title: Revisiting global gene expression analysis.
abstract: Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease, and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from multiple analysis platforms.
authors.affiliation: Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, USA.
authors.forename: Jakob
authors.initials: J
authors.lastname: Lovén
authors.forename: David A
authors.initials: DA
authors.lastname: Orlando
authors.forename: Alla A
authors.initials: AA
authors.lastname: Sigova
authors.forename: Charles Y
authors.initials: CY
authors.lastname: Lin
authors.forename: Peter B
authors.initials: PB
authors.lastname: Rahl
authors.forename: Christopher B
authors.initials: CB
authors.lastname: Burge
authors.forename: David L
authors.initials: DL
authors.lastname: Levens
authors.forename: Tong Ihn
authors.initials: TI
authors.lastname: Lee
authors.forename: Richard A
authors.initials: RA
authors.lastname: Young
mesh_terms: D020869:Gene Expression Profiling / Q000379:methods*; D055106:Genome-Wide Association Study; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D016271:Proto-Oncogene Proteins c-myc / Q000235:genetics; D017423:Sequence Analysis, RNA; D014158:Transcription, Genetic
chemical_list: C489427:MYC protein, human; D016271:Proto-Oncogene Proteins c-myc