User talk:Emilio Palumbo/g2f rna

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http://rnaseq.uoregon.edu/img/image1.png
http://rnaseq.uoregon.edu/img/image1.png
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===Analyses workflow===
===Analyses workflow===
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** block order
** block order
** min/max distance
** min/max distance
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===Input files===
===Input files===
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'''Important note''': Please make sure the contig names for you reference genome and annotation correspond.  
'''Important note''': Please make sure the contig names for you reference genome and annotation correspond.  
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===Gemtools===
===Gemtools===
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The default gemtools RNAseq pipeline is shown [[http://genome.crg.es/~epalumbo/gene2farm/gem-pipeline.pdf here]].
The default gemtools RNAseq pipeline is shown [[http://genome.crg.es/~epalumbo/gene2farm/gem-pipeline.pdf here]].
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Revision as of 05:27, 15 November 2013

Contents

RNAseq

image1.png


Analyses workflow

An example of a standard workflow we use for RNAseq analyses can be seen [here].

Common analyses that can be performed on RNAseq data are:

  • expression quantitative traits loci (eQTL)
  • splicing quantitative traits loci (sQTL)
  • differantial gene/isoform expression


Mapping

Specific variables to consider when mapping RNAseq:

  • intron size
  • overhang (number of bases from each side of the junction that should be covered by a certain read)
  • splice site consensus (canonical, extended, non-canonical)
  • donor/acceptor splice site consensus sequences
  • junction “filtering”:
    • chromosome/strand
    • block order
    • min/max distance


Input files

To perform RNAseq analysis we need:

  • reference genome sequence
  • reference gene annotation
  • sequences

Important note: Please make sure the contig names for you reference genome and annotation correspond.


Gemtools

The [GEM mapper] is a mapping program for next generation sequencing developed in collaboration between CRG and CNAG in Barcelona. Many high-performance standalone programs (splice mapper, concersion tool, etc.) are provided along with the mapper; in general, new algorithms and tools can be easily implemented on the top of these.

[Gemtools] is a powerful set of high-level pipelines which greatly simplifies the use of the GEM mapper. Using gemtools one can index references and/or map several kinds of data from a simple command-line interface, without having to type complicated commands. In particular, gemtools contains a fast and accurate pipeline for mapping RNA-sequencing data.

The default gemtools RNAseq pipeline is shown [here].


Element quantification

  • exon
  • intron
  • splice junction
  • transcript
  • gene

Transcript expression quantification

Transcript quantification is a complex problem. Quantifying the expression of a gene is simple. We just need to count the RNA-seq reads that fall within the exons of this gene. However, to quantify expression of a transcript we can have reads mapping to an exon of the gene where multiple transcripts overlap. The process of assigning a read to a certain transcript is called read deconvolution or isoform expression quantification.

For transcript expression we use [Flux Capacitor] developed at the CRG in Barcelona.


Running the pipeline

The following step are needed to run the gemtools rnaseq pipeline:

  • Genome indexing:
gemtools index -i genome.fa
  • Transcriptome generation and indexing:
gemtools t-index -i genome.gem -a annotation.gtf -m 80

After those steps completed successfully you can run the pipeline:

gemtools rna-pipeline -f sample.fastq.gz -q 33 -i genome.gem -a annotation.gtf -m 110

To run the Flux Capacitor a bam file sorted by genomic position and indexed is needed. To do this two command hav to be run:

samtools sort my_file.bam my_file_sorted
samtools index my_file_sorted.bam

You can then run the transcript quantifications in the following way:

flux-capacitor -i sample.bam -a annotation.gtf -o sample.gtf
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