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From Raw Sequence Data To mining Functional Information From Gene Lists Using Galaxy And R

The workshop is currently full. However, if there is enough demand we will offer it again. So if you are interested in attending, please fill in the information here. Also, people on the waiting list will receive the first opportunity to sign up for the next workshop!

Dates: June 3^rd, 4^th, 6^th & 7^th, 2013

Time: 1 pm – 5 pm

Location: 607 IGB – University of Illinois High-Performance Biological Computing

Workshop description: This is a 4-day workshop for RNA-Seq data analysis using the Galaxy interface and R. It will cover experimental design, evaluation of sequencing data, genome alignment, gene count extraction, statistical analysis to find differential expression and data mining. Data mining will include annotation of gene lists, Venn diagrams, heatmaps. The workshop will use the local Galaxy instance and open-source R and Bioconductor packages (no prior experience with Galaxy or R is necessary). Read more

Incoming search terms:

• miRNAs bioconductor
• pipeline for differential expression with galaxy
• R walpepar
• tophat bioconductor
• www rna-seqblog com workshop-on-rna-seq-data-analysis

Centro di Biotecnologie Molecolari, Via Nizza 52, Torino, Italy, 27-28 March 2013

Next Generation Sequencing platforms changes the conventional view of transcript analysis. Massive Parallel Sequencing methods (MPS) can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs.

This hands-on course is organized by B&Gu with guest speakers from Illumina , Singapore Immunology Network and Polytechnic of Torino. The course is suitable for biologists who are new to RNA-seq technology. Additionally, if you have analyzed gene expression data from microarrays and would now like to do projects using RNA-seq technology, then this workshop will enable you to gather information on the critical issue on RNA-seq from sample prep to data analysis.

The course is based on the use of Bioconductor open-source software. However, R coding skill is not required since all the analyses are done using oneChannelGUI, a graphical interface to Bioconductor tools, designed for life scientists who are not familiar with R language.

Knowledge of statistics is not necessary prior to attending the course.

Further course information, agenda and logistics can be found in the course booklet.

(more info…)

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• R biocondutor

htSeqTools is a Bioconductor package with quality assessment, processing and visualization tools for high-throughput sequencing data, with emphasis in ChIP-seq and RNA-seq studies. It includes detection of outliers and biases, inefficient immuno-precipitation and overamplification artifacts, de novo identification of read-rich genomic regions and visualization of the location and coverage of genomic region lists.

Availability: http://watson.nci.nih.gov/bioc_mirror/packages/2.9/bioc/html/htSeqTools.html

Contact: david.rossell@irbbarcelona.org

• Planet E, Stephan-Otto Attolini C, Reina O, Flores O, Rossell D. (2011) htSeqTools: High-Throughput Sequencing Quality Control, Processing and Visualization in R. Bioinformatics [Epub ahead of print]. [abstract]

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Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, more than 460 packages, and an active user community. Read more

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Technical Guides

• RNA-Seq Technical Guide – From Genomeweb. A panel of experts answer questions regarding RNA-Seq experiments.

Discussion Forums

• The RNA-Seq Blog – A discussion forum for all things transcriptomic.
• SEQanswers – The next-generation sequencing community – threads tagged with RNA-Seq.

Webinars

• An Illumina-Demonstrated Method for Sequencing the Complete Transcriptome -  Session will introduce an improved solution for the reduction of abundant transcripts in RNA-Seq experiments, based on an Illumina-optimized protocol utilizing duplex-specific nuclease (DSN) from Evrogen. Illumina scientists will provide a brief overview of DSN, will describe the enhancements made to the DSN workflow to optimize its performance for Illumina RNA-Seq, and will demonstrate its utility in a wide range of applications, including ncRNA discovery and FFPE transcriptome profiling.

