

Prognosys Biosciences announced Voila!™, a new cloud-based data analysis service for next-generation sequencing data. Voila! will be available initially for RNA sequencing projects that utilize data from Illumina HiSeq and GAIIx next-generation sequencing instruments.

(Read the press release… )

Golden Helix and Expression Analysis announced they will be developing a cloud-based analytic solution to increase adoption of RNA sequencing. Bioinformatic processes will be performed in a service-based cloud compute environment. This offering will address the obstacles of sequence data by providing cloud-based and integrated desktop analysis tools that are scalable, affordable, and simplified.

(Read the press release… )

Appistry, Inc. announced the release of a series of advanced RNA-Seq solutions for the rapid analysis of sequencing data generated by this emerging technology. The TopHat, TopHat-Fusion and MapSplice-based solutions leverage the Ayrris/BIO(TM) high-performance computing platform to foster Personalized Medicine approaches by enabling researchers to process and analyze large volumes of data in a fraction of the time currently required by conventional gene expression profiling technologies. The RNA-Seq solutions were developed by the Appistry Life Sciences Group–recently established to conceptualize and deliver technologies for Next Generation Sequencing.

(Read the press release… )

Incoming search terms:

• human bodymap 2 0 data from illumina review
• cloud rna seq
• rna-seq data storage
• RNA sequencer instruments
• instrument for rna sequencing
• illumina human bodymap 2 0 software
• illumina body map normal
• GAIIX transcriptome seq
• epicentre biotechnologies acquisition revenue
• cloud-based rna-seq

Motivation: High throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq), cell counting. Statistical inference of differential signal in these data needs to take into account their natural variability throughout the dynamic range. When the number of replicates is small, error modeling is needed to achieve statistical power. Read more

Incoming search terms:

• deseq
• Differential gene expression analysis based on the negative binomial distribution
• deseq rnaseq
• rna seq negative binomial distribution
• rna-seq negative binomial
• negative binomial rna-seq
• what is DESeq
• ovation ffpe rna-seq
• Differential gene expression analysis based on the negative bionomial distribution
• rna seq deseq

Expression Analysis – mRNA-Seq is a cDNA sequencing application that generates a more comprehensive, quantitative view of the mRNA portion of the transcriptome. With no probes or primer design needed, RNA-Seq has the potential to provide relatively unbiased sequence information from polyA-tailed RNA for analysis of gene expression, novel transcripts, novel isoforms, alternative splice sites, allele-specific expression, cSNPs, and rare transcripts in a single experiment, depending on read depth.

http://expressionanalysis.com/rnaseq

• 

• 

• 

• 

• Social Networking Pages

  

• 

• SEQanswers – RNA Sequencing

  • CuffDiff strange output May 23, 2013
    Hi, I hope that someone can be so gentle to help me. I'm analizing some data from RNA-Seq with TopHat and Cufflinks and I focus my attention on... […]
    Pruexel
  • cannot away with cuffdiff,incredible May 23, 2013
    Hi,all I have 4(A,B,C,D) sample in 4 times(increasing time),I got diff result in 3 different cuffdiff 1.cuffdiff 3(A,B,C) individual... […]
    upper
  • TopHat extremely low paired mapping rate. PLS HELP! May 22, 2013
    Hey guys, I have some problems with my paried-end RNA seq analysis on Galaxy. As you can see in the bam flagstat output, my tophat alignment rate is... […]
    Felix.Lee
  • Identifying small RNA sequence within whole genome sequence May 21, 2013
    Hi all, I want to know if there are any useful bioinformatic tool to find small RNA sequence within a whole bacteria genome. Thank you in... […]
    Inma
  • standard of clean data May 21, 2013
    Hi all I recently got my prokaryotes RNA-seq data report back. the standard filter steps of the raw data set by our local sequencing center is as... […]
    Pengfei Liu
  • Problem with cummeRbund diffData() May 20, 2013
    Hi all, I'm running Tophat/cufflinks/cuffdiff for differential gene expression and analysis with cummeRbund (v 2.0.0). I'm having an issue with... […]
    Enrique Zudaire

• Biostar – RNA-Seq

  • Why am I getting so many unmapped reads in STAR, classified as "too short"?
    I am currently using STAR to map several Hi-SEQ mRNA runs. I'm having trouble getting a decent amount of reads to map, but I don't really understand why. I'm hoping you can shed some light :) In the final log, only about 50% (or less) of the reads map to the reference. I'm using a GTF in addition to the genome. The unmapped bin that most […]
  • What are the best practices for SNP identification in RNA seq transcriptome data
    I have 20 RICE RNA seq tranascriptome data hiseq 2000 platform paired end reads. I aligned fasta reads with BWA and remove PCR duplicates with PICARD. Later I call SNP with samtools using various parameters. I would like to clarify what parameters should I used while alinging to reference rice genome for looking SNP location 100 bp upstream and 250 bp downst […]
  • How do TopHat options -g , --supress-hits, and Bowtie options interplay?
    Hi, I am currently using TopHat2 to map RNA-seq runs. I think there have been some changes pertaining the -g option. Does anyone know how it works now? I used to think that setting -g would look for n alignments for a given read, report them [if top-scoring] and discard those reads that had more than g [top scoring] alignments. Now, the description sounds mo […]
  • What happened to -k in TopHat for multiple-mapping reads?
    Selecting -g n in tophat does not discard reads mapping more than n, but instead only reports n alignments for those out all all their TOP scoring alignments. I think there used to be an option -k that would allow one to discard reads that topped x alignments -- whatever happened to that? I only see -g in the tophat 2 manual, no reporting options like before […]
  • Does tophat use the library-type information for mapping, or just for the XS flag?
    When I specify library-type to TopHat, i.e., first-strand, second-strand, unstranded, TopHat appends a value + or - to the XS:A flag, which is useful for subsequent analyses, such as annotation. However, does this information actually influence the "mappability" of reads, or is this unaffected? My thinking is that the information would be considere […]
  • Purpose of Y-shaped adapters in Illumina Sequencing?
    Hi all, Y adapters different sequences to be annealed to the 5' and 3' ends of each molecule in a library. The arms of the Y are unique, and the middle part, connected to the DNA fragment, is complementary. What are the advantages of this? My take of this over having fully-complementary adapters (ADAPTER1 - - - - - ADAPTER1) is that: -Upon primer a […]