1. MCB3895-004 Lecture #15 Oct 23/14 De novo assemblies using PacBio

2. PacBio Long read sequencing technology High error rate (~13%) threw people at first What would this be good for? Scaffolding an early focus Also correct reads using Illumina data (now obsolete)

9. HGAP "Hierarchical Genome Assembly Process" 1.Preassembly - corrects longest reads by mapping shorter reads to them, quality trims 2.Assembly - OLC approach 3.Polishing - Quiver software derives consensus from mapped reads, uses to correct assembly

11. Results My test gave an impressive 1 contig! High ~60X coverage, tame dataset Known problem: still some SNP errors Can run Quiver again 1.Import assembly as a reference sequence 2.Perform reference mapping using same reads vs. new reference 3.Will output a new consensus fasta file incorporating the variants it finds

16. PacBio chemistries PacBio has continually updated both its polymerases and detection chemistry Current test data uses P4-C2 chemistry P5-C3 gave slightly better length, maybe a bit more error Fastq available for this E.coli: SRR1284073 Brand new: P6-C4

17. P6-C4 As per last week 10-15kb read N50 Slightly better accuracy? http://blog.pacificbioscie nces.com/2014/10/new- chemistry-boosts- average-read.html

18. Other options: hybrid assemby It is possible to combine multiple data types Goal: cover the respective strengths of each (of course, could confound too!) SPAdes is one of the most flexible assemblers in this regard Must have some Illumina Will accept corrected, uncorrected PacBio (and many more, including Oxford Nanopore)

19. Assignment #7 Create 2 E.coli assemblies using PacBio data Use P4-C2 alone and HGAP Use Illumina + P5-C3 uncorrected Use Illumina + P4-C2 uncorrected Use Illumina + P4-C2 corrected Multiple quiver steps to correct Some other option! Hand in: 2 genome assemblies Lab notebook file detailing exact commands