title: SIBER: systematic identification of bimodally expressed genes using RNAseq data.
abstract: BACKGROUND
  Identification of bimodally expressed genes is an important task, as genes with bimodal expression play important roles in cell differentiation, signalling and disease progression. Several useful algorithms have been developed to identify bimodal genes from microarray data. Currently, no method can deal with data from next-generation sequencing, which is emerging as a replacement technology for microarrays.
  
  
  RESULTS
  We present SIBER (systematic identification of bimodally expressed genes using RNAseq data) for effectively identifying bimodally expressed genes from next-generation RNAseq data. We evaluate several candidate methods for modelling RNAseq count data and compare their performance in identifying bimodal genes through both simulation and real data analysis. We show that the lognormal mixture model performs best in terms of power and robustness under various scenarios. We also compare our method with alternative approaches, including profile analysis using clustering and kurtosis (PACK) and cancer outlier profile analysis (COPA). Our method is robust, powerful, invariant to shifting and scaling, has no blind spots and has a sample-size-free interpretation.
  
  
  BACKGROUND
  The R package SIBER is available at the website http://bioinformatics.mdanderson.org/main/OOMPA:Overview.
authors.affiliation: Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
authors.forename: Pan
authors.initials: P
authors.lastname: Tong
authors.forename: Yong
authors.initials: Y
authors.lastname: Chen
authors.forename: Xiao
authors.initials: X
authors.lastname: Su
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Coombes
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism; D016000:Cluster Analysis; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software