RNA-Seq Data Analysis Tools

• rQuant.web – is a web service to provide convenient access to tools for the quantitative analysis of RNA-Seq data. It allows to determine abundances of multiple transcripts per gene locus from RNA-Seq measurements. rQuant.web is available free of charge, to all users as a tool in a Galaxy installation. 
• Scripture – is a method for transcriptome reconstruction that relies solely on RNA-Seq reads and an assembled genome to build a transcriptome ab initio.
• Cufflinks – assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one.
• SpliceMap – SpliceMap is a de novo splice junction discovery tool. It offers high sensitivity and support for arbitrarily long RNA-seq read lengths.
• TopHat – is a fast splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to mammalian-sized genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons.
• PALMapper – a combination of the spliced alignment method QPALMA with the short read alignment tool GenomeMapper. The resulting method, called PALMapper, efficiently computes both spliced and unspliced alignments at high accuracy while taking advantage of base quality information and splice site predictions.
• RNA-MATE – A recursive mapping strategy for high-throughput RNA-sequencing data.
• ERANGE – Mapping and Quantifying Mammalian Transcriptomes by RNA-Seq
• SeqMap – A Tool For Mapping Millions Of Short Sequences To The Genome.
• Bioconductor – Bioconductor is an open source and open development software project for the analysis and comprehension of genomic data.
• BWA – BWA is a fast light-weighted tool that aligns relatively short sequences (queries) to a sequence database (targe), such as the human reference genome.
• CisGenome – An integrated tool for tiling array, ChIP-seq, genome and cis-regulatory element analysis.
• 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. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.
• Galaxy – Mapping pipeline for Illumina, 454, and SOLiD sequencing data.
• MAQ – stands for Mapping and Assembly with Quality It builds assembly by mapping short reads to reference sequences.
• UCSC Genome Browser – This site contains the reference sequence and working draft assemblies for a large collection of genomes. It also provides portals to the ENCODE and Neandertal projects.

Incoming search terms:

• seq web
• rquant
• chip-seq fastqc to cisgenome
• s eq uen
• RNA-seq websites
• rna seq questions
• rna seq question
• resource for learning rna seq
• mtdna rna-seq seq answers
• cisgenome protocol

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• SEQanswers – RNA Sequencing

  • How to increase rowsize in heatmap? May 16, 2013
    Hi, I am a complete newbie to all things cummeRbund and am currently fighting with generating readable heatmaps. When I use ... […]
    Mags
  • novoalign mapping May 15, 2013
    Hi, I want to use novoalign to map reads - allowing up to 15 mismatches for 100 bp paired-end reads I am new to novoalign(went through the... […]
    abh
  • Design of expt across multiple lanes May 15, 2013
    Hi, I am performing an RNA-seq experiment to look at differential expression. The design is as follows: 2 populations x 3 biological... […]
    jbono
  • RNA kinds expected in RNA-seq results May 15, 2013
    Hi, We use RNA isolation and library preparation protocols which capture polyadenylated RNA. My question is what kinds of RNA can we expect to... […]
    Kocur
  • Discrepancy between genotype and expressed alleles May 15, 2013
    Hi all, I am working on the analysis of allele-specific expression using both genotype information and RNA-seq data from the same individuals. I... […]
    RedMary
  • Does Cufflinks Give Me Trascriptomes? May 14, 2013
    Hi Everyone, I'm a beginner in this area, please forget any silly question. My situation is that I have a raw scaffold whole genome... […]
    hchang10

• Biostar – RNA-Seq

  • 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 tag, which is useful for subsequent analyses, such as annotation. However, does this information influence the "mappability" of reads, or is this unaffected? My guess is that the information will be considered for mapping […]
  • 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 […]
  • Cell Type composition in a tissue based on gene marker expression
    I am not sure if the following would even make sense.... Tissues are composed of composite cell types, and often there are studies such as microarray/NGS where we perform a collective sampling of cells from these tissues. Information about the composition (say percentage of cell type) is not taken into consideration. In some case (such as brain/cancer), ther […]
  • Which SNP caller / method to use after aligning RNA-seq with TopHat
    Which SNP caller / method can / should I use after aligning RNA-seq data with TopHat? For genomic data I use GATK, but supposedly it is not just as easy as running GATK on the TopHat RNA-seq data. The team from Broad has no information / documentation on how to use GATK for RNA-seq data. I don't have any variants yet from DNA re-sequencing. […]