Probabilistic analysis of gene expression measurements from heterogeneous tissues.
Probabilistic analysis of gene expression measurements from heterogeneous tissues.
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DOI：
10.1093/bioinformatics/btq406
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发表时间：
2010-10-15
期刊：
影响因子：
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通讯作者：
Lähdesmäki H
中科院分区：
文献类型：
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作者：
Erkkilä T;Lehmusvaara S;Ruusuvuori P;Visakorpi T;Shmulevich I;Lähdesmäki H
动机：由多种细胞类型引起的组织异质性是专注于研究细胞类型（例如，它们的单独表达谱）的实验中的主要混杂因素。虽然样品异质性可以通过手动显微切割来解决，但在进行实验之前，对异质性测量的计算处理已经成为在计算机上进行这种显微切割的可靠替代方案。与人工纯化相比，支持计算具有其优点，例如耗时、同时测量多种细胞类型的响应、保持样品不受外部扰动以及分子含量的产率不变。结果如下：我们正式的概率模型，DSection，并显示与模拟以及与真实的微阵列数据，DSection达到增加建模精度方面（i）估计细胞类型的异质性组织样本的比例，（ii）估计复制方差和（iii）确定不同的实验条件下的细胞类型的差异表达。作为我们的参考，我们使用相应的线性回归模型，它反映了当前大多数非概率建模方法的性能。可用性和软件：所有代码都是用Matlab编写的，可根据要求免费获得，也可在项目网页http：//www.cs.tut.fi/jerkkila2/上获得。此外，在http://informatics.systemsbiology.net/DSection上有一个DSection的网上应用程序。联系人：timo.p. tut.fi; harri. tut.fi
Motivation: Tissue heterogeneity, arising from multiple cell types, is a major confounding factor in experiments that focus on studying cell types, e.g. their expression profiles, in isolation. Although sample heterogeneity can be addressed by manual microdissection, prior to conducting experiments, computational treatment on heterogeneous measurements have become a reliable alternative to perform this microdissection in silico. Favoring computation over manual purification has its advantages, such as time consumption, measuring responses of multiple cell types simultaneously, keeping samples intact of external perturbations and unaltered yield of molecular content. Results: We formalize a probabilistic model, DSection, and show with simulations as well as with real microarray data that DSection attains increased modeling accuracy in terms of (i) estimating cell-type proportions of heterogeneous tissue samples, (ii) estimating replication variance and (iii) identifying differential expression across cell types under various experimental conditions. As our reference we use the corresponding linear regression model, which mirrors the performance of the majority of current non-probabilistic modeling approaches. Availability and Software: All codes are written in Matlab, and are freely available upon request as well as at the project web page http://www.cs.tut.fi/∼erkkila2/. Furthermore, a web-application for DSection exists at http://informatics.systemsbiology.net/DSection. Contact: timo.p.erkkila@tut.fi; harri.lahdesmaki@tut.fi