scholarly journals CTen: a web-based platform for identifying enriched cell types from heterogeneous microarray data

BMC Genomics ◽  
2012 ◽  
Vol 13 (1) ◽  
pp. 460 ◽  
Author(s):  
Jason E Shoemaker ◽  
Tiago JS Lopes ◽  
Samik Ghosh ◽  
Yukiko Matsuoka ◽  
Yoshihiro Kawaoka ◽  
...  
Keyword(s):  
2011 ◽  
Vol 12 (S7) ◽  
Author(s):  
Vinhthuy T Phan ◽  
Nam S Vo ◽  
Thomas R Sutter

2019 ◽  
Vol 47 (W1) ◽  
pp. W142-W150 ◽  
Author(s):  
Selim Kalayci ◽  
Myvizhi Esai Selvan ◽  
Irene Ramos ◽  
Chris Cotsapas ◽  
Eva Harris ◽  
...  

Abstract Humans vary considerably both in their baseline and activated immune phenotypes. We developed a user-friendly open-access web portal, ImmuneRegulation, that enables users to interactively explore immune regulatory elements that drive cell-type or cohort-specific gene expression levels. ImmuneRegulation currently provides the largest centrally integrated resource on human transcriptome regulation across whole blood and blood cell types, including (i) ∼43,000 genotyped individuals with associated gene expression data from ∼51,000 experiments, yielding genetic variant-gene expression associations on ∼220 million eQTLs; (ii) 14 million transcription factor (TF)-binding region hits extracted from 1945 ChIP-seq studies; and (iii) the latest GWAS catalog with 67,230 published variant-trait associations. Users can interactively explore associations between queried gene(s) and their regulators (cis-eQTLs, trans-eQTLs or TFs) across multiple cohorts and studies. These regulators may explain genotype-dependent gene expression variations and be critical in selecting the ideal cohorts or cell types for follow-up studies or in developing predictive models. Overall, ImmuneRegulation significantly lowers the barriers between complex immune regulation data and researchers who want rapid, intuitive and high-quality access to the effects of regulatory elements on gene expression in multiple studies to empower investigators in translating these rich data into biological insights and clinical applications, and is freely available at https://immuneregulation.mssm.edu.


2010 ◽  
Vol 4 (1) ◽  
pp. 9-15
Author(s):  
Qingyun Shi ◽  
Yijun Meng ◽  
Dijun Chen ◽  
Fei He ◽  
Haibin Gu ◽  
...  
Keyword(s):  

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e80837 ◽  
Author(s):  
Brett Trost ◽  
Jason Kindrachuk ◽  
Pekka Määttänen ◽  
Scott Napper ◽  
Anthony Kusalik
Keyword(s):  

2007 ◽  
Vol 23 (10) ◽  
pp. 1304-1306 ◽  
Author(s):  
K. Le Brigand ◽  
P. Barbry

2020 ◽  
Author(s):  
Agaz H Wani ◽  
D Armstrong ◽  
Jan Dahrendorff ◽  
Monica Uddin

AbstractSummaryDNA methylation microarray data may suffer from batch effects due to improper handling of the samples during the plating process. RANDOMIZE is a web-based application designed to perform randomization of relevant metadata to evenly distribute samples across the factors typically responsible for batch effects in DNA methylation microarrays, such as row, chips and plates. Randomization helps to reduce the likelihood of bias and impact of difference among groups.AvailabilityThe tool is freely available online at https://coph-usf.shinyapps.io/RANDOMIZE/ and can be accessed using any web browser. Sample data and tutorial is also available with the [email protected]


2008 ◽  
Vol 36 (Web Server) ◽  
pp. W308-W314 ◽  
Author(s):  
J. Tarraga ◽  
I. Medina ◽  
J. Carbonell ◽  
J. Huerta-Cepas ◽  
P. Minguez ◽  
...  

2002 ◽  
Vol 3 (2) ◽  
pp. 91-96
Author(s):  
Madhusmita Mitra ◽  
Nigam Shah ◽  
Lukas Mueller ◽  
Scuth Pin ◽  
Nina Fedoroff

We have built a microarray database, StressDB, for management of microarray data from our studies on stress-modulated genes in Arabidopsis. StressDB provides small user groups with a locally installable web-based relational microarray database. It has a simple and intuitive architecture and has been designed for cDNA microarray technology users. StressDB uses Windows™2000 as the centralized database server with Oracle™8i as the relational database management system. It allows users to manage microarray data and data-related biological information over the Internet using a web browser. The source-code is currently available on request from the authors and will soon be made freely available for downloading from our website athttp://arastressdb.cac.psu.edu.


2005 ◽  
Vol 94 (4) ◽  
pp. 493-495 ◽  
Author(s):  
Kenji Saito ◽  
Soichi Arai ◽  
Hisanori Kato

In the current situation where microarray data in the field of nutritional genomics (nutrigenomics) are accumulating rapidly, there is imminent need for an efficient data infrastructure to support research workflow. We have established a web-based, integrated database of the publications and microarray expression data in the field of nutrigenomics. The registered data include links to external databases such as PubMed of the National Center for Biotechnology Information and public microarray databases that contain Minimum Information About a Microarray Experiment-compliant microarray expression data. Using this database, all data sets created will be effectively utilized and shared with other researchers. This database is built on an open-source database system and is freely accessible via the World Wide Web (http://a-yo5.ch.a.u-tokyo.ac.jp/index.phtml</url).


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