Difference between revisions of "Genome Assembly Project: Leland Taylor '12"
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**Find Eulerian path(s) in these graphs | **Find Eulerian path(s) in these graphs | ||
**Note the assumptions made in the paper | **Note the assumptions made in the paper | ||
| + | **TOOL: Jellyfish - counts k-mers http://www.cbcb.umd.edu/software/jellyfish/ | ||
*Lists compression techniques and the order to employ them | *Lists compression techniques and the order to employ them | ||
*Can use this method to compute N50 | *Can use this method to compute N50 | ||
Revision as of 14:38, 23 May 2011
November 21 2024
Kingsford, C., Schatz, M.C. & Pop, M. Assembly complexity of prokaryotic genomes using short reads. BMC Bioinformatics 11, 21 (2010).
Notes
- Use De Brujin graphs to estimate "completeness" of genomes assembled via de novo assembly
- Find Eulerian path(s) in these graphs
- Note the assumptions made in the paper
- TOOL: Jellyfish - counts k-mers http://www.cbcb.umd.edu/software/jellyfish/
- Lists compression techniques and the order to employ them
- Can use this method to compute N50
- N50 = the length of the largest contig (m) such that at least 50% of genome covered by contigs of size >= m.
- A higher N50 score usually correlates to a more "correct" genome
- Regardless of correctness of genome, for nearly all read sizes (1000nt > size > 25nt), 85%+ of genes accurately identified (85% is for 25nt reads).
Thoughts
- Look for assembler that uses De Brujin graph?
- This paper showed how to get an upper limit of correctness of genome. Compare several existing de novo assemblers using the methods here as comparison.
- Is it possible to get the code used in this project?
Pop, M. Genome assembly reborn: recent computational challenges. Briefings in Bioinformatics 10, 354-366 (2009).
