title: Computational Biology Methods for Characterization of Pluripotent Cells.
abstract: Pluripotent cells are a powerful tool for regenerative medicine and drug discovery. Several techniques have been developed to induce pluripotency, or to extract pluripotent cells from different tissues and biological fluids. However, the characterization of pluripotency requires tedious, expensive, time-consuming, and not always reliable wet-lab experiments; thus, an easy, standard quality-control protocol of pluripotency assessment remains to be established. Here to help comes the use of high-throughput techniques, and in particular, the employment of gene expression microarrays, which has become a complementary technique for cellular characterization. Research has shown that the transcriptomics comparison with an Embryonic Stem Cell (ESC) of reference is a good approach to assess the pluripotency. Under the premise that the best protocol is a computer software source code, here I propose and explain line by line a software protocol coded in R-Bioconductor for pluripotency assessment based on the comparison of transcriptomics data of pluripotent cells with an ESC of reference. I provide advice for experimental design, warning about possible pitfalls, and guides for results interpretation.
authors.affiliation: Computational Biology and Systems Biomedicine, Biodonostia Health Research Institute, Calle Doctor Begiristain s/n, 20014, San Sebastián, Spain. mararabra@yahoo.co.uk.|IKERBASQUE, Basque Foundation for Science, Bilbao, Spain. mararabra@yahoo.co.uk.
authors.forename: Marcos J
authors.initials: MJ
authors.lastname: Araúzo-Bravo
mesh_terms: D000818:Animals; D002454:Cell Differentiation; D019070:Cell Lineage; D065150:Cellular Reprogramming; D000067470:Cellular Reprogramming Techniques / Q000379:methods; D019295:Computational Biology; D053595:Embryonic Stem Cells; D015870:Gene Expression; D057166:High-Throughput Screening Assays; D006801:Humans; D057026:Induced Pluripotent Stem Cells / Q000166:cytology* / Q000637:transplantation; D051379:Mice; D008819:Mice, Nude; D025341:Principal Component Analysis; D011994:Recombinant Proteins / Q000235:genetics; D012107:Research Design; D012984:Software; D013724:Teratoma / Q000473:pathology; D014157:Transcription Factors / Q000235:genetics / Q000502:physiology; D059467:Transcriptome
chemical_list: D011994:Recombinant Proteins; D014157:Transcription Factors
keywords: Bioconductor; Cellular reprogramming; Computational biology; Hierarchical clustering; Principal component analysis; R; Scatterplots; Transcriptomics; iPSC