VizR (VIsualiZation of Rna seq), a web- based platform that integrates end-to-end RNA-seq analysis and visualization within a single integrated environment, lowers the technical barrier to transcriptome analysis and provides a practical platform for plant biology research.
Abstract
RNA sequencing (RNA-seq) is widely used to investigate transcriptional programs in plant biology, yet the need to combine multiple specialized tools and bioinformatics expertise to convert raw sequencing reads into biologically interpretable results remains a major technical barrier for many plant biologists. Here, we present VizR (VIsualiZation of Rna seq), a web- based platform that integrates end-to-end RNA-seq analysis and visualization within a single integrated environment. VizR automates upstream processing, including quality control, adapter trimming, genome alignment, and transcript quantification, and connects the resulting expression data to downstream exploratory analyses. Its interface is designed to make expression patterns immediately searchable and interpretable: users can query genes through an equalizer-style expression-pattern interface, inspect expression profiles using inline heatmaps embedded in gene tables, and perform context-integrated gene ontology analysis throughout the workflow. VizR also supports comparative analysis through interactive Venn diagram module, allowing users to transfer gene sets directly from result tables. As a Docker- based application, VizR can be deployed locally and accessed through a standard web browser. By unifying automated RNA-seq processing, interactive visualization, and functional interpretation, VizR lowers the technical barrier to transcriptome analysis and provides a practical platform for plant biology research.
FetchPA is an intuitive pipeline which allows users with virtually no scripting and version control experience to install and manage all software for end-to-end analyses of ATAC-Seq data and guides the user through the identification of differentially accessible regions.
Dustin R. Fetch, Alexey A. Soshnev· bioRxiv· 0 citations
Bulk RNA-sequencing is routine, but turning a gene-level count matrix into biological insight still requires combining specialised tools for quality control, differential expression, dimensionality reduction, enrichment, co-expression networks, and activity inference. These steps are typically performed either wi...
Karim Matmat, Tamara Pfanner, Rafael P. Silveira et al.· BMC Bioinformatics· 0 citations
Graphical abstract Translation elongation relies on accurate codon-anticodon pairing. Here, we present tTEscanR, an R package designed to investigate this translational interface. By quantifying mRNA codon demand alongside tRNA anticodon availability, tTEscanR provides scalable estimates of translation rates directly f...
Ana Varas-Sánchez, Carlos J. Gallardo-Dodd, Qun Li et al.· bioRxiv· 0 citations
Background/Objectives: ATAC-seq footprinting can infer transcription-factor (TF) occupancy across the genome at near-base-pair resolution. However, its broad adoption is limited by high computational demands, complex command-line workflows, and fragmented support for bulk data with biological replicates and single-cell...
Bulk RNA-seq and single-cell RNA-seq (scRNA-seq) are widely used to investigate gene-expression changes, but downstream analysis often requires multiple statistical, visualization, and reporting tools, creating fragmented workflows that are difficult to configure and reproduce. We developed CoTRA (Comprehensive Toolbox...
Abstract RNA–RNA interactions (RRI) can now be probed on a transcriptome-wide scale using proximity ligation methods such as SPLASH, PARIS, LIGR-seq, RIC-seq, and others. While individual pipelines for computationally processing the corresponding raw duplex reads exist, there is currently no method for comparing and ex...
Egor Semenchenko, Jing-Wen Luo, Volodymyr Tsybulskyi et al.· NAR Genomics and Bioinformat...· 0 citations
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