title: Identifying transcriptional miRNA biomarkers by integrating high-throughput sequencing and real-time PCR data.
abstract: Using both high-throughput sequencing and real-time PCR, the miRNA transcriptome can be analyzed in complementary ways. We describe the necessary bioinformatics pipeline, including software tools, and key methodological steps in the process, such as adapter removal, read mapping, normalization, and multiple testing issues for biomarker identification. The methods are exemplified by the analysis of five favorable (event-free survival) vs. five unfavorable (died of disease) neuroblastoma tumor samples with a total of over 188 million reads.
authors.affiliation: Bioinformatics, Computer Science XI, TU Dortmund, Germany; Collaborative Research Center (SFB) 876, TU Dortmund, Germany. Sven.Rahmann@uni-due.de
authors.forename: Sven
authors.initials: S
authors.lastname: Rahmann
authors.forename: Marcel
authors.initials: M
authors.lastname: Martin
authors.forename: Johannes H
authors.initials: JH
authors.lastname: Schulte
authors.forename: Johannes
authors.initials: J
authors.lastname: Köster
authors.forename: Tobias
authors.initials: T
authors.lastname: Marschall
authors.forename: Alexander
authors.initials: A
authors.lastname: Schramm
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000378:metabolism; D002874:Chromosome Mapping; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing / Q000592:standards*; D006801:Humans; D035683:MicroRNAs / Q000235:genetics* / Q000302:isolation & purification / Q000378:metabolism; D009447:Neuroblastoma / Q000235:genetics / Q000378:metabolism; D011786:Quality Control; D060888:Real-Time Polymerase Chain Reaction / Q000592:standards*; D012015:Reference Standards; D012689:Sequence Homology, Nucleic Acid; D012984:Software
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs