lecture_notes:04-09-2010
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lecture_notes:04-09-2010 [2010/04/11 22:09] learithe |
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| Take fix mode script from /projects/compbio/bin/scripts and replace protein user group with BME 235 user group. | Take fix mode script from /projects/compbio/bin/scripts and replace protein user group with BME 235 user group. | ||
| - | Next week will have a reference genome (POG) to use for testing the tools on. | + | Next week will have a reference genome (//Pyrobaculum oguniense//, aka //"Pog"//) to use for testing the tools on. |
| - | For the most part POG is done; however, there are still some uncertainty with 8 SNPs left. It is definitely past the MIAMI standard at this point. | + | For the most part Pog is done; however, there are still some uncertainty with 8 SNPs left. It is definitely past the MIAMI standard at this point. (//Pog// assembly is down to only 8 snps & one potentially variable insert) |
| - | Note about sequencing platform quality scores: most platforms are trying to use the phred quality score((http://en.wikipedia.org/wiki/Phred_quality_score)), so the quality score is comparable between the platforms and runs | + | Note about sequencing platform quality scores: most platforms are trying to use the phred quality score((http://en.wikipedia.org/wiki/Phred_quality_score)), so the quality score is theoretically comparable between the platforms and runs (although calibration causes scores to vary between runs and instruments nonetheless) |
| It can be informative, once reads are mapped, to look at the quality scores for reads with observed errors. | It can be informative, once reads are mapped, to look at the quality scores for reads with observed errors. | ||
| - | //Pog// assembly is down to only 8 snps & one potentially variable insert | + | |
| Lior Pachter (from UC Berkeley) is vising on Monday, to speak about the Bowtie/TopHat/CuffLinks algorithms. Bowtie: mapping; TopHat/Cufflinks: find splice junctions, predicted spliced transcripts. Bowtie is used in a lot of the assembly agorithms. | Lior Pachter (from UC Berkeley) is vising on Monday, to speak about the Bowtie/TopHat/CuffLinks algorithms. Bowtie: mapping; TopHat/Cufflinks: find splice junctions, predicted spliced transcripts. Bowtie is used in a lot of the assembly agorithms. | ||
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| Realistically, there are issues: | Realistically, there are issues: | ||
| + | == End of Contig boundaries: == | ||
| - | Spurs: | + | what if A->B and A->C and A->D BUT A->B and A->C are inconsistent with each other? |
| + | … A becomes “end of contig”, because you aren’t sure where to go next | ||
| + | also end of contig if there are no more edges from the node | ||
| + | |||
| + | == Spurs: == | ||
| <code> | <code> | ||
| kmer -> kmer -> kmer -> kmer -> kmer | kmer -> kmer -> kmer -> kmer -> kmer | ||
| \-> kmer -> kmer -> kmer (off to nowhere) | \-> kmer -> kmer -> kmer (off to nowhere) | ||
| </code> | </code> | ||
| + | path diverges but does not reconverge, resulting in source/sink dead-ends (these are likely due to read errors) | ||
| - | Collapse bubbles: | + | == Bubbles: == |
| <code> | <code> | ||
| /-> kmer -> kmer -> kmer -\ | /-> kmer -> kmer -> kmer -\ | ||
| Line 116: | Line 122: | ||
| </code> | </code> | ||
| - | Other issues: | + | path splits due to a SNP but then converges. this can happen with real SNPs, read error SNPs, and real repeats which differ by a SNP or two |
| - | Loop: | + | == Loop: == |
| <code> | <code> | ||
| kmer -> kmer -> kmer -> kmer -> kmer -> kmer -> kmer | kmer -> kmer -> kmer -> kmer -> kmer -> kmer -> kmer | ||
| \- kmers <-/ | \- kmers <-/ | ||
| </code> | </code> | ||
| + | tandem repeats will generate a circle, but have edges in and out; hard to disambiguate copy # though. If the data is really clean (ie, in/out edges are ~10 read-depth with low SD, and inside circle has ~20 read-depth with low SD), can guess that there might be 2 copies of the repeat, but not highly reliable | ||
| - | Take the loop? | + | == Multiple paths: == |
| - | + | ||
| - | Multiple paths: | + | |
| <code> | <code> | ||
| A B | A B | ||
| Line 140: | Line 145: | ||
| Largest bias usually comes from PCR for amplification. | Largest bias usually comes from PCR for amplification. | ||
| - | Need to collapse the graph (both overlap and de Bruijn) to assemble the reads. | + | ===Assembly:=== |
| + | algorithms (both overlap and de Bruijn) need to collapse bubbles and trim spurs.\\ | ||
| + | spurs: discard if their read count is low\\ | ||
| + | bubbles: tricky, because they can represent real, divergent paths | ||
| + | |||
| + | |||
lecture_notes/04-09-2010.txt · Last modified: 2010/04/12 21:37 by cbrumbau
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