lecture_notes:04-08-2015
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision | Next revision Both sides next revision | ||
|
lecture_notes:04-08-2015 [2015/04/09 19:12] jolespin |
lecture_notes:04-08-2015 [2015/04/09 22:42] sihussai |
||
|---|---|---|---|
| Line 1: | Line 1: | ||
| - | **De nova Assembly II** | Wed 8 April 2015 | Stefan Prost | stefan.prost@berkley.edu | jolespin notes | + | =====De novo Assembly II===== |
| + | **Guest lecturer: Stefan Prost, stefan.prost@berkley.edu** | ||
| - | #Illumina Paired-end Sequencing Libraries | + | ====Illumina Paired-end Sequencing Libraries==== |
| - | . MiSeq has 300 bp reads | + | * MiSeq has 300 bp reads |
| - | . Paired ends read from both directions | + | * Paired ends read from both directions, so you get one read for each end (may or may not overlap depending on molecule and read size) |
| - | =====> read_1 | + | =====> end_1 |
| ________________________ | ________________________ | ||
| - | read_2 <===== | + | end_2 <===== |
| - | . Can’t sequence repeat regions with paired-end reads | + | |
| - | #Illumina Mate-Pair Sequencing Libraries | + | * Can’t sequence repeat regions with paired-end reads |
| - | <===== read_1 | + | * ends can't be very far apart because Illumina can't handle big molecules |
| + | * not enough info for scaffolding | ||
| + | |||
| + | ====Illumina Mate-Pair Sequencing Libraries=== | ||
| + | * Idea: get paired reads that are much farther away (for more scaffolding info) | ||
| + | * Basically, the same idea as paired-ends, except the middle section is missing and the ends are oriented the opposite way. | ||
| + | |||
| + | <===== end_1 | ||
| ________________________ | ________________________ | ||
| - | read_2 =====> | + | end_2 =====> |
| - | . Dependent on inferring insert size | + | |
| - | . Genomic DNA > Fragment (2-5 kb) > biotinylate ends > | + | * Genomic DNA > Fragment (2-5 kb) > biotinylate ends > Circularize > Fragment (400-600 bp) > Enrich biotinylated fragments > Ligate adaptors > … |
| - | Circularize > Fragment (400-600 bp) > Enrich biotinylated fragments > | + | * Dependent on inferring insert size |
| - | Ligate adaptors > … | + | |
| - | #BAC (Bacterial Artificial Chromosome) and Fosmid Libraries | + | ====BAC (Bacterial Artificial Chromosome) and Fosmid Libraries==== |
| - | . Bacterial F-plasmid takes< 40 kb insert size | + | * Bacterial F-plasmid takes< 40 kb insert size |
| - | . Fragment query DNA > DNA into BAC > Transform E. coli with BAC > ~300 kb long reads | + | * Fragment query DNA > DNA into BAC > Transform E. coli with BAC > ~300 kb long reads |
| - | . http://www.scq.ubc.ca/wp-content/plasmidtext.gif | + | * http://www.scq.ubc.ca/wp-content/plasmidtext.gif |
| - | #Read Quality Assessment Tools | + | ====Read Quality Assessment Tools==== |
| - | . FastQC (Most popular tool to tell you about the read library) | + | * FastQC (Most popular tool to tell you about the read library) |
| - | . Preqc | + | * Preqc |
| - | . Reads decrease in quality further down the read | + | * Reads decrease in quality further down the read |
| - | . Pacific Bio doesn’t have GC|AT bias | + | * Pacific Bio doesn’t have GC|AT bias |
| - | #Estimating Genome Size from Read Data | + | ====Estimating Genome Size from Read Data==== |
| . G = (pn(1-k+1))/(λ_k) | . G = (pn(1-k+1))/(λ_k) | ||
| G = Genome size | G = Genome size | ||
| Line 38: | Line 45: | ||
| Simpson 2013, arXiv | Simpson 2013, arXiv | ||
| - | . To estimate genome size need to know:i) total number of reads; ii) length of reads; and iii) kmer distribution | + | * To estimate genome size need to know:i) total number of reads; ii) length of reads; and iii) kmer distribution |
| - | #Error Correction | + | ====Error Correction==== |
| - | . High amount of small kmers are usually errors | + | * High amount of small kmers are usually errors |
| ***Simulated contif length in the k-de Brujin graph can estimate the best kmer to use for assembly. Based on contif length N50 | ***Simulated contif length in the k-de Brujin graph can estimate the best kmer to use for assembly. Based on contif length N50 | ||
lecture_notes/04-08-2015.txt · Last modified: 2015/04/17 22:34 by sihussai
Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Noncommercial-Share Alike 3.0 Unported
