Following up on yesterday’s conversation:
uclust is the same as CD-HIT but faster because it doesn’t search all transcripts, but stops when probability of a match declines below threshold.
Ran CAP3 on Trinity assembled transcripts from all reads.
cap3 Trinity.fasta -f 50 -a 50 -k 0 -p 90 -o 100 > Trinity_cap3.out
Took about 2 hours to run.
Started with 126,172 transcripts.
15,250 transcripts were clustered into 6,567 contigs, leaving 110,922 singlets and a total of 117,489. Some reduction…but far from the half expected based on read mapping.
Ran uclust on this fasta file to further reduce.
# sort uclust –sort Trinity_cap3.fasta –output Trinity_cap3_sorted.fasta # cluster by 90% similarity threshold uclust –input Trinity_cap3_sorted.fasta –uc Trinity_cap3_uclust.fasta –id 0.90
Last trial yielded zero DNA. Bummer.
Round 3 of Genomic-tip extraction - use overnight incubation with Proteinase K as with first round.
Finish extraction tomorrow morning.
Very interesting project for teaching stats with R. Worked through the first 5 minutes or so. Nice integration of text, video and figures.
Nosek, B.A., Spies, J.R. & Motyl, M. (2012). Scientific Utopia II. Restructuring Incentives and Practices to Promote Truth Over Publishability. Perspectives on Psychological Science, 7, 615–631.
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