Laboratorio Internacional de Investigación sobre el Genoma Humano, UNAM, Juriquilla, Mexico.
Unit of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.
Sci Rep. 2020 Jan 16;10(1):514. doi: 10.1038/s41598-019-56339-5.
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.
慢性阻塞性肺疾病(COPD)和特发性肺纤维化(IPF)具有截然不同的临床和病理特征,以及有趣的全基因组转录组特征。然而,来自公共存储库的数据很难重新处理和重新分析。在这里,我们展示了 PulmonDB,这是一个基于网络的数据库(http://pulmondb.liigh.unam.mx/)和 R 库,通过整合来自不同来源的转录组数据和精心注释,方便探索这些疾病的基因表达谱。我们通过展示 COPD 和 IPF 中已经众所周知的基因在多个实验中的表达情况,以及两个差异表达分析的结果,证明了该资源的价值,我们成功地识别了差异和相似之处。通过 PulmonDB 的第一个版本,我们从转录组学的角度提出了一个新的假设,并对这两种疾病进行了比较。