IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae

Ingham, Victoria ORCID: https://orcid.org/0000-0001-5708-4741, Bennett, Andrew, Peng, Duo, Wagstaff, Simon ORCID: https://orcid.org/0000-0003-0577-5537 and Ranson, Hilary ORCID: https://orcid.org/0000-0003-2332-8247 (2020) 'IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae'. Journal of Visualized Experiments (JoVE), Issue 155, e60721.

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Abstract

IR-TEx is an application written in Shiny (an R package) that allows exploration of the expression of (as well as assigning functions to) transcripts whose expression is associated with insecticide resistance phenotypes in Anopheles gambiae mosquitoes. The application can be used online or downloaded and used locally by anyone. The local application can be modified to add new insecticide resistance datasets generated from multiple -omics platforms. This guide demonstrates how to add new datasets and handle missing data. Furthermore, IR-TEx can be completely and easily recoded to use-omics datasets from any experimental data, making it a valuable resource to many researchers. The protocol illustrates the utility of IR-TEx in identifying new insecticide resistance candidates using the the microsomal glutathione transferase, GSTMS1, as an example. This transcript is upregulated in multiple pyrethroid resistant populations from Côte D'Ivoire and Burkina Faso. The identification of co-correlated transcripts provides further insight into the putative roles of this gene.

Item Type:	Article
Subjects:	QU Biochemistry > QU 26.5 Informatics. Automatic data processing. Computers QU Biochemistry > Genetics > QU 550 Genetic techniques. PCR. Chromosome mapping QX Parasitology > Insects. Other Parasites > QX 515 Anopheles WC Communicable Diseases > Tropical and Parasitic Diseases > WC 750 Malaria
Faculty: Department:	Biological Sciences > Department of Tropical Disease Biology Biological Sciences > Vector Biology Department
Digital Object Identifer (DOI):	https://doi.org/10.3791/60721
Depositing User:	Stacy Murtagh
Date Deposited:	17 Jan 2020 12:31
Last Modified:	17 Jan 2020 12:31
URI:	https://archive.lstmed.ac.uk/id/eprint/13542

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