Data visualization

2006
Ian Flockhart, Matthew Booker, Amy Kiger, Michael Boutros, Susan Armknecht, Nadire Ramadan, Kris Richardson, Andrew Xu, Norbert Perrimon, and Bernard Mathey-Prevot. 2006. “FlyRNAi: the Drosophila RNAi screening center database.” Nucleic Acids Res, 34, Database issue, Pp. D489-94.Abstract

RNA interference (RNAi) has become a powerful tool for genetic screening in Drosophila. At the Drosophila RNAi Screening Center (DRSC), we are using a library of over 21,000 double-stranded RNAs targeting known and predicted genes in Drosophila. This library is available for the use of visiting scientists wishing to perform full-genome RNAi screens. The data generated from these screens are collected in the DRSC database (http://flyRNAi.org/cgi-bin/RNAi_screens.pl) in a flexible format for the convenience of the scientist and for archiving data. The long-term goal of this database is to provide annotations for as many of the uncharacterized genes in Drosophila as possible. Data from published screens are available to the public through a highly configurable interface that allows detailed examination of the data and provides access to a number of other databases and bioinformatics tools.

2006_Nucl Acids Res_Flockhart.pdf
Christophe J Echeverri and Norbert Perrimon. 2006. “High-throughput RNAi screening in cultured cells: a user's guide.” Nat Rev Genet, 7, 5, Pp. 373-84.Abstract

RNA interference has re-energized the field of functional genomics by enabling genome-scale loss-of-function screens in cultured cells. Looking back on the lessons that have been learned from the first wave of technology developments and applications in this exciting field, we provide both a user's guide for newcomers to the field and a detailed examination of some more complex issues, particularly concerning optimization and quality control, for more advanced users. From a discussion of cell lines, screening paradigms, reagent types and read-out methodologies, we explore in particular the complexities of designing optimal controls and normalization strategies for these challenging but extremely powerful studies.

2006_Nat Rev Gene_Echeverri.pdf

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