A Single-Subject Method to Detect Pathways Enriched With Alternatively Spliced Genes
暂无分享,去创建一个
Yves A. Lussier | Colleen Kenost | Dillon Aberasturi | Alfred Grant Schissler | Y. Lussier | C. Kenost | Dillon Aberasturi | A. G. Schissler
[1] Bradley Efron,et al. Local False Discovery Rates , 2005 .
[2] B. Efron. Correlation and Large-Scale Simultaneous Significance Testing , 2007 .
[3] Richard E. Neapolitan. Analyzing Gene Expression Data , 2009 .
[4] Peter Bühlmann,et al. Analyzing gene expression data in terms of gene sets: methodological issues , 2007, Bioinform..
[5] C. Perou,et al. Molecular Subtypes in Breast Cancer Evaluation and Management: Divide and Conquer , 2008, Cancer investigation.
[6] Yves A Lussier,et al. Testing for differentially expressed genetic pathways with single-subject N-of-1 data in the presence of inter-gene correlation , 2018, Statistical methods in medical research.
[7] Mary Goldman,et al. The UCSC Cancer Genomics Browser: update 2015 , 2014, Nucleic Acids Res..
[8] Marla Johnson,et al. Clustering of mRNA-Seq data for detection of alternative splicing patterns , 2015, bioRxiv.
[9] Sorin Draghici,et al. MicroRNA-Augmented Pathways (mirAP) and Their Applications to Pathway Analysis and Disease Subtyping , 2017, PSB.
[10] Taesung Park,et al. Personalized identification of altered pathways in cancer using accumulated normal tissue data , 2014, Bioinform..
[11] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[12] M. Ladomery. Aberrant Alternative Splicing Is Another Hallmark of Cancer , 2013, International journal of cell biology.
[13] F. Collins,et al. A new initiative on precision medicine. , 2015, The New England journal of medicine.
[14] I. Langner. Survival Analysis: Techniques for Censored and Truncated Data , 2006 .
[15] Elizabeth Purdom,et al. Clustering of mRNA‐Seq data based on alternative splicing patterns , 2017, Biostatistics.
[16] Genevera I. Allen,et al. TCGA2STAT: simple TCGA data access for integrated statistical analysis in R , 2016, Bioinform..
[17] Yves A. Lussier,et al. Dynamic changes of RNA-sequencing expression for precision medicine: N-of-1-pathways Mahalanobis distance within pathways of single subjects predicts breast cancer survival , 2015, Bioinform..
[18] Yong Huang,et al. Single Sample Expression-Anchored Mechanisms Predict Survival in Head and Neck Cancer , 2012, PLoS Comput. Biol..
[19] Yves A. Lussier,et al. kMEn: Analyzing noisy and bidirectional transcriptional pathway responses in single subjects , 2017, J. Biomed. Informatics.
[20] Yves A. Lussier,et al. N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes , 2017, BMC Medical Genomics.
[21] Atul J. Butte,et al. Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges , 2012, PLoS Comput. Biol..
[22] John G Kenny,et al. Transcriptome sequencing of human breast cancer reveals aberrant intronic transcription in amplicons and dysregulation of alternative splicing with major therapeutic implications. , 2016, International journal of oncology.
[23] Hiroyuki Ogata,et al. KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..
[24] Dawei Li,et al. High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery , 2020, Frontiers in Genetics.
[25] Minoru Yoshida,et al. Splicing in oncogenesis and tumor suppression , 2012, Cancer science.
[26] B. Efron. Large-Scale Simultaneous Hypothesis Testing , 2004 .
[27] Maria Teresa Bustamante-Teixeira,et al. [Survival analysis techniques]. , 2002, Cadernos de saude publica.
[28] S. Sugano,et al. Frequent pathway mutations of splicing machinery in myelodysplasia , 2011, Nature.
[29] Hugo Y. K. Lam,et al. Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes , 2012, Cell.
[30] C. Perou,et al. Molecular Features and Survival Outcomes of the Intrinsic Subtypes Within HER2-Positive Breast Cancer , 2014, Journal of the National Cancer Institute.
[31] Mary Goldman,et al. The UCSC Cancer Genomics Browser: update 2015 , 2014, Nucleic Acids Res..
[32] Pablo Tamayo,et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[33] C. Perou,et al. Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. , 2005, Cancer research.
[34] Ian T. Foster,et al. ‘N-of-1-pathways’ unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine , 2014, J. Am. Medical Informatics Assoc..
[35] John G Kenny,et al. Transcriptome sequencing of human breast cancer reveals aberrant intronic transcription in amplicons and dysregulation of alternative splicing with major therapeutic implications , 2017, International journal of oncology.
[36] R. Tibshirani,et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[37] Mark T. W. Ebbert,et al. PAM50 Breast Cancer Subtyping by RT-qPCR and Concordance with Standard Clinical Molecular Markers , 2012, BMC Medical Genomics.