• Subscribe to the RNA-Seq Blog

  
  

  
  Or subscribe by RSS Reader
  
• 6,801 feed subscribers
• 
  

• Featured Events

  

• 

• 

• Media Partners

  
  

• 

• Polls

  What is the greatest immediate need facing the RNA Sequencing community? (Choose Only One)

  • Continued reduction in cost of sequencing reagents/services
  • Skilled bioinformatics specialists
  • Better (more uniform, less bias, simpler, faster, easier, etc) library preparation protocols
  • A standardized data analysis pipeline
  • More sequencing capacity
  • Further advancement in sequencing technology capabilities (throughput, depth, accuracy, etc)

  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 bioinformatics breast cancer 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 nih pacific biosciences poll results RNA-Seq rnaseq rna sequencing roche small rna 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 Data Visualization 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

  • Nicolas on Computational approaches to the analysis of RNA-seq data
  • Ernesto on Novel amplification based RNA-seq methodology generates highly reproducible sequencing libraries from as low as 25 picograms of mRNA
  • Arrayers on RNA-Seq Data Analysis Tools
  • Brian Haas on Interview – Brian Haas Manager of Genome Annotation, Outreach, Bioinformatics and Analysis Broad Institute
  • Bret on The Magic of RNA-Seq

• Popular Search Terms

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

• Recent Search Terms

  • type of normalization most used for rna seq data
  • rna assembly
  • microRNA ppt
  • long noncoding rna june 2013
  • mapping rna seq
  • Bowtie map RNA-seq
  • Mapping and quantifying mammalian transcriptomes by RNA-Seq
  • y adapter illumina
  • allele specific expression
  • ion torrent pgm transcriptome arabidopsis

• Archives

  • June 2013
  • 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

“RNA-Seq is perhaps the most complex NGS application “

In recent years, the introduction of massively parallel sequencing platforms for Next Generation Sequencing (NGS) protocols, able to simultaneously sequence hundred thousand DNA fragments, dramatically changed the landscape of the genetics studies. RNA-Seq for transcriptome studies, Chip-Seq for DNA-proteins interaction, CNV-Seq for large genome nucleotide variations are only some of the intriguing new applications supported by these innovative platforms. Among them RNA-Seq is perhaps the most complex NGS application. Expression levels of specific genes, differential splicing, allele-specific expression of transcripts can be accurately determined by RNA-Seq experiments to address many biological-related issues. All these attributes are not readily achievable from previously widespread hybridization-based or tag sequence-based approaches. However, the unprecedented level of sensitivity and the large amount of available data produced by NGS platforms provide clear advantages as well as new challenges and issues. This technology brings the great power to make several new biological observations and discoveries, it also requires a considerable effort in the development of new bioinformatics tools to deal with these massive data files. The paper aims to give a survey of the RNA-Seq methodology, particularly focusing on the challenges that this application presents both from a biological and a bioinformatics point of view.

J Biomed Biotechnol – 2010 – Costa V, Angelini C, De Feis I, Ciccodicola A

Incoming search terms:

• next generation sequencing review
• new generation sequencing ppt
• transcriptomes
• next generation sequencing video
• third generation sequencing
• short sequence alignment visualization tools
• seqmonk distribution of insert
• Bioinformatics tools RNA sequence
• role of bioinformatics ppt
• sequencing

Mar 15, 2011, 06:00 ET

Ingenuity Announces RNA-Sequencing Workflow Support and First-of-Its-Kind microRNA Filtering Capability With Latest Release of IPA

PR Newswire – Processed RNA-Seq datasets can now be uploaded directly into IPA and analyzed in the context of pathways and diseases for a rich biological interpretation of the data. This helps researchers quickly and accurately focus on the most important information within their large RNA – Seq datasets quickening…

March 14, 2011 08:30 ET

Partek Expands Global Operations – Software Manufacturer Increases Staff in Europe and Asia

Business Wire – Partek Incorporated, a global leader in bioinformatics software, today announced the expansion of its business development and support staff to keep pace with continued demand for its core product offering, Partek Genomics Suite. The company now has personnel throughout Europe — United Kingdom, France, Germany, Spain and Croatia — and a wholly owned subsidiary in Singapore servicing Asia, Australia and New Zealand.

