Abstract
Chronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) have contrasting clinical and pathological characteristics and interesting whole-genome transcriptomic profiles. However, data from public repositories are difficult to reprocess and reanalyze. Here, we present PulmonDB, a web-based database (http://pulmondb.liigh.unam.mx/) and R library that facilitates exploration of gene expression profiles for these diseases by integrating transcriptomic data and curated annotation from different sources. We demonstrated the value of this resource by presenting the expression of already well-known genes of COPD and IPF across multiple experiments and the results of two differential expression analyses in which we successfully identified differences and similarities. With this first version of PulmonDB, we create a new hypothesis and compare the two diseases from a transcriptomics perspective.
Highlights
Chronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) have contrasting clinical and pathological characteristics and interesting whole-genome transcriptomic profiles
For COPD and IPF, because the information from only a few experiments is available in these resources, such an analysis requires manual annotation by the user or inclusion of only curated Gene Expression Omnibus (GEO) Datasets, and only none of them integrates microarray and RNA-Seq data, to our knowledge
We integrated transcriptomic experiments from different sources and their curated annotations, and built an online web resource to facilitate the exploration of gene expression profiles for COPD and IPF creating new hypotheses, and to allow for the identification of co-expression patterns in further analyses
Summary
Chronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) have contrasting clinical and pathological characteristics and interesting whole-genome transcriptomic profiles. We demonstrated the value of this resource by presenting the expression of already well-known genes of COPD and IPF across multiple experiments and the results of two differential expression analyses in which we successfully identified differences and similarities. With this first version of PulmonDB, we create a new hypothesis and compare the two diseases from a transcriptomics perspective. We integrated transcriptomic experiments from different sources and their curated annotations, and built an online web resource to facilitate the exploration of gene expression profiles for COPD and IPF creating new hypotheses, and to allow for the identification of co-expression patterns in further analyses
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