ArticlePloS one2016
hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- The mutational profile of immune surveillance genes in diagnostic and refractory/relapsed DLBCLs.BMC cancer · 2021Article
- Article
- A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.Blood advances · 2018Article
- A B-cell-associated gene signature classification of diffuse large B-cell lymphoma by NanoString technology.Blood advances · 2018Article
- Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow - A proof of concept study.PloS one · 2018Article
- Molecular classification of tissue from a transformed non-Hogkin's lymphoma case with unexpected long-time remission.Experimental hematology & oncology · 2017Article
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Authors and funding
13 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDozens 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.
resultsThis 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.
conclusionsThe 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.
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