Difference between revisions of "Kallisto"
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| − | It's the new (2015) way of | + | It's the new (2015) way of evaluating gene expression abundance from NGS short reads. |
| − | It | + | 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. |
| − | =Using= | + | =Using the software= |
== Links == | == Links == | ||
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* [https://benchtobioinformatics.wordpress.com/2015/07/10/using-kallisto-for-gene-expression-analysis-of-published-rnaseq-data benchtobioinformatics] | * [https://benchtobioinformatics.wordpress.com/2015/07/10/using-kallisto-for-gene-expression-analysis-of-published-rnaseq-data benchtobioinformatics] | ||
* [http://andrewtmckenzie.com/2015/05/12/how-to-run-kallisto-on-ncbi-sra-rna-seq-data-for-differential-expression-using-the-mac-terminal Andrew MacKenzie] | * [http://andrewtmckenzie.com/2015/05/12/how-to-run-kallisto-on-ncbi-sra-rna-seq-data-for-differential-expression-using-the-mac-terminal Andrew MacKenzie] | ||
| + | |||
| + | =Analysis= | ||
| + | |||
| + | Also part of Lior Pachter's lab is the Sleuth software and this is recommended for analysis of kallisto output | ||
Revision as of 16:55, 24 March 2016
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.
Using the software
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
