R package for the Analysis of Ribosomal RNA Fragments, generally generated by Ribosome Profiling (Ribo-Seq) experiments
Currently, it includes the following methods:
In R (>= 2.10) environment
install.packages("devtools")
devtools::install_github("fallerlab/ARF@main")
Please make sure that you have the following packages installed as dripARF requires them:
To be able to use the ARF package, you first need to align your adapter-trimmed Ribo-seq reads to given rRNA sequences which are provided under the "rRNAs/" folder for two organisms; human and mouse. Using these alignments, ARF quantifies the rRNA fragments at each rRNA position for further analysis.
Currently, ARF package contains only the dripARF method. Please stay tuned for future additions :)
Based on position-specific rRNA abundances and the 3D structure of the ribosome, dripARF predicts which ribosomal proteins have a change in their ribosomal incorporation between given conditions. With such prediction, it identifies the prime candidates that contributes to the inter-sample heterogeneity of ribosomes across conditions.
The input for the dripARF pipeline is as follows:
Prior to using dripARF, assuming rRNA read alignments are ready, we also suggest to perform your positional rRNA abundance quantifications using the "bedtools" software. Note that this is not mandatory since you can also use your indexed .bam files as input. However, using pre-processed alignments (.bedGraph) will significantly increase the computational speed of dripARF. Following is the example on how you can create your .bedGraph files.
bedtools genomecov -bg -ibam /your/bam/file.bam > /your/bedGraph/file.bedGraph
If your alignment files, whether in .bam or .bedGraph format, are ready and accessible through the paths given within samples.tsv file, and your target folder is accessible, you can run the dripARF wrapper function in one line within your R environment.
dripARF_results <- ARF::dripARF(samplesFile = "samples.tsv", organism="mm", QCplot=TRUE, targetDir="dripARF_results/")
This function will run the whole pipeline and will return a data frame with the ribosome heterogeneity prediction results for all possible comparisons. It will also create comparison-specific ".csv" files to store your results in addition to a few informative QC plots. Most importantly, the pipeline will save a scatterplot and heatmap visualization summarizing your results.
Within this function, there exists a few other options as well. For example, you can specify which comparisons you want to focus on, or which samples to exclude from the analysis.
Please note that you have to specify the organism and align your reads strictly to given rRNA sequences when running the pipeline.
dripARF() wrapper function uses series of other dripARF functions to obtain your results. We summarize below what these functions are used for.
If you have installed the ARF package successfully, you can test it with the data provided under the test_data/ folder.
Copyright 2021 by Ferhat Alkan
ARF is released under the GNU General Public License.
GNU GENERAL PUBLIC LICENSE
This is a free software: you can redistribute it and/or modify it under the terms of the GNU General Public License, either version 3 of the License, or (at your option) any later version. You should have received a copy of the GNU General Public License along with ARF, see file LICENSE. If not, see http://www.gnu.org/licenses/.
This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
If you actively use the ARF platform, please cite the following publications:
Ferhat Alkan, Oscar Wilkins, Santiago Hernandez-Perez, Sofia Ramalho, Joana Silva, Jernej Ule, William J Faller; Identifying ribosome heterogeneity using ribosome profiling data, Nucleic Acids Research, 2022; gkac484, https://doi.org/10.1093/nar/gkac484
For questions, queries, bug reports; please use the github issues tab or contact: fallerlab@gmail.com and/or feralkan@gmail.com.