Beyond differential expression: the quest for causal mutations and effector molecules.
Beyond differential expression: the quest for causal mutations and effector molecules.
复制标题
DOI：
10.1186/1471-2164-13-356
复制
发表时间：
2012-07-31
期刊：
影响因子：
4.4
通讯作者：
Reverter A
中科院分区：
文献类型：
--
作者：
Hudson NJ;Dalrymple BP;Reverter A
High throughput gene expression technologies are a popular choice for researchers seeking molecular or systems-level explanations of biological phenomena. Nevertheless, there has been a groundswell of opinion that these approaches have not lived up to the hype because the interpretation of the data has lagged behind its generation. In our view a major problem has been an over-reliance on isolated lists of differentially expressed (DE) genes which – by simply comparing genes to themselves – have the pitfall of taking molecular information out of context. Numerous scientists have emphasised the need for better context. This can be achieved through holistic measurements of differential connectivity in addition to, or in replacement, of DE. However, many scientists continue to use isolated lists of DE genes as the major source of input data for common readily available analytical tools. Focussing this opinion article on our own research in skeletal muscle, we outline our resolutions to these problems – particularly a universally powerful way of quantifying differential connectivity. With a well designed experiment, it is now possible to use gene expression to identify causal mutations and the other major effector molecules with whom they cooperate, irrespective of whether they themselves are DE. We explain why, for various reasons, no other currently available experimental techniques or quantitative analyses are capable of reaching these conclusions.
登录
查看更多内容
影响因子：
4.3
作者：
Hudson NJ;Reverter A;Dalrymple BP
通讯作者：
Dalrymple BP
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：
3.7
作者：
Lawhon SD;Khare S;Rossetti CA;Everts RE;Galindo CL;Luciano SA;Figueiredo JF;Nunes JE;Gull T;Davidson GS;Drake KL;Garner HR;Lewin HA;Bäumler AJ;Adams LG
通讯作者：
Adams LG
影响因子：
3.7
作者：
Hudson NJ;Reverter A;Wang Y;Greenwood PL;Dalrymple BP
通讯作者：
Dalrymple BP
影响因子：
3.7
作者：
Baron, Daniel;Magot, Armelle;Pereon, Yann
通讯作者：
Pereon, Yann