@article{perkins_mazzoni-putman_stepanova_alonso_heber_2019, title={RiboStreamR: a web application for quality control, analysis, and visualization of Ribo-seq data}, volume={20}, ISSN={["1471-2164"]}, DOI={10.1186/s12864-019-5700-7}, abstractNote={Ribo-seq is a popular technique for studying translation and its regulation. A Ribo-seq experiment produces a snap-shot of the location and abundance of actively translating ribosomes within a cell's transcriptome. In practice, Ribo-seq data analysis can be sensitive to quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. However, many of these tools require considerable practical knowledge of software applications, and often multiple different tools have to be used in combination with each other.We present riboStreamR, a comprehensive Ribo-seq quality control (QC) platform in the form of an R Shiny web application. RiboStreamR provides visualization and analysis tools for various Ribo-seq QC metrics, including read length distribution, read periodicity, and translational efficiency. Our platform is focused on providing a user-friendly experience, and includes various options for graphical customization, report generation, and anomaly detection within Ribo-seq datasets.RiboStreamR takes advantage of the vast resources provided by the R and Bioconductor environments, and utilizes the Shiny R package to ensure a high level of usability. Our goal is to develop a tool which facilitates in-depth quality assessment of Ribo-seq data by providing reference datasets and automatically highlighting quality issues and anomalies within datasets.}, journal={BMC GENOMICS}, author={Perkins, Patrick and Mazzoni-Putman, Serina and Stepanova, Anna and Alonso, Jose and Heber, Steffen}, year={2019}, month={Jun} }
 @inproceedings{perkins_heber_2017, title={riboStreamR: A web application for quality control, analysis, and visualization of Ribo-seq data}, DOI={10.1109/iccabs.2017.8114317}, abstractNote={Ribo-seq is a popular technique for studying translation and its regulation. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. However, many of them are inaccessible to users without a thorough practical knowledge of software applications, and often multiple different tools have to be used in combination with each other. Here, we present riboStreamR, a comprehensive Ribo-seq quality control (QC) platform in the form of an R Shiny web application. RiboStreamR provides visualization and analysis tools for various Ribo-seq QC metrics, including read length distribution, read periodicity, and translational efficiency. The platform's environment is centered on providing a user-friendly experience, and includes numerous options for graphical customization and report generation. In practice, Ribo-seq data analysis can be sensitive to data quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. What constitutes ‘high quality’ data is often unclear. Our goal is to develop novel functionality to automatically highlight quality issues and anomalies in the data. This NSF-supported project is performed in collaboration with Jose Alonso, Anna Stepanova, Serina Mazzoni-Putman, and Cranos Williams.}, booktitle={International conference on computational advances in bio and medical}, author={Perkins, P. and Heber, Steffen}, year={2017} }