Protocol for computationally evaluating the loss of stoichiometry and coordinated expression of proteins.
Protocol for computationally evaluating the loss of stoichiometry and coordinated expression of proteins.
复制标题
用于计算评估蛋白质化学计量损失和协调表达的协议。
DOI：
10.1016/j.xpro.2022.101182
复制
发表时间：
2022-06-17
期刊：
影响因子：
--
通讯作者：
LaBarge MA
中科院分区：
文献类型：
--
作者：
Hinz S;Todhunter ME;LaBarge MA
转录或翻译机制的失调可以改变多蛋白复合物的化学计量，并发生在自然过程中，如衰老。化学计量的损失已经显示改变蛋白质复合物功能。我们提供了一个协议和相关的代码，使用组学数据来量化这些化学计量的变化，通过统计分散利用四分位数范围的表达值每个分组变量。这种描述性统计方法能够在不采集额外数据的情况下量化化学计量变化。有关本方案使用和执行的完整详细信息，请参阅。基于表达的四分位数范围的稳健和通用输出轻量级R函数通过GitHub轻松加载到数据管道中使用ggplot2包装函数方便地绘制测量的化学计量变化转录或翻译机制的失调可以改变多蛋白复合物的化学计量，并发生在自然过程中，如衰老。化学计量的损失已经显示改变蛋白质复合物功能。我们提供了一个协议和相关的代码，使用组学数据来量化这些化学计量的变化，通过统计分散利用四分位数范围的表达值每个分组变量。这种描述性统计方法能够在不采集额外数据的情况下量化化学计量变化。
Dysregulation of the transcriptional or translational machinery can alter the stoichiometry of multiprotein complexes and occurs in natural processes such as aging. Loss of stoichiometry has been shown to alter protein complex functions. We provide a protocol and associated code that use omics data to quantify these stoichiometric changes via statistical dispersion utilizing the interquartile range of expression values per grouping variable. This descriptive statistical approach enables the quantification of stoichiometry changes without additional data acquisition. For complete details on the use and execution of this protocol, please refer to. A protocol to quantify stoichiometry changes of protein complexes Robust and versatile output based on interquartile range of expression Lightweight R functions easily loaded into data pipeline via GitHub Conveniently plot measured stoichiometry changes with ggplot2 wrapper function Dysregulation of the transcriptional or translational machinery can alter the stoichiometry of multiprotein complexes and occurs in natural processes such as aging. Loss of stoichiometry has been shown to alter protein complex functions. We provide a protocol and associated code that use omics data to quantify these stoichiometric changes via statistical dispersion utilizing the interquartile range of expression values per grouping variable. This descriptive statistical approach enables the quantification of stoichiometry changes without additional data acquisition.
影响因子：
9.9
作者：
Sacramento, Erika Kelmer;Kirkpatrick, Joanna M.;Ori, Alessandro
通讯作者：
Ori, Alessandro
影响因子：
5.8
作者：
Hinz S;Manousopoulou A;Miyano M;Sayaman RW;Aguilera KY;Todhunter ME;Lopez JC;Sohn LL;Wang LD;LaBarge MA
通讯作者：
LaBarge MA