Banana Slug Genomics

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====== Lecture Notes for April 09, 2010 ======

Add to these lecture notes with any notes you have!

===== Notes before main lecture =====

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.
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.

===== Main lecture: Assembler graphs =====

Types of assembler graphs:
  * Overlap graph
  * de Bruijn graph

Differences are "What are the nodes?"
  * Overlap: reads
  * de Bruijn: k-mers (usually fixed k, k <= length(read))

=== Overlap graphs ===

* read -> * read (a directed graph)
<code>
        A
_______________
    | | | | | |
    __________________
            B
</code>
The problem is the direction of the reads when aligning:
  * 4 different edge scenarios:
    * -> -> (A -> B)
    * -> <- (A -> B' or B -> A')
    * <- -> (B' -> A or A' -> B)
    * <- <- (B -> A)
  * 3 different edge types:
    * A to B
    * B to A
    * A' to B / A to B'

Need to have some tolerance for error because the reads are noisy.

=== de Bruijn graphs ===

* kmer -> * kmer -> * kmer -> * kmer …

<code>
|----------|
 |-----------|
  |----------|
   |----------|
    …
</code>

No different than a count of k+1 mers.

Ways to handle representing the graph:
  * Direct addressing (becomes useless for assembly, need to map to unique places)
  * Hashing (key = size of kmer, have to go to 20…25 mer for the keys to start to be unique)

 May run into problems with RAM on the computational nodes. 
  * ~ 16 GB per core, was that 4 cores sharing 16 GB or each core with 16 GB?
  * /proc/meminfo, /proc/cpuinfo directories contains information about the node

With overlap graph:

A -> B

A -> C

A -> D

<code>
|----------| A
    |----------| B
    |----------| C
       |----------| D
</code>

Don't know where to go / which copy of the repeat currently in.

In ideal situation for de Bruijn graph:

<code>
kmer -> kmer -> kmer -> kmer -> kmer (done!)
</code>

Realistically, there are issues:

Spurs:
<code>
kmer -> kmer -> kmer -> kmer -> kmer
    \-> kmer -> kmer -> kmer (off to nowhere)
</code>

Collapse bubbles:
<code>
    /-> kmer -> kmer -> kmer -\
kmer -> kmer -> kmer -> kmer -> kmer
</code>

Other issues:

Loop:
<code>
kmer -> kmer -> kmer -> kmer -> kmer -> kmer -> kmer
                            \- kmers <-/
</code>

Take the loop?

Multiple paths:
<code>
A                      B
 \                    /
  ------------------->
 /                    \
B                      A'
</code>

Which path to take?

If you have clean data, you can disambiguate some issues.
Largest bias usually comes from PCR for amplification.

Need to collapse the graph (both overlap and de Bruijn) to assemble the reads.
Banana Slug Genomics

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