A. Using MIRA
B. Comparing Assemblers
Transcriptome Assembly Workshop
2010.11.01
Sujai Kumar, University of Edinburgh
Why MIRA
Open source
(Very) Well documented
Well maintained
Active user groups
It works!
How MIRA works
Mimicking Intelligent Read Assembly
Overlap-layout-consensus paradigm (OLC)
Iteratively resolves repeats
Can call SNPs
But is it better to assemble first, then map reads back?
Does not deal well with high coverage
Non-normalised libraries, too much RNA not ideal
Getting started
Exercise 2A
Trim reads
Rename files
Use quick switches
--job=454,denovo,est,accurate
MIRA Options
Try other options along with quick switches
-GENERAL (-GE)
-LOADREADS options (-LR)
-ASSEMBLY (-AS)
-STRAIN/BACKBONE (-SB)
-DATAPROCESSING (-DP)
-CLIPPING (-CL)
-SKIM (-SK)
-ALIGN (-AL)
-CONTIG (-CO)
Q: How do you get mira to not create redundant/repetitive
contigs?
Comparing Assemblers
Comparing Assemblers
Comparing Assemblies
Comparing Assemblies
Litomosoides sigmodontis 700k+ 454 reads
Comparing Assemblies
Novel sequence in one assembly compared to another
Comparing Assemblies
Alignments to reference sequences
ESTs from same species (blat)
Comparing Assemblies
Alignments to reference sequences
Proteins from related species (blastx)
Comparing Assemblies
Exercise 2B