lecture_notes:04-21-2010
Table of Contents
April 21st, 2010
Logistic related notes
- There will be a guest lecture on Friday, April 23rd, 2010. Please do not be late!
- By Friday, April 23rd, 2010, all published sources which contain information pertaining to Banana slug should be added to the Banana Slug Biology page. Is this the right page?
- Expect 40-50 different resources (papers, books, phd theses)
- The bibliography must be annotated, though annotations are not required this friday.
- As you run assembly tool, keep the assemblies/ wiki page updated!
Continuation of Newbler Assembler methods
- By running Newbler using settings described last friday, Kevin obtained 43 contigs and ~2.4 megabases of DNA.
- This measure is not bad compared to most other assemblers
Overview of directories
- Newbler-clean
- Not attempting to assemble data.
- Used to remove contamination for H. Pylori which was sequenced on the same machine in the same run.
- If you have a reference genome for your contaminants, you can try to clean them out computationally by mapping and removing matches.
- Makefile Overview
- Set up a new mapping
- Maps reads from 454 Pog data to the contaminant genome
- Interesting output: ReadStatus.txt
- Contains mapping status of each read (Mapped, unmapped, partially mapped, too short)
- Reads mapped to contaminants should be filtered out from 454 data and should not be sued for assembly.
- Create a new SFF file (using sfffile utility) with unmapped data in file “no_Hyp.sff”
- It may be beneficial to hang onto “too short” reads for use in assemblers which utilize shorter reads.
- You can also use Megablast and NCBI's Taxonomy Report to identify contaminants.
- Newbler-assembly2
- Uses clean data (no H. Pylori) from newbler-clean1
- One less small contig, mostly the same
- Newbler *
- Changed expected coverage to 60x– This number is closer to the real coverage based on better estimates of genome size.
- Still reported 41 contigs (or maybe one less?)
- good news- All contigs map to reference genome
- Map-colorspace3 (Map-colorspace directories begin indexing at 3 rather than 1)
- The scripts ran in this directory were originally intended for finding inverseions from mate-pair reads.
- New features have been added since then.
- Now looks for reads between contigs
- Tries to orient contigs
- Newbler-partial3
- attempts to use only partially mapped/unmapped reads
- Plan is to later map contigs from this assembly to the full contigs from before (extend edges?)
- Megablast, blastn, blat, find dna differences are four methods for mapping partially mapped reads onto contigs created by newbler.
- Megablast and blastn showed very similar results
- blat
- output is a psl file
- Nice results
- Very sensitive but also very slow
- Shows matches down to 14 bases in size
- can handle intros and splice sites
- May be too sensitive for some purposes
- There are some parameters you can tweak which will alter the output.
- Kevin thought it would be best to keep blat's default parameters and filter output.
- A script was written to filter output and find the best matches.
- For a resequencing project, take all contigs, map with blat, sort by start site and build a scaffold according to the order of the start sites of each contig.
- Find dna differences
- Shows differences between contigs and a reference genome in a human readable format
- Newbler-assembly4
- Adds partial3 contigs to full search as reads
- Didn't seem to help much
- The resulting output had fewer total bases and more contigs than originally - perhaps worse.
- Newbler-assembly5
- Utilized Sanger reads produced by David Bernick to join contigs
- 45 Sanger reads total
- Sanger reads were created by running pcr on conjectured contig join sites.
- Two possible methods for guessing contig join sites
- Use mate-pair data from solid run as evidence to create primers
- David Bernick used know Crispr repeats. Some contigs showed the start of a repeat, while others showed the end
- After adding Sanger reads, the final assembly went down to 31 contigs
- In contig-length.rdb
- Most reads have ~0.16 reads/base
- The reads/base metric was utilized because computation was simpler than coverage.
- Some reads had greater reads/base ~0.32 (qty. 3) and ~0.44 reads per base
- Could 0.32 reads/base indicate two occurences of the contig in the genome?
- Could 0.44 occur three times in the genome?
- All 0.16 reads/base contigs occured a single time in the genome
- 2/3 0.32 reads/base appeared twice in the genome.
- 1/3 0.32 reads/base was a short contig and was within the expected deviation in reads/base from a sequencing run
- 0.44 reads/base occured twice, not three times
- Less contigs and more bases
- Map-colorspace5
- map-colorspace has many parameters.
- You can list all the parameters by issuing the command “map-colorspace –help”
- Lots of output files using this command (~2 per contig). May prove problematic with assemblies that contain many contigs
- Set length parameters using a histogram of reads mapped to contigs
- merge_cross option merges all cross products into a single file rather than (number of contigs)^2 files
- scaffold fasta & and color qualities are thrown out in this method
- If F3 or R3 maps, the program aggresivly tries to map the paired read.
- Output
- Uniquely mapped reads mapped both F3 and R3 (Forward and Reverse) reads to the same contig
- Multiply mapped- can map to multiple contigs
- Wrong range, only F3 or R3 map
- Summary File
- Maps F3 and R3 from the end of one contig to the beginning of another
- Shows that contigs are near, not touching.
- short contigs may be skipped in paired end reads
- QUESTION: Can we make a single connected graph using this data and all possible paths? -sometimes if data is particularly coherent. not guaranteed.
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