User Tools

Site Tools


lecture_notes:04-05-2010

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
lecture_notes:04-05-2010 [2010/04/07 11:27]
galt
lecture_notes:04-05-2010 [2010/04/15 18:16]
karplus fixed citations to use Refnotes syntax
Line 29: Line 29:
   * SOLiD System Tools (Corona_lite,​ etc): Hyunsung and Chris   * SOLiD System Tools (Corona_lite,​ etc): Hyunsung and Chris
   * Newbler documentation:​ Galt and Herbert   * Newbler documentation:​ Galt and Herbert
 +  * SOAPdenovo: Galt and Jenny
  
  
- +Assembly Review Articles: 
-[[http://​www.sciencedirect.com/​science?​_ob=ArticleURL&​_udi=B6WG1-4YJ6GD8-1&​_user=10&​_coverDate=03%2F06%2F2010&​_rdoc=1&​_fmt=high&​_orig=search&​_sort=d&​_docanchor=&​view=c&​_searchStrId=1282691739&​_rerunOrigin=google&​_acct=C000050221&​_version=1&​_urlVersion=0&​_userid=10&​md5=32c08d11cc10fd1eefca0f8a8def738b|Review Article]+  * Jason R. Miller, Sergey Koren and Granger Suttona ​[(cite:​Miller2010>​Jason R. Miller, Sergey Koren, Granger Sutton, Assembly algorithms for next-generation sequencing data, Genomics, In Press, Corrected Proof, Available online 6 March 2010, ISSN 0888-7543, DOI: 10.1016/​j.ygeno.2010.03.001 ​http://​www.sciencedirect.com/​science/article/B6WG1-4YJ6GD8-1/​2/​ae6c957910e4ea658cdebff4a0ce9793)\\ Covers these assemblers: ​SSAKE, SHARCGS, VCAKE, Newbler, Celera, Euler, Velvet, ABySS, AllPaths, and SOAPdenovo.Compares ​de Bruijn graph to overlap/​layout/​consensus. 
- +  ​ 
- ​Assembly algorithms for next-generation sequencing data + 
- +
- Jason R. Miller, Sergey Korena and Granger Suttona +
- +
- SSAKE, SHARCGS, VCAKE, Newbler, Celera ​Assembler, Euler, Velvet, ABySS, AllPaths, and SOAPdenovo. +
- +
- More generally, it compares the two standard methods known as the de Bruijn graph approach and the overlap/​layout/​consensus ​approach to assembly+
 =====Assembly Overview===== =====Assembly Overview=====
  
Line 64: Line 58:
       * Expect half your reads to have an error in them.       * Expect half your reads to have an error in them.
   * Contiguous chromosomes with a low error rate ( output from assemblers).   * Contiguous chromosomes with a low error rate ( output from assemblers).
-    * Miami standard for a finished genome should have an error rate of 1 x 10^-5 bases.+    * Bermuda ​standard for a finished genome should have an error rate of 1 x 10^-5 bases.1) [(cite:​Bermuda1>​[[http://​www.genome.gov/​page.cfm?​pageID=10506376]])] [(cite:​Bermuda2>​[[http://​www.ornl.gov/​sci/​techresources/​Human_Genome/​research/​bermuda.shtml]])]
     * To reduce error rate in short reads, stack up many reads and take the most common base at each position.     * To reduce error rate in short reads, stack up many reads and take the most common base at each position.
   * How much data do we have?   * How much data do we have?
Line 103: Line 97:
     - Can find repeat regions using paired-end data.     - Can find repeat regions using paired-end data.
   * Most resquencing projects map reads to scaffolds and create contigs based upon mapping. Sections with missing read data can be assumed to be a deleting or an alteration to the existing scaffold.   * Most resquencing projects map reads to scaffolds and create contigs based upon mapping. Sections with missing read data can be assumed to be a deleting or an alteration to the existing scaffold.
 +
 +
 +===== References =====
 +<​refnotes>​notes-separator:​ none</​refnotes>​
 +~~REFNOTES cite~~
 +
 +
lecture_notes/04-05-2010.txt · Last modified: 2010/04/15 18:16 by karplus