Literature DB >> 18565726

Finding common genes in multiple cancer types through meta-analysis of microarray experiments: a rank aggregation approach.

V Pihur1, Somnath Datta, Susmita Datta.   

Abstract

Discovering genes involved in multiple types of cancers is of significant therapeutic importance. We show that collective evidence for such genes can be obtained via a form of meta-analysis that aggregates the results (rankings and p values) from various cancer-specific microarray experiments. This method is illustrated by a combined analysis of 20 microarray experiments. In the aggregated list of top-50 genes, 36 of them have been implicated in cancer (often multiple cancers) genesis in past studies, which also suggests that this list may contain some novel cancer genes that may deserve further scrutiny in the future.

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Year:  2008        PMID: 18565726     DOI: 10.1016/j.ygeno.2008.05.003

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  23 in total

Review 1.  The role of imprinted genes in fetal growth abnormalities.

Authors:  Jorge A Piedrahita
Journal:  Birth Defects Res A Clin Mol Teratol       Date:  2011-06-06

2.  Integrated Analysis of RNA and DNA from the Phase III Trial CALGB 40601 Identifies Predictors of Response to Trastuzumab-Based Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer.

Authors:  Maki Tanioka; Cheng Fan; Joel S Parker; Katherine A Hoadley; Zhiyuan Hu; Yan Li; Terry M Hyslop; Brandelyn N Pitcher; Matthew G Soloway; Patricia A Spears; Lynn N Henry; Sara Tolaney; Chau T Dang; Ian E Krop; Lyndsay N Harris; Donald A Berry; Elaine R Mardis; Eric P Winer; Clifford A Hudis; Lisa A Carey; Charles M Perou
Journal:  Clin Cancer Res       Date:  2018-07-23       Impact factor: 12.531

3.  Disease signatures are robust across tissues and experiments.

Authors:  Joel T Dudley; Robert Tibshirani; Tarangini Deshpande; Atul J Butte
Journal:  Mol Syst Biol       Date:  2009-09-15       Impact factor: 11.429

4.  Independent validation test of the vote-counting strategy used to rank biomarkers from published studies.

Authors:  Brad A Rikke; Murry W Wynes; Leslie M Rozeboom; Anna E Barón; Fred R Hirsch
Journal:  Biomark Med       Date:  2015-07-30       Impact factor: 2.851

5.  DawnRank: discovering personalized driver genes in cancer.

Authors:  Jack P Hou; Jian Ma
Journal:  Genome Med       Date:  2014-07-31       Impact factor: 11.117

6.  Network selection: a method for ranked lists selection.

Authors:  Luisa Cutillo; Annamaria Carissimo; Silvia Figini
Journal:  PLoS One       Date:  2012-08-24       Impact factor: 3.240

7.  MGEx-Udb: a mammalian uterus database for expression-based cataloguing of genes across conditions, including endometriosis and cervical cancer.

Authors:  Akhilesh K Bajpai; Sravanthi Davuluri; Darshan S Chandrashekar; Selvarajan Ilakya; Mahalakshmi Dinakaran; Kshitish K Acharya
Journal:  PLoS One       Date:  2012-05-11       Impact factor: 3.240

8.  Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods.

Authors:  Priit Adler; Raivo Kolde; Meelis Kull; Aleksandr Tkachenko; Hedi Peterson; Jüri Reimand; Jaak Vilo
Journal:  Genome Biol       Date:  2009-12-04       Impact factor: 13.583

9.  Role of opiorphin genes in prostate cancer growth and progression.

Authors:  Amarnath Mukherjee; Augene Park; Li Wang; Kelvin P Davies
Journal:  Future Oncol       Date:  2021-02-17       Impact factor: 3.404

10.  Feature Ranking and Screening for Class-Imbalanced Metabolomics Data Based on Rank Aggregation Coupled with Re-Balance.

Authors:  Guang-Hui Fu; Jia-Bao Wang; Min-Jie Zong; Lun-Zhao Yi
Journal:  Metabolites       Date:  2021-06-14
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