Assessment of engineered cells using CellNet and RNA-seq.
Assessment of engineered cells using CellNet and RNA-seq.
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DOI：
10.1038/nprot.2017.022
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发表时间：
2017-05
期刊：
影响因子：
14.8
通讯作者：
Cahan P
中科院分区：
文献类型：
--
作者：
Radley AH;Schwab RM;Tan Y;Kim J;Lo EKW;Cahan P
CellNet是一个计算平台，旨在评估通过多能干细胞的定向分化或通过直接转化工程化的细胞群，并提出具体的假设，以改善细胞命运工程方案。CellNet将基因表达数据作为输入，并将其与从公共来源汇编的正常表达谱的大型数据集进行比较，以确定细胞和组织特异性基因调控网络的建立程度。CellNet最初设计用于处理21种细胞和组织类型的人类或小鼠微阵列表达数据。在这里，我们描述了如何将CellNet应用于RNA-Seq数据，以及如何构建适用于其他物种或其他细胞和组织类型的全新CellNet平台。一旦原始数据经过预处理，运行CellNet只需要几分钟，而创建一个全新的CellNet需要几个小时。
CellNet is a computational platform designed to assess cell populations engineered via either directed differentiation of pluripotent stem cells or via direct conversion, and to suggest specific hypotheses to improve cell fate engineering protocols. CellNet takes as input gene expression data and compares it to large data sets of normal expression profiles compiled from public sources in terms of the extent to which cell and tissue specific gene regulatory networks are established. CellNet was originally designed to work with human or mouse microarray expression data of 21 cell and tissue types. Here we describe how to apply CellNet to RNA-Seq data and how to build a completely new CellNet platform applicable to, for example, other species or additional cell and tissue types. Once the raw data has been pre-processed, running CellNet only takes several minutes whereas the time required to create a completely new CellNet requires several hours.
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