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hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine
- Source :
- PLoS ONE, Larsen, S F, Ellern Bilgrau, A, Brøndum, R F, Hjort Jakobsen, L, Have, J, Lindblad Nielsen, K, El-Galaly, T C, Bødker, J S, Schmitz, A, H Young, K, Johnsen, H E, Dybkær, K & Bøgsted, M 2016, ' hemaClass.org : Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine ', P L o S One, vol. 11, no. 10, e0163711 . https://doi.org/10.1371/journal.pone.0163711, PLoS ONE, Vol 11, Iss 10, p e0163711 (2016)
- Publication Year :
- 2016
-
Abstract
- BACKGROUND: Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting.RESULTS: This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically.CONCLUSIONS: The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.
- Subjects :
- 0301 basic medicine
Male
B Cells
Microarray
Microarrays
Cancer Treatment
lcsh:Medicine
Datasets as Topic
Gene Expression
Web Browser
Bioinformatics
computer.software_genre
Computer Applications
Plasma Cell Disorders
Workflow
Hematologic Cancers and Related Disorders
White Blood Cells
Animal Cells
Medicine and Health Sciences
Medicine
Precision Medicine
lcsh:Science
Multidisciplinary
Patient portal
Hematology
Middle Aged
Tonsils
Bioassays and Physiological Analysis
Oncology
Hematologic Neoplasms
Web-Based Applications
Lymphomas
DNA microarray
Anatomy
Cellular Types
Multiple Myeloma
Research Article
Normalization (statistics)
Adult
Computer and Information Sciences
Immune Cells
Immunology
Machine learning
Research and Analysis Methods
Throat
03 medical and health sciences
Patient Portals
Genetics
Web application
Humans
Antibody-Producing Cells
Aged
Blood Cells
business.industry
Gene Expression Profiling
lcsh:R
Computational Biology
Reproducibility of Results
Biology and Life Sciences
Cancers and Neoplasms
Cell Biology
Precision medicine
030104 developmental biology
lcsh:Q
Artificial intelligence
business
computer
Software
Neck
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 11
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- PloS one
- Accession number :
- edsair.doi.dedup.....14bf142a4151f5b40bb7f5dc535a039e
- Full Text :
- https://doi.org/10.1371/journal.pone.0163711