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hemaClass.org:用于精准医学的血液病在线逐个微阵列标准化和分类。

hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

机构信息

Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.

Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.

出版信息

PLoS One. 2016 Oct 4;11(10):e0163711. doi: 10.1371/journal.pone.0163711. eCollection 2016.

DOI:10.1371/journal.pone.0163711
PMID:27701436
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5049784/
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.

摘要

背景

已经提出了数十种基于组学的癌症分类系统,具有预后、诊断和预测能力。然而,它们通常采用复杂的算法,并且仅适用于整个患者队列,因此难以在个性化的临床环境中应用。

结果

这促使我们创建了 hemaClass.org,这是一个在线网络应用程序,提供了一个简单的界面,可对微阵列进行逐个 RMA 标准化,并随后将弥漫性大 B 细胞淋巴瘤 (DLBCL) 分为起源细胞和化疗敏感性类别进行风险分类。在 4 个公开可用的数据集上,比较了逐个阵列预处理和没有实验室特定 RMA 参考数据集的分类结果与基于队列的分类器。当提供实验室特定的参考集时,分类结果在逐个和整个队列预处理数据之间显示出高度一致性。该网站本质上是 hemaClass 的 R 包,带有一个闪亮的网络应用程序。该文档齐全的软件包可用于在本地运行网站或使用开发的方法进行编程。

结论

该网站和 R 包适用于使用 Affymetrix U-133 Plus 2 阵列的生物和临床淋巴瘤研究人员,因为它为计算疾病亚类提供了可靠且快速的方法。所提出的逐个预处理方法适用于所有使用微阵列的研究人员。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f7a/5049784/99dcbf14c991/pone.0163711.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f7a/5049784/6e5371e186f2/pone.0163711.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f7a/5049784/a0046cddb27e/pone.0163711.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f7a/5049784/99dcbf14c991/pone.0163711.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f7a/5049784/6e5371e186f2/pone.0163711.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f7a/5049784/a0046cddb27e/pone.0163711.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f7a/5049784/99dcbf14c991/pone.0163711.g003.jpg

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