Ribofilio

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Ribofilio: A tool to estimate ribosomes drop-off rate

Ribofilio is a tool to estimate ribosomes drop-off rate that has been tested in ecoli and yeast so far.

Installation

Manual Installation

  git clone https://github.com/SherineAwad/ribofilio.git
  cd src 

Dependencies

screed

numpy

matplotlib

sklearn 
    
scipy

How to run Ribofilio

To run ribofilio:

python ribofilio.py --transcripts --footprint footprint.bed --rnaseq rnaseq.bed --binsize binsize --output output 

or simply:

python ribofilio.py -t transcripts.fa -f footprint.bed -r rnaseq.bed  -b binsize -o output 

Parameters

--transcripts or -t for transcripts in fasta format (required)

--footprint or -f for footprint bed file (required)

--rnaseq or -r for rnaseq bed file (if not available, dropoff rate won't be normalized by mRNA)

--subset or -s is a list of genes in file to run ribofilio on this subset only

--binsize or -b for binsize (default: 50)

--pvalue or -v choose 1 for one-sided pvalue or 2 for two-sided pvalue (default: 1)

--output or -o for output name

--plot or -p choose 1 for turning on plot mode and 0 to disable plots (default: 1)

--ylogmin is the minimum y axis for log plots (default: -3)

--ylogmax is the maximum y axis for log plots (default: 2)

Example

Running ribofilio on all gene:

python ribofilio.py -t yeast.fa -f SRR5945809.bed -r SRR5945808.bed 

Where yeast.fa is the transcripts, SRR5945809.bed is the bed file of footprints of sample, SRR5945808.bed is the mRNA bed file

here binsize used is 50 as no other binsize is passed.

To run ribofilio on a subset of genes:

python ribofilio.py -t yeast.fa -f SRR5945809.bed -r SRR5945808.bed -s subsetofgenes.txt 

Where subsetofgenes.txt is a list of genes:

    YDL067C

    YGL187C

    YGL191W

    YHR051W

    YIL111W

    YLR038C

    YLR395C

    YMR256C

    YNL052W

Bed file format

6 columns bed file format is required, a sample is as follows:

  YGL135W_mRNA    95      125     SRR5090936.1.1  1       +
  YKL009W_mRNA    70      98      SRR5090936.1.5  42      +
  YNL045W_mRNA    1664    1692    SRR5090936.1.11 40      +
  YNR050C_mRNA    32      62      SRR5090936.1.18 42      +
  YLR159C-A_mRNA  26      54      SRR5090936.1.20 0       -
  YHR133C_mRNA    443     473     SRR5090936.1.23 42      +

Refer to Ensemble Bed format for more details regarding bed file formats.

Output

Dropoff rate, dropoff rate per codon along with standard error, 95% confidence interval, root mean squared error (RMSE), R2 error, a t-test score of comparing the slope to a slope of zero and the corresponding pvalue will be print to both screen and output.regression.log file, and number of bins. If the plot mode is on, a weighted linear regression plot will be saved into output.Log.WLR.png.

A sample of output.regression.log:

   Dropoff Dropoff per codon       RMSE    Rsquare SE      Margin Error    tscore  pvalue  No.of Bins
   -0.0051 -0.0003 0.0143  0.4907  0.0006  0.0011  -9.089848129268738      0.0     295

and output.Log.WLR.png:

Documentation

Looking for a more detailed tutorial: Take a look into Our Documentation for a complete Ribosomal profiling protocol using Ribofilio.

Pipeline

For the sake of repoducibility of our results, to run our pipeline on our data in the data directory use:

 snakemake --cores --use-conda 

This require snakemake and conda installed in your system.

Data

The data used to test our tool and used in the pipeline can be downloaded using a Makefile in the data directory:

 make yeast.fa
 make SRR5090937.fastq
 make SRR9670823.fastq
 make clean

Sample Prepared Bed files

We provide sample Bed Files prepared for the sake of trying out ribofilio without the need to go through the upstream pipeline.