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TopHat, a popular spliced aligner for RNA-seq experiments has now been succeeded by TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which occur after genomic translocations. TopHat2 combines the ability to discover novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.

Availability: TopHat2 is available at http://ccb.jhu.edu/software/tophat.

• Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. (2013) TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 14(4), R36. [Epub ahead of print]. [abstract]

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Bioinformatics has published a Next-Gen Sequencing “Virtual Issue” covering all the sequencing tools that appeared in the journal.  We have listed those described as applicable to RNA-Seq.

Statistical Inferences for Isoform Expression in RNA-Seq.
Hui Jiang and Wing Wong
Bioinformatics (2009) 25: 1026–1032 Full Text

A toolkit for analysing large-scale plant small RNA datasets
Simon Moxon et al.
Bioinformatics (2008) 24: 2252-2253 Full Text

TopHat: discovering splice junctions with RNA-Seq
Cole Trapnell et al.
Bioinformatics (2009) 25: 1105–1111 Full Text

Read more

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Bellerophontes is a new framework for the detection of fusion transcripts through short paired-end reads which integrates splicing-driven alignment and abundance estimation analysis, producing a more accurate set of reads supporting the junction discovery and taking into account also not annotated transcripts. Bellerophontes performs a selection of putative junctions on the basis of a match to an accurate gene fusion model. Bellerophontes runs on top of TopHat and Cufflinks tools (developed by Trapnell et al.). The analysis is based on the results of TopHat alignment and Cufflinks transcript isoform detection.

AVAILABILITY:  Bellerophontes JAVA/Perl/Bash software implementation is free and available at http://eda.polito.it/bellerophontes/

• Abate F, Acquaviva A, Paciello G, Ficarra E, Ferrarini A, Delledonne M, Soverini S, Martinelli G, Macii E. (2102) Bellerophontes: A RNA-Seq data analysis framework for chimeric transcripts discovery based on accurate fusion model. Bioinformatics [Epub ahead of print]. [abstract]

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• cufflinks alternative splicing
• MATS alternative splicing
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Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions.

This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol’s execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ~1 h of hands-on time.

• Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L. (2012) Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 7(3), 562-78. [article]

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Monday, October 17, 2011 – 9:30am – 1:00pm

VLSCI Boardroom

Topics covered:

• Mapping RNA-seq data using tophat and bowtie,
• Analyzing and comparing transcripts using cufflinks,
• Visualising data using IGV.

You will need to bring your own laptop (Macs and linux machines work better than PCs, but any laptop is OK)

Registration essential: Places are limited. To register, email course coordinator Dr Nathan Hall (below) and please include one or two sentences about the type of NGS research you are doing.

RSVP Email Address for this Event: nhal@unimelb.edu.au

More info: http://www.vlsci.org.au/events/lscc-workshop-rna-seq-analysis

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TopHat-Fusion is an algorithm designed to discover transcripts representing fusion gene products, which result from the breakage and re-joining of two different chromosomes, or from rearrangements within a chromosome. TopHat-Fusion is an enhanced version of TopHat, an efficient program that aligns RNA-seq reads without relying on existing annotation.

Because it is independent of gene annotation, TopHat-Fusion can discover fusion products deriving from known genes, unknown genes and unannotated splice variants of known genes. Using RNA-seq data from breast and prostate cancer cell lines, we detected both previously reported and novel fusions with solid supporting evidence.

TopHat-Fusion is available at http://tophat-fusion.sourceforge.net/.

Kim D, Salzberg SL. (2011) TopHat-Fusion: an algorithm for discovery of novel fusion transcripts. Genome Biol 12(8), R72. [abstract]]

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• Top-Hat algorithms
• top hat algorithm

A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or ‘reads’, can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites. Read more

The accurate mapping of reads that span splice junctions is a critical component of all analytic techniques that work with RNA-seq data. Here is a second generation splice detection algorithm, MapSplice, whose focus is high sensitivity and specificity in the detection of splices as well as CPU and memory efficiency. Read more

Incoming search terms:

• mapsplice
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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
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• chip-seq fastqc to cisgenome

• 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:

• rna seq analysis
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• rnaseq analysis
• rna-seq pipeline
• rna seq analysis software
• RNA-seq data analysis
• rna seq data analysis pipeline
• rna seq data
• rnaseq pipeline

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• SEQanswers – RNA Sequencing

  • RNAseq (SOLiD) from 18 - 200 nt June 18, 2013
    We 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, 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

• 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 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 […]