lecture_notes:04-08-2015
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lecture_notes:04-08-2015 [2015/04/09 23:05] sihussai |
lecture_notes:04-08-2015 [2015/04/17 22:34] sihussai fixing capitalization |
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| - | =====De novo Assembly II===== | + | ======De novo assembly II====== |
| **Guest lecturer: Stefan Prost, stefan.prost@berkley.edu** | **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, so you get one read for each end (may or may not overlap depending on molecule and read size) | * 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) | ||
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| * not enough info for scaffolding | * not enough info for scaffolding | ||
| - | ====Illumina Mate-Pair Sequencing Libraries=== | + | =====Illumina mate-pair sequencing libraries==== |
| * Idea: get paired reads that are much farther away (for more scaffolding info) | * 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. | * Basically, the same idea as paired-ends, except the middle section is missing and the ends are oriented the opposite way. | ||
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| - | ====BAC (Bacterial Artificial Chromosome) and Fosmid Libraries==== | + | =====BAC (Bacterial Artificial Chromosome) and fosmid libraries===== |
| * Uncommon and expensive, but the gold standard | * Uncommon and expensive, but the gold standard | ||
| * Bacterial F-plasmid takes< 40 kb insert size | * Bacterial F-plasmid takes< 40 kb insert size | ||
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| * http://www.scq.ubc.ca/wp-content/plasmidtext.gif | * http://www.scq.ubc.ca/wp-content/plasmidtext.gif | ||
| - | ====Read Quality Assessment==== | + | =====Read quality assessment===== |
| * Base quality: Phred scores reported by sequencer. | * Base quality: Phred scores reported by sequencer. | ||
| * Fastq files: fasta files, plus encoded phred scores | * Fastq files: fasta files, plus encoded phred scores | ||
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| * Pacific Bio doesn’t have GC|AT bias | * Pacific Bio doesn’t have GC|AT bias | ||
| - | ===Tools=== | + | ====Tools==== |
| * FastQC (Most popular tool to tell you about the read library) | * FastQC (Most popular tool to tell you about the read library) | ||
| * FastQC reported an issue with our data with kmer count (related to adapter content) | * FastQC reported an issue with our data with kmer count (related to adapter content) | ||
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| * Estimates how difficult the assembly will be | * Estimates how difficult the assembly will be | ||
| - | ====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 | ||
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| * 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 contig length in the k-de Brujin graph can estimate the best kmer to use for assembly. Based on contig length N50** | **Simulated contig length in the k-de Brujin graph can estimate the best kmer to use for assembly. Based on contig length N50** | ||
lecture_notes/04-08-2015.txt · Last modified: 2015/04/17 22:34 by sihussai
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