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The current revolution in sequencing technologies allows us to obtain a much more detailed picture of transcriptomes via RNA-Sequencing. We have developed the first integrative online platform, Oqtans, for quantitatively analyzing RNA-Seq experiments. It is based on the Galaxy-framework and provides tools for read mapping, transcript reconstruction and quantitation. Read more

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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. (read more… )

Costa V, Angelini C, De Feis I, Ciccodicola A. (2010) Uncovering the complexity of transcriptomes with RNA-Seq. J Biomed Biotechnol 2010, 853916. [article]

The domestic pig is of enormous agricultural significance and valuable models for many human diseases. Information concerning the pig microRNAome (miRNAome) has been long overdue and elucidation of this information will permit an atlas of microRNA (miRNA) regulation functions and networks to be constructed. Here we performed a comprehensive search for porcine miRNAs on ten small RNA sequencing libraries prepared from a mixture of tissues obtained during the entire pig lifetime, from the fetal period through adulthood. The sequencing results were analyzed using mammalian miRNAs, the precursor hairpins (pre-miRNAs) and the first release of the high-coverage porcine genome assembly (Sscrofa9, April 2009) and the available expressed sequence tag (EST) sequences. 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.

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• SEQanswers – RNA Sequencing

  • 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
  • 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

• 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 […]