scholarly journals Differential gene expression profiles of neurothekeomas and nerve sheath myxomas by microarray analysis

2011 ◽  
Vol 24 (3) ◽  
pp. 343-354 ◽  
Author(s):  
Sachiv Sheth ◽  
Xinmin Li ◽  
Scott Binder ◽  
Sarah M Dry
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Microarray Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Nerve Sheath ◽  
Differential Gene

scholarly journals Differential Gene Expression Profiles of Cells from Normal, Traumatic and Idiopathic Scoliotic Discs Identify Molecular Dysregulation in Scoliosis

2016 ◽  
Vol 6 (1_suppl) ◽  
pp. s-0036-1582635-s-0036-1582635 ◽  
Author(s):  
Sibylle Grad ◽  
Ying Zhang ◽  
Olga Rozhnova ◽  
Elena Schelkunova ◽  
Mikhail Mikhailovsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differential Gene

scholarly journals RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Web Application ◽  
Cellular Response ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Experimental Conditions ◽  
Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

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