DOI QR코드

DOI QR Code

HisCoM-PAGE: software for hierarchical structural component models for pathway analysis of gene expression data

  • Mok, Lydia (Interdisciplinary Program in Bioinformatics, Seoul National University) ;
  • Park, Taesung (Interdisciplinary Program in Bioinformatics, Seoul National University)
  • Received : 2019.11.19
  • Accepted : 2019.11.22
  • Published : 2019.12.31

Abstract

To identify pathways associated with survival phenotypes using gene expression data, we recently proposed the hierarchical structural component model for pathway analysis of gene expression data (HisCoM-PAGE) method. The HisCoM-PAGE software can consider hierarchical structural relationships between genes and pathways and analyze multiple pathways simultaneously. It can be applied to various types of gene expression data, such as microarray data or RNA sequencing data. We expect that the HisCoM-PAGE software will make our method more easily accessible to researchers who want to perform pathway analysis for survival times.

Keywords

References

  1. Casamassimi A, Federico A, Rienzo M, Esposito S, Ciccodicola A. Transcriptome profiling in human diseases: new advances and perspectives. Int J Mol Sci 2017;18:E1652.
  2. Jacquier A. The complex eukaryotic transcriptome: unexpected pervasive transcription and novel small RNAs. Nat Rev Genet 2009;10:833-844. https://doi.org/10.1038/nrg2683
  3. Byron SA, Van Keuren-Jensen KR, Engelthaler DM, Carpten JD, Craig DW. Translating RNA sequencing into clinical diagnostics: opportunities and challenges. Nat Rev Genet 2016;17:257-271. https://doi.org/10.1038/nrg.2016.10
  4. Lee S, Kim J, Lee S. A comparative study on gene-set analysis methods for assessing differential expression associated with the survival phenotype. BMC Bioinformatics 2011;12:377. https://doi.org/10.1186/1471-2105-12-377
  5. Glazko GV, Emmert-Streib F. Unite and conquer: univariate and multivariate approaches for finding differentially expressed gene sets. Bioinformatics 2009;25:2348-2354. https://doi.org/10.1093/bioinformatics/btp406
  6. Khatri P, Sirota M, Butte AJ. Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol 2012;8:e1002375. https://doi.org/10.1371/journal.pcbi.1002375
  7. Mok L, Kim Y, Lee S, Choi S, Lee S, Jang JY, et al. HisCoM-PAGE: hierarchical structural component models for pathway analysis of gene expression data. Genes (Basel) 2019;10:E931.
  8. Lee S, Choi S, Kim YJ, Kim BJ, Consortium Td-G, Hwang H, et al. Pathway-based approach using hierarchical components of collapsed rare variants. Bioinformatics 2016;32:i586-i594. https://doi.org/10.1093/bioinformatics/btw425
  9. Kim Y, Lee S, Choi S, Jang JY, Park T. Hierarchical structural component modeling of microRNA-mRNA integration analysis. BMC Bioinformatics 2018;19:75. https://doi.org/10.1186/s12859-018-2070-0
  10. Choi S, Lee S, Kim Y, Hwang H, Park T. HisCoM-GGI: Hierarchical structural component analysis of gene-gene interactions. J Bioinform Comput Biol 2018;16:1840026. https://doi.org/10.1142/s0219720018400267
  11. Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 1999;27:29-34. https://doi.org/10.1093/nar/27.1.29
  12. Nishimura D. BioCarta. Biotech Softw Internet Rep 2001;2:117-120. https://doi.org/10.1089/152791601750294344
  13. Kim Y, Park T. HisCoM-mimi: software for hierarchical structural component analysis for miRNA-mRNA integration model for binary phenotypes. Genomics Inform 2019;17:e10. https://doi.org/10.5808/GI.2019.17.1.e10
  14. Choi S, Lee S, Park T. HisCoM-GGI: software for hierarchical structural component analysis of gene-gene interactions. Genomics Inform 2018;16:e38. https://doi.org/10.5808/GI.2018.16.4.e38