Difference between revisions of "Kallisto"
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It's the new (2015) way of evaluating gene expression abundance from NGS short reads. | It's the new (2015) way of evaluating gene expression abundance from NGS short reads. | ||
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=Steps in Brief= | =Steps in Brief= | ||
| − | First off, we need an assembly of some sort: a reference transcriptome or genome, which may have been de-novo assembled. | + | First off, we need an assembly of some sort: a reference transcriptome or genome, which may have been de-novo assembled. As is often the case, this needs to be indexed first. Kallisto has its own tool for that. Here we use the example data from the Edgen RNAseq pipeline: |
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| + | kallisto index -i mm10_chr19-1-20000000.idx mm10_chr19-1-20000000.fasta | ||
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| + | <ins>Explanation</ins>: | ||
| + | * '''-i''' is not the input option but rather the index name option, whihc is this command is the chosen output name for the index file. | ||
| + | * the reference or assembly follows with no associated option | ||
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Revision as of 23:09, 22 May 2016
Contents
Inroduction
It's the new (2015) way of evaluating gene expression abundance from NGS short reads.
It is considerably faster than other methods (like those based on say, RSEM) in that it omits the conventional alignment step, and instead calculates what it calls compatibility classes for each read, which are transcripts that the read could align with, if a proper alignment had taken place.
Steps in Brief
First off, we need an assembly of some sort: a reference transcriptome or genome, which may have been de-novo assembled. As is often the case, this needs to be indexed first. Kallisto has its own tool for that. Here we use the example data from the Edgen RNAseq pipeline:
kallisto index -i mm10_chr19-1-20000000.idx mm10_chr19-1-20000000.fasta
Explanation:
- -i is not the input option but rather the index name option, whihc is this command is the chosen output name for the index file.
- the reference or assembly follows with no associated option
Links
- Kallisto's own getting started page at starting
- benchtobioinformatics
- Andrew MacKenzie
Analysis
Also part of Lior Pachter's lab is the Sleuth software and this is recommended for analysis of kallisto output