Feb 23, 2011, 07:30 ET

Life Technologies to Launch Ion 318 Chip in Second Half of 2011 with 1Gb of Data Output

PR Newswire – Life Technologies Corporation (Nasdaq: LIFE) today announced that the Ion 318 semiconductor sequencing chip will be available for early access in September of this year, complete with RNA – Seq kits and analysis software, providing up to 1Gb of data output – 100…

Transcriptome characterization of the South African abalone Haliotis midae using sequencing-by-synthesis

Worldwide, the genus Haliotis is represented by 56 extant species and several of these are commercially cultured. Among the six abalone species found in South Africa, Haliotis midae is the only aquacultured species. Despite its economic importance, genomic sequence resources for H. midae, and for abalone in general, are still scarce. Next generation sequencing technologies provide a fast and efficient tool to generate large sequence collections that can be used to characterize the transcriptome and identify expressed genes associated with economically important traits like growth and disease resistance.¹

Novel and Conserved Micrornas in Dalian Purple Urchin (Strongylocentrotus Nudus) Identified by Next Generation Sequencing

The purple urchin, Strongylocentrotus nudus, is one of the most important marine economic animals that widely distributed in the cold seas along the coasts of eastern pacific area. To date, only 45 microRNAs have been identified in a related species, Strongylocentrotus purpurtus, and there is no report on S. nudus microRNAs. Herein, solexa sequencing technology was used to high throughput sequencing analysis of microRNAs in small RNA library isolated from five tissues of S. nudus.²

1. Franchini P, van der Merwe M, Roodt-Wilding R (2011) Transcriptome characterization of the South African abalone Haliotis midae using sequencing-by-synthesis. BMC Research Notes 4, 59. [article]
2. Wei Z, Liu X, Feng T, Chang Y. (2011) Novel and conserved micrornas in dalian purple urchin (strongylocentrotus nudus) identified by next generation sequencing. Int J Biol Sci 7(2):180-92. [article]

Incoming search terms:

• next generation sequencing in phaseolus vulgaris rna
• transcriptome related species

GenomeView is a next-generation genome browser. This video shows some RNA-seq data from B. anthracis.

Incoming search terms:

• genomeview trinity rnaseq
• somewrong with genomeview
• visualize stranded rna seq

SeqMonk is a program to enable the visualization and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It’s main features are:

• Import of mapped data from text files
• Creation of data groups for visualization and analysis
• Visualization of mapped regions against an annotated genome.
• Flexible quantitation of the mapped data to allow comparisons between data sets
• Statistical analysis of data to find regions of interest
• Creation of reports containing data and genome annotation

Incoming search terms:

• seqmonk
• visualizing RNA-seq data
• differential expression seqmonk
• visualize seq
• visualize rna-seq mappin
• Visualization RNA-Seq data
• visualization of RNA-seq data
• visualization and analysis of mapped sequences
• visualise sequencing coverage
• seqmonk tutorial

ArrayExpressHTS is an R based pipeline for pre-processing, expression estimation and data quality assessment of high-throughput sequencing transcriptional profiling (RNA-seq) datasets. The pipeline starts from raw sequence files and produces standard Bioconductor R objects containing gene or transcript measurements for downstream analysis along with web reports for data quality assessment. It may be run locally on a user’s own computer or remotely on a distributed R-cloud farm at the European Bioinformatics Institute. It can be used to analyse user’s own datasets or public RNA-seq datasets from the ArrayExpress Archive. Read more

Incoming search terms:

• arrayexpresshts
• arrayexpresshts junction reads
• data processing rna seq cloud computing
• data quality assessment blog
• dispersion plots for assessing the quality of RNA seq data

GenePattern – is a powerful genomic analysis platform that provides access to more than 100 tools for gene expression analysis, proteomics, SNP analysis and common data processing tasks.

GenePattern offers a suite of tools to support a wide variety of RNA-seq analyses, including short-read mapping, identification of splice junctions, transcript and isoform detection, quantitation, and differential expression. The modules have been adapted from widely-used tools. GenePattern also provides pipelines that allow you to perform a number of multi-step RNA-seq analyses automatically. Read more

Incoming search terms:

• genepattern rna-seq
• tophat fusion genepattern
• genepatter paper
• genepattern
• genepattern ngs
• RNA-seq alternative splicing in silico full length

We asked: In the Year 2015, what will it cost to perform RNA-Seq (whole transcriptome sequencing – human sample)?

You Answered:

$10	17	13%
$100	40	31%
$500	38	29%
$1,000	25	19%
$2,500	6	5%
$5,000	5	4%

The second wave of next generation sequencing technologies, referred to as single-molecule sequencing (SMS), carries the promise of profiling samples directly without employing polymerase chain reaction steps used by amplification-based sequencing (AS) methods. With the goal of uncovering the merits of both technologies, researchers at the University of Michigan examined mRNA sequencing results from single-molecule and amplification-based sequencing in a set of human cancer cell lines and tissues.

