Pop’s Pipes: poplar gene expression data analysis pipelines

Abstract

We developed multiple gene expression pipelines and assembled them into a web-based tool called Pop's Pipes to facilitate preprocessing and analysis of substantial poplar gene expression data. The input data can be spatio- temporal microarray and RNA-seq data from comparable tissues, time points, or treatment-vs-control conditions. Pop's Pipes can be used to identify differentially expressed genes between one or multiple paired tissues, time points, or treatment-vs-control conditions in a single in silico anal- ysis. The differentially expressed genes (DEGs) obtained for each comparison will be automatically analyzed by Pop's Pipes for identifying significantly enriched gene on- tologies and interpro protein domains. Also, significantly changed metabolic pathways across all input data sets will be identified. We also integrated a pipeline into Pop's Pipes for constructing any of three type gene ontology trees when a short list of gene ontologies from biological processes, molecular functions, or cellular components is used as an input. The resulting information from Pop's Pipes enables scrutiny to create spatiotemporal models and hypotheses to understand how poplar develops and functions. Pop' sP ipes can analyze a microarray or RNA-seq data set with 10 time points in 4-10 h, with each time point containing three replicates of treatments and three controls. Such a data set usually takes a bioinformatician a few months to a year to analyze. Pop's Pipes can thus save users tremendous amounts of research time when large numbers of compara- tive data need to be analyzed.