Ribosome footprinting analysis tools Files

This set of scripts is designed to analyze ribosome footprinting and mRNA sequencing reads in the ER and cytosol. Its framework may be adapted to other sorts of questions related to sequencing data.

This was written for Pyton 2.7.1 using Ubuntu. In other systems, your mileage may vary. Required plugins include Matplotlib, Numpy and Scipy.

This readme will walk through the steps required to complete the analysis discussed in Reid and Nicchitta 2011. 

We will assume that you already have mapped reads (in .map format) generated by Bowtie. If you don't have reads, you can use thoes from out paper (GEO ascession XXXXXX)

1) Place your .map files for mRNA and ribosome footprints in the same folder to which you extracted the contents of the zip file
2) Open countReads.py in a text editor. At the top of that file, you will find four variables to change. cytRNA and memRNA represent the total amount of mRNA in each fraction. mem and cytmRNAReads point to your map files. RNALevelsCutoff is the RNA levels (in RPKM) above which mRNAs will be considered.
3) Run countReads.py. This will make the file memOut, which describes the mRNA levels in each compartment.
4) Open countFoots.py in a text editor. Again, you will find several variables to change, including the location of your mapped reads, the total amount of ribosomes from each sample, and the read length (35 for human ribosomes).
5) Run countFoots.py
6) Your plots will go to the densityPlots folder in the format specified by fileFormat. There will also be a file called footOut that will describe several abstractions of the data (ribosome loading, density, efficiency, etc)