Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data.
Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data.
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DOI：
10.1038/s41467-021-24584-w
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发表时间：
2021-07-19
影响因子：
16.6
通讯作者：
Chaussabel D
中科院分区：
文献类型：
--
作者：
Altman MC;Rinchai D;Baldwin N;Toufiq M;Whalen E;Garand M;Syed Ahamed Kabeer B;Alfaki M;Presnell SR;Khaenam P;Ayllón-Benítez A;Mougin F;Thébault P;Chiche L;Jourde-Chiche N;Phillips JT;Klintmalm G;O'Garra A;Berry M;Bloom C;Wilkinson RJ;Graham CM;Lipman M;Lertmemongkolchai G;Bedognetti D;Thiebaut R;Kheradmand F;Mejias A;Ramilo O;Palucka K;Pascual V;Banchereau J;Chaussabel D
随着生成大规模分子谱数据的能力不断增长，从中提取有意义的生物学知识的能力仍然受到限制。在这里，我们描述了一个新的固定剧目的转录模块，BloodGen3，旨在作为一个稳定的可重复使用的框架，分析和解释血液转录组数据的发展。该库的构建基于在16种免疫和生理状态下观察到的共聚类模式，包括985个血液转录组谱。解释由定制资源支持，包括模块级分析工作流程，指纹网格图可视化，交互式Web应用程序和广泛的注释框架，包括功能分析报告和参考转录概况。总之，这种良好表征和良好支持的转录模块库可用于患者队列内和跨患者队列的血液转录组谱的解释和基准。16个参考队列的血液转录组指纹可通过https://drinchai.shinyapps.io/BloodGen3Module/交互访问。人类受试者的血液转录组可以在转化研究环境中几乎常规地进行分析。在这里，作者表明，一个固定的和良好的特点剧目转录模块可以作为一个可重用的框架，分析，可视化和解释这样的数据
As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via: https://drinchai.shinyapps.io/BloodGen3Module/. The blood transcriptome of human subjects can be profiled on an almost routine basis in translational research settings. Here the authors show that a fixed and well-characterized repertoire of transcriptional modules can be employed as a reusable framework for the analysis, visualization and interpretation of such data
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影响因子：
30.5
作者：
Alsina, Laia;Israelsson, Elisabeth;Altman, Matthew C.;Dang, Kristen K.;Ghandil, Pegah;Israel, Laura;von Bernuth, Horst;Baldwin, Nicole;Qin, Huanying;Jin, Zongbo;Banchereau, Romain;Anguiano, Esperanza;Ionan, Alexei;Abel, Laurent;Puel, Anne;Picard, Capucine;Pascual, Virginia;Casanova, Jean Laurent;Chaussabel, Damien
通讯作者：
Chaussabel, Damien
影响因子：
3.7
作者：
Linsley PS;Speake C;Whalen E;Chaussabel D
通讯作者：
Chaussabel D
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
13.3
作者：
Chiche, Laurent;Jourde-Chiche, Noemie;Whalen, Elizabeth;Presnell, Scott;Gersuk, Vivian;Dang, Kristen;Anguiano, Esperanza;Quinn, Charlie;Burtey, Stephane;Berland, Yvon;Kaplanski, Gilles;Harle, Jean-Robert;Pascual, Virginia;Chaussabel, Damien
通讯作者：
Chaussabel, Damien
影响因子：
5.8
作者：
Gu, Zuguang;Eils, Roland;Schlesner, Matthias
通讯作者：
Schlesner, Matthias