Integrated Expression Analysis and E-support using Bayesian Models for Affymetrix Exon and Gene Arrays

使用 Affymetrix 外显子和基因阵列的贝叶斯模型进行集成表达分析和电子支持

• 批准号: BB/G000352/1
• 负责人: Alexandra Lewin
• 金额: $ 12.06万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FG000352%2F1
• 关键词: Integrated; Expression; Analysis; support; using

DNA microarrays measure the expression of thousands of genes simultaneously. In the past decade they have become the standard technology for studying gene expression differences between different experimental conditions, for example between individuals suffering from certain diseases and unaffected individuals. The latest generation of Affymetrix microarrays have increased the resolution of genomic expression detection from the gene level down to the exon level, enabling measurement of different splice variants. Currently there are very few tools to take advantage of the additional information contained within these Exon arrays. The aim of this project is to develop powerful and robust methods for Exon array analysis including alternative splice detection and gene expression analyses. The software will be made available for researchers to download and use on their own sytem. In addition, data sets from microarray experiments can be very large and complex. The use of such high-throughput technology brings challenges for researchers in terms of data analysis and storage. Many biologists do not have direct collaboration with statisticians and bioinformaticians who are able to advise on and carry out data analysis. Thus there is a need for readily available analysis tools, in a form accessible to the biological community. Therefore this project also aims to present the developed analysis methods in a user friendly analysis environment, along with technical support and training software. The work will build on an existing resource called EMAAS, created for microarray data analysis and management which has been developed by the Bioinformatics Support Service at Imperial College. This utilises Grid clusters of computers which allows very fast data analysis, accessed via a user-friendly web interface.

DNA微阵列可以同时测量数千个基因的表达。在过去的十年中，它们已经成为研究不同实验条件之间基因表达差异的标准技术，例如患有某些疾病的个体和未受影响的个体之间。最新一代的Affytek微阵列提高了从基因水平到外显子水平的基因组表达检测的分辨率，从而能够测量不同的剪接变体。目前，很少有工具可以利用这些外显子阵列中包含的额外信息。该项目的目的是开发强大的和强大的外显子阵列分析方法，包括选择性剪接检测和基因表达分析。该软件将供研究人员下载并在自己的系统上使用。此外，来自微阵列实验的数据集可能非常庞大和复杂。这种高通量技术的使用为研究人员在数据分析和存储方面带来了挑战。许多生物学家没有与统计学家和生物信息学家直接合作，他们能够提供建议并进行数据分析。因此，有必要以生物界可以获得的形式提供现成的分析工具。因此，本项目的目的也是在一个用户友好的分析环境，沿着技术支持和培训软件的开发分析方法。这项工作将建立在现有的资源称为EMAAS，创建微阵列数据分析和管理，已开发的生物信息学支持服务在帝国理工学院。这利用了计算机的网格集群，可以通过用户友好的Web界面进行非常快速的数据分析。

项目成果

On fuzzy familywise error rate and false discovery rate procedures for discrete distributions

• DOI: 10.1093/biomet/asn061
• 发表时间: 2009-03-01
• 期刊: BIOMETRIKA
• 影响因子: 2.7
• 作者: Kulinskaya, Elena;Lewin, Alex
• 通讯作者: Lewin, Alex

Sarcoidosis and tuberculosis cytokine profiles: indistinguishable in bronchoalveolar lavage but different in blood.

• DOI: 10.1371/journal.pone.0038083
• 发表时间: 2012
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Thillai M;Eberhardt C;Lewin AM;Potiphar L;Hingley-Wilson S;Sridhar S;Macintyre J;Kon OM;Wickremasinghe M;Wells A;Weeks ME;Mitchell D;Lalvani A
• 通讯作者: Lalvani A

Free serum haemoglobin is associated with brain atrophy in secondary progressive multiple sclerosis.

• DOI: 10.12688/wellcomeopenres.9967.2
• 发表时间: 2016-11-15
• 期刊: Wellcome open research
• 作者: Lewin A;Hamilton S;Witkover A;Langford P;Nicholas R;Chataway J;Bangham CRM
• 通讯作者: Bangham CRM

Plasma proteome analysis in HTLV-1-associated myelopathy/tropical spastic paraparesis.

• DOI: 10.1186/1742-4690-8-81
• 发表时间: 2011-10-12
• 期刊: Retrovirology
• 影响因子: 3.3
• 作者: Kirk PD;Witkover A;Courtney A;Lewin AM;Wait R;Stumpf MP;Richardson S;Taylor GP;Bangham CR
• 通讯作者: Bangham CR

Balancing the robustness and predictive performance of biomarkers.

• DOI: 10.1089/cmb.2013.0018
• 发表时间: 2013-12
• 期刊: Journal of computational biology : a journal of computational molecular cell biology
• 作者: Kirk P;Witkover A;Bangham CR;Richardson S;Lewin AM;Stumpf MP
• 通讯作者: Stumpf MP