RNAlysis: analyze your RNA sequencing data without writing a single line of code

Abstract

Background: Amongst the major challenges in next-generation sequencing experiments are exploratory data analysis, interpreting trends, identifying potential targets/candidates, and visualizing the results clearly and intuitively. These hurdles are further heightened for researchers who are not experienced in writing computer code, since the majority of available analysis tools require programming skills. Even for proficient computational biologists, an efficient and replicable system is warranted to generate standardized results. Results: We have developed RNAlysis, a modular Python-based analysis software for RNA sequencing data. RNAlysis allows users to build customized analysis pipelines suiting their specific research questions, going all the way from raw FASTQ files, through exploratory data analysis and data visualization, clustering analysis, and gene-set enrichment analysis. RNAlysis provides a friendly graphical user interface, allowing researchers to analyze data without writing code. We demonstrate the use of RNAlysis by analyzing RNA data from different studies using C. elegans nematodes. We note that the software is equally applicable to data obtained from any organism. Conclusions: RNAlysis is suitable for investigating a variety of biological questions, and allows researchers to more accurately and reproducibly run comprehensive bioinformatic analyses. It functions as a gateway into RNA sequencing analysis for less computer-savvy researchers, but can also help experienced bioinformaticians make their analyses more robust and efficient, as it offers diverse tools, scalability, automation, and standardization between analyses.

A recipe for extremely reproducible enrichment analysis (and why we need it)

“…Some progress is being made to make web-based point-and-click tools more reproducible. The Galaxy, GenePattern and RNAlysis projects offer graphical tools to create, edit and import workflows that enable reproducibility [71][72][73]. The Degust differential expression suite is a graphical interface to popular expression tools like edgeR and limma and allows users to download the computer script to facilitate future non-interactive reproducibility [74].…”

A Tunable and Druggable Mechanism to Delay Forgetting of Olfactory Memories inC. elegans

“…Genes were regarded as differentially expressed if they passed the criterion ofFDR <= 0.1. Further analysis was performed using the python-based package RNAlysis (Teichman et al 2023, Python package version 2.1.1).…”

Peristromal niches protect lung cancers from targeted therapies through a combined effect of multiple molecular mediators

“…The cluster maps reinforce the presence of DEGs unique to each sample, and the potential effects of treatment on the DEGs. Gene set enrichment analysis for the mouse and human mapped genes was performed, using the KEGG7 database 50 (www.kegg.jp) and RNAlysis software 51 to identify the biological pathways that are significantly associated with each sample, and to assess the influence of treatment. We considered KEGG terms with p-adj < 0.05 as significant enrichment.…”