bioRxivGenomicsPreprint
Phinch: An interactive, exploratory data visualization framework for –Omic datasets
Abstract
Using environmental sequencing approaches, we now have the ability to deeply characterize biodiversity and biogeographic patterns in understudied, uncultured microbial taxa (investigations of bacteria, archaea, and microscopic eukaryotes using 454/Illumina sequencing platforms). However, the sheer volume of data produced from these new technologies requires fundamentally different approaches and new paradigms for effective data analysis. Scientific visualization represents an innovative method towards tackling the current bottleneck in bioinformatic workflows. In addition to giving researchers a unique approach for exploring large datasets, it stands to empower biologists with the ability to conduct powerful analyses without requiring a deep level of computational knowledge. Here we present Phinch, an interactive, browser-based visualization framework that can be used to explore and analyze biological patterns in high-throughput -Omic datasets. This project takes advantage of standard file formats from computational pipelines in order to bridge the gap between biological software (e.g. microbial ecology pipelines) and existing data visualization capabilities (harnessing the flexibility and scalability of technologies such as HTML5).
- assay: metagenomics
- research focus: database / resource
- research focus: benchmarking
- research focus: software / tool
- approach: deep learning
- approach: statistical model
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