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SelectiveGenomeAmplification
============================
PI: http://brisson.bio.upenn.edu/
## Requirements
To use this you'll need:
- A unix environment
- kmer_total_count, a kmer counter available here: http://github.com/mutantturkey/dna-utils/
- bash or compliant shell.
## Setup
git clone git@github.com:mutantturkey/SelectiveGenomeAmplification.git
cd SelectiveGenomeAmplification
make
sudo make install
## Usage Examples
Standard use of (SGA) SelectiveGenomeAmplification is easy. it takes two arguments,
the foreground and background
SelectiveGenomeAmplification PfalciparumGenome.fasta HumanGenome.fasta;
less PfalciparumGenome_HumanGenome/final_mers
SGA allows for many tunable parameters, which are all explained in the chart
below. For user customizable variables, they need to be passed in as
environmental variables like so:
max_mer_distance=5000 max_select=6 min_mer_range=6 max_mer_range=12 \
SelectiveGenomeAmplification.sh PfalciparumGenome.fasta half.fasta
SGA also comes with a easy to use user prompt called SelectiveGenomeAmplificationUI.
It allows for a less expereienced user to use
SGA without issue.
### Running individual steps
By default SelectiveGenomeAmplification runs all four steps, but you can
specify the program to run other steps, like in these examples.
current_run=run_1 SelectiveGenomeAmplification target.fasta bg.fasta score
current_run=run_1 SelectiveGenomeAmplification target.fasta bg.fasta select score
current_run=run_1 SelectiveGenomeAmplification target.fasta bg.fasta 3 4
valid steps are these:
- count (1)
- filter (2)
- select (3)
- score (4)
This function does not try to be smart, so use it wisely
### Manually scoring specific mer combinations from file
Users can manually score combinations of mers they choose using the
score\_mers.py script.
score_mers.py -f foreground.fa -b background.fa -c combination file -o output
The combination file should look like this:
ACGATATAT TACATAGA TATATATAT ACGTACCAT ATATTA
AAATTATCAGT ATACATA ATATACAT ATATACATA ACATA
ATATACATA ATCATGATA CCAGATACATAT
each row is combination to be scored.
### Manually score all combinations from file
Users can manually score all combinations of mers they choose using the
score\_mers.py script.
score_mers.py -f foreground.fa -b background.fa -m mer file -o output
The mer file should look like this:
ATATAT
TACATA
TACATAGCA
TATAGAATAC
CGTAGATA
TAGAAT
each row is a seperate mer. do not put multiple mers on one line.
## Customizable variables
range of mers, min and max
variable | default | notes
:---- | :---- | ---- | :----
current\_run | Not Enabled | specify the run you want to run steps on
min\_mer\_range | 6 | minimum mer size to use
max\_mer\_range | 12 | maximum mer size to use
max\_mer\_distance | 5000 | maximum distance between mers in foreground
output\_directory | $foreground\_$background/ | ex. if fg is Bacillus.fasta and bg is HumanGenome.fasta then folder would be $PWD/Bacillus.fasta\_HumanGenome\_output.fasta/
counts\_directory | $output\_directory/.tmp | directory for counts directory
tmp\_directory | $output\_directory/.tmp | temporary files directory
max\_melting\_temp | 30° | maximum melting temp of mers
min\_melting\_temp | 0° | minimum melting temp of mers
min\_foreground\_binding\_average | 50000 | elminate mers that appear less frequently than the average (length of foreground / # of occurances)
max\_select | 15 | maximum number of mers to pick
max\_check | 35 | maximum number of mers to select (check the top #)
ignore\_mers | Not Enabled | mers to explicitly ignore, space seperated ex. ignore\_mers="ACAGTA ACCATAA ATATATAT"
ignore\_all\_mers\_from\_files | Not Enabled | ignore any mers found in these files. space seperated.
foreground | Not Enabled | path of foreground file
background | Not Enabled | path of background file
max\_consecutive\_binding | 4 | The maxium number of consecutive binding nucleotides in homodimer and heterodimers
fg\_weight | 0 | How much extra weight to give higher frequency mers in fg. see "equations" (between 0 and 1)
primer\_weight | 0 | How much extra weight to give to sets with a higher number of priemrs. (between 0 and 1)
## Equations
Here's what we are using to determine our scoring and selectivity
### Selecivity
Our selectivity is what we use to determine what top $max\_check mers are checked later
on in our scoring function. Currently we use this formula:
By default our fg\_weight is zero. This gives no extra weight to more
frequently occuring mers, but can be set higher with the fg\_weight
environmental variable if you wish to do so.
hit = abundance of primer X (ex. 'ATGTA') in background
(foreground hit / background hit) * (foreground hit ^ fg_weight)
### Score function
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