They observed a characteristic coverage bias towards high abundance transcripts in amplification-based sequencing. A larger fraction of AS reads cover highly expressed genes, such as those associated with translational processes and housekeeping genes, resulting in relatively lower coverage of genes at low and mid-level abundance. In contrast, the coverage of high abundance transcripts plateaus off using SMS. Consequently, SMS is able to sequence lower- abundance transcripts more thoroughly, including some that are undetected by AS methods; however, these include many more mapping artifacts.

A better understanding of the technical and analytical factors introducing platform specific biases in high throughput transcriptome sequencing applications will be critical in cross platform meta-analytic studies.

Sam LT, Lipson D, Raz T, Cao X, Thompson J, et al. (2011) A Comparison of Single Molecule and Amplification Based Sequencing of Cancer Transcriptomes. PLoS ONE 6(3), e17305. [article]

Incoming search terms:

• rna seq amplification
• rna amplification for next generation sequencing
• Sequencing Quality Control Consortium
• single molecule sequencing amplification
• amplification bias RNA seq
• single molecule rna-seq
• single molecule sequencing RNA

By Vicki Glaser – Genetic Engineering News

Advanced Technological Approach Generates Genomic Data Better, Faster, and Cheaper

In the next-gen sequencing (NGS) arena, the focus over the past several years has been on technological advances, moving from second-generation to third-generation sequencing strategies and producing research instruments capable of delivering whole-genome sequences in parallel at increasing speed. More recently, as read lengths and coverage continue to increase, throughputs rise, and costs decline, the expanding range of applications of NGS has taken center stage.

…Genomic Health announced results from its next-gen sequencing-driven biomarker discovery program in breast cancer at the recent “Advances in Genome Biology and Technology” (AGBT) meeting. Based on sequencing of the whole human transcriptome in formalin-fixed paraffin-embedded (FFPE) tumor and normal breast tissue samples, the company found hundreds of differences in both coding and noncoding transcripts between the two sample populations. Genomic Health reported an association between specific genes and some non-coding RNAs and risk of breast cancer recurrence.

(read the entire article… )

Incoming search terms:

• next generation sequencing ppt 2012
• NGS applications
• applications ngs
• applications og NGS
• ngs technology ppt

Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Using high-throughput Illumina RNA-seq, the transcriptome from C. sinensis was analyzed at an unprecedented depth.

(read more… )

Shi C et al. (2011) Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds. BMC Genomics [Epub ahead of print]. [article]

Incoming search terms:

• TEA genome
• tea genome project
• tea transcriptome
• Camellia sinensis transcriptome
• tea sequencing
• RNA-SEQ tea
• nTARs transcript sequencing rna-seq
• genes tea plant
• deep sequencing metabolic tea shi
• Camellia sinensis transcriptome data

SeqMap is a tool for identifying viral integration sites from LAM-PCR and LM-PCR analysis. The tool will extract vector sequence data then search existing genome databases for matches to the unique sequences generated by the LAM or LM-PCR reaction. SeqMap displays the vector insertion site graphically, showing the chromosome location and distance to surrounding genes. The tool also allows you to organize your data and make notations. Read more

Incoming search terms:

• seqmap
• bam to seqmap
• lam pcr mapping
• LAM PCR
• seqmap how to
• seqmap manual
• SeqMap tophat

Incoming search terms:

• rna-seq prostate cancer
• in silico ngs data
• ngs and prostate cancer
• prostate cancer ngs

• 

• 

• 

• 

• Social Networking Pages

  

• 

• SEQanswers – RNA Sequencing

  • Unmapped ratio very high on mouse genome June 17, 2013
    Hi, 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, 2013
    Hello 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, 2013
    Hi, 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, 2013
    Hi, 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, 2013
    I have a query regarding what samples should be merged using cuffmerge, when you have multiple phenotypes (each with replicates). Lets say my mouse... […]
    ParthavJailwala
  • cuffdiff - the -c parameter June 12, 2013
    Hello, I'm running cuffdiff for DE. I'm running with -c parameter as 10. I'm gettig test OK, while the raw counts at that locus are lower than... […]
    MayaAM

• Biostar – RNA-Seq

  • Normalising tag count to RPKM
    Hi! 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 terminology
    This 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 coverage
    Hi, 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 counting
    I 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 […]
  • RNA-Seq: novel transcripts found. What next?
    If I were use cufflinks in de novo mode to find transcripts or genes in my data that did not align to known transcripts from UCSC or Ensembl, I wouldn't know what to do downstream of this. How would one go about confirming that these are indeed novel? What sort of validation steps would one take (computational or non-computational), what in-depth inform […]