A python package which provides a suite of functions to aid in the generation and interpretation of MISO data. Package provides both plotting features and functions to consolidate and extract psi values from summary data.
misoWrapper.py provides a minimal higher-level wrapper around MISO (Mixture of Isoforms) API. For ease of use, the script.py is the companion to the misoWrapper and allows for function calls from the command line.
#Usage ##Basic Usage
After the python packages have been downloaded and MISO has been locally installed, we can evoke the run MISO command by simply typing:
1) Use MISO to quantitate psi values:
python script.py misoWrapper.runMISO bams/ indexedMisoEvents/ overhanglen False outDir misoSettings.txt all numProcessors sge/torque
2) Use MISO to compare psi values:
python script.py misoWrapper.compareMISO misoDir/ comparisonDir/ all True
3) Summarize MISO quantitations:
python script.py misoWrapper.summarize misoDir/ summaryDir/ sge
4) Summarize MISO comparison:
python script.py misoWrapper.summarizeVs comparisonDir/ mapFile summaryDir/
If you want to consolidate and run the "monotonicity" test to find consistently changing events across replicates, or use a time course, do this:
1) Consolidate the information
python script.py misoWrapper.consolidateSummaries summaryDir/ groups_f consolidated.txt
groups_f needs to be a file that contains a line for each sample, with the group that each sample should be in. For example:
MEFWT_2C5 WT
MEFWT_2E4 WT
MEFWT_4G4 WT
MEFKO_1F11 KO
MEFKO_2E8 KO
MEFKO_4B10 KO
It should have 2 columns, were there is a space or tab between each column.
2) Run the monotonicity test
python cript.py misoWrapper.monotonic consolidated.txt groups_f minbf nshuffles monotonic.txt
minbf can be 5
nshuffles can be 100
The Z-score gives you the metric for "monotonicity".