A Survey and Comparative Study of Statistical Tests for Identifying Differential Expression from Microarray Data

2014 ◽  
Vol 11 (1) ◽  
pp. 95-115 ◽  
Author(s):  
Sanghamitra Bandyopadhyay ◽  
Saurav Mallik ◽  
Anirban Mukhopadhyay
Keyword(s):  
Comparative Study ◽  
Differential Expression ◽  
Microarray Data ◽  
Statistical Tests

scholarly journals Differential expression of CNGB1 in cancer of the vulva.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Disease Progression ◽  
Differential Expression ◽  
Microarray Data ◽  
Transcriptome Analysis ◽  
Cyclic Nucleotide ◽  
Vulvar Cancer ◽  
Vulvar Carcinoma ◽  
Gated Channel ◽  
Tissue Of Origin

In these brief notes we document work using published microarray data (1, 2) to pioneer integrative transcriptome analysis comparing vulvar carcinoma to its tissue of origin, the vulva. We report the differential expression of cyclic nucleotide gated channel beta 1, encoded by CNGB1, in cancer of the vulva. CNGB1 may be of pertinence to understanding transformation and disease progression in vulvar cancer (3).

scholarly journals Differential expression of DCLK1 in cancer of the vulva.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Disease Progression ◽  
Differential Expression ◽  
Microarray Data ◽  
Transcriptome Analysis ◽  
Vulvar Cancer ◽  
Vulvar Carcinoma ◽  
Tissue Of Origin

In these brief notes we document work using published microarray data (1, 2) to pioneer integrative transcriptome analysis comparing vulvar carcinoma to its tissue of origin, the vulva. We report the differential expression of doublecortin-like kinase 1, encoded by DCLK1, in cancer of the vulva. DCLK1 may be of pertinence to understanding transformation and disease progression in vulvar cancer (3).

scholarly journals Analysis of Genes Involved in Persistent Atrial Fibrillation: Comparisons of ‘Trigger’ and ‘Substrate’ Differences

2018 ◽  
Vol 47 (3) ◽  
pp. 1299-1309 ◽  
Author(s):  
Rongjun Zou ◽  
Minglei Yang ◽  
Wanting Shi ◽  
Chengxi Zheng ◽  
Hui Zeng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Atrial Fibrillation ◽  
Signaling Pathways ◽  
Differential Expression ◽  
Microarray Data ◽  
Left Atrial ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Genetic Traits ◽  
Receptor Interactions

Background/Aims: Recent research has improved our understanding of the pulmonary vein and surrounding left atrial (LA-PV) junction and the left atrial appendage (LAA), which are considered the ‘trigger’ and ‘substrate’ in the development of atrial fibrillation (AF), respectively. Herein, with the aim of identifying the underlying potential genetic mechanisms, we compared differences in gene expression between LA-PV junction and LAA specimens via bioinformatic analysis. Methods: Microarray data of AF (GSE41177) were downloaded from the Gene Expression Omnibus database. In addition, linear models for microarray data limma powers differential expression analyses and weighted correlation network analysis (WGCNA) were applied. Results: From the differential expression analyses, 152 differentially expressed genes and hub genes, including LEP, FOS, EDN1, NMU, CALB2, TAC1, and PPBP, were identified. Our analysis revealed that the maps of extracellular matrix (ECM)-receptor interactions, PI3K-Akt and Wnt signaling pathways, and ventricular cardiac muscle tissue morphogenesis were significantly enriched. In addition, the WGCNA results showed high correlations between genes and related genetic clusters to external clinical characteristics. Maps of the ECM-receptor interactions, chemokine signaling pathways, and the cell cycle were significantly enriched in the genes of corresponding modules and closely associated with AF duration, left atrial diameter, and left ventricular ejection function, respectively. Similarly, mapping of the TNF signaling pathway indicated significant association with genetic traits of ischemic heart disease, hypertension, and diabetes comorbidity. Conclusions: The ECM-receptor interaction as a possible central node of comparison between LA-PV and LAA samples reflected the special functional roles of ‘triggers’ and ‘substrates’ and may be closely associated with AF duration. Furthermore, LEP, FOS, EDN1, NMU, CALB2, TAC1, and PPBP genes may be implicated in the occurrence and maintenance of AF through their interactions with each other.

A comparative study of multiclass feature selection on RNAseq and microarray data

2019 ◽  
Vol 12 (2) ◽  
pp. 128
Author(s):  
Silu Zhang ◽  
Junqing Wang ◽  
Keli Xu ◽  
Megan M. York ◽  
Yin yuan Mo ◽  
...  
Keyword(s):  
Feature Selection ◽  
Comparative Study ◽  
Microarray Data

scholarly journals Variance stabilization applied to microarray data calibration and to the quantification of differential expression

2002 ◽  
Vol 18 (Suppl 1) ◽  
pp. S96-S104 ◽  
Author(s):  
W. Huber ◽  
A. von Heydebreck ◽  
H. Sultmann ◽  
A. Poustka ◽  
M. Vingron
Keyword(s):  
Differential Expression ◽  
Microarray Data ◽  
Variance Stabilization ◽  
Data Calibration

scholarly journals A Comparative Study of Techniques for Differential Expression Analysis on RNA-Seq Data

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e103207 ◽  
Author(s):  
Zong Hong Zhang ◽  
Dhanisha J. Jhaveri ◽  
Vikki M. Marshall ◽  
Denis C. Bauer ◽  
Janette Edson ◽  
...  
Keyword(s):  
Comparative Study ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Rna Seq

scholarly journals Predicting survival from microarray data a comparative study

2007 ◽  
Vol 23 (16) ◽  
pp. 2080-2087 ◽  
Author(s):  
H.M. Bovelstad ◽  
S. Nygard ◽  
H.L. Storvold ◽  
M. Aldrin ◽  
O. Borgan ◽  
...  
Keyword(s):  
Comparative Study ◽  
Microarray Data
Sign in / Sign up

Export Citation Format

Share Document