Banana Slug Genomics

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====== Overview of Assembly ======
Kevin outlined the processes involving in assembling a genome. 

  * Clean up the Reads
  * Clustering and Building Contigs
  * Order and Orient Contigs

===== Clean Up Reads =====
There are two separate and distinct parts of data clean up; error correction and contaminant removal.

=== Error Correction ===
  * May not be necessary for all types of data (Sanger/454).
  * Can be done before or after contig assembly.
    * Before: K-mer Counting
    * After: Map reads to consensus sequences from contigs. 

== K-mer Counting ==
  * Count the number of occurrences of each K-mer in the reads.
  * Remove reads or correct individual bases of K-mers with low counts. 
  * K-mer size must be large enough not to produce trivial counts, but small enough to fit memory constraints.

=== Contaminant Removal ===
  * Contamination can come from many sources:
    * Human (dust)
    * Bacterial
    * Viral (hard to remove)
  * Use BLAST to remove sequences that are unexpected.
    * Expensive to run.
    * Blast contigs instead of individual reads.
    * Strategies:
      * Look for specific contaminants (Human, E. coli).
      * Examine ribosome to identify possible contaminants.
      * Look for things we would not expected to see (e.g. eukaryotic sequence in prokaryotes or vice versa).
    * Once a contig is identified as contaminant:
      * Remove the contig and reads that map to it.
      * Rebuild the contigs.
  * We risk removing parts of the target genome that are very similar to the contaminant 
    * Example from class: nitrogen fixing genes common to two bacterial strains.

===== Cluster Reads and Build Contigs =====
  * Build a graph for the reads
    * De Bruijn Graph
      * Typically used for small reads.
    * Overlap Consensus
      * Generally used for larger reads. 
      * larger memory requirements.
  * Reads that don't quite fit can be error corrected.
  * Ideally use high quality data (Sanger,454). Recent trend is to use cheaper data.
  * **Result**: Contigs


===== Order and Orient Contigs =====
  * Iterative process:
    * Use new data when available.
    * Map reads to draft to import draft version.
    * Leftover reads are sent back for clustering.
  * Mate-pair data is useful for bridging contigs that are adjacent but do not overlap (due to missing data, repeat sequence, etc.)
  * **Result**: Scaffolds

====== Homework ======
Learn about the  [[http://www.cbcb.umd.edu/software/jellyfish/|Jellyfish]] tool for K-mer counting. Try running it on the //Pyrobaculum// data.
Use different parameters and monitor its memory usage. Fill the the wiki page for [[bioinformatic_tools:jellyfish|Jellyfish]].
Banana Slug Genomics

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