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. 2007;8(9):R190.
doi: 10.1186/gb-2007-8-9-r190.

DetectiV: visualization, normalization and significance testing for pathogen-detection microarray data

Affiliations

DetectiV: visualization, normalization and significance testing for pathogen-detection microarray data

Michael Watson et al. Genome Biol. 2007.

Abstract

DNA microarrays offer the possibility of testing for the presence of thousands of micro-organisms in a single experiment. However, there is a lack of reliable bioinformatics tools for the analysis of such data. We have developed DetectiV, a package for the statistical software R. DetectiV offers powerful yet simple visualization, normalization and significance testing tools. We show that DetectiV performs better than previously published software on a large, publicly available dataset.

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Figures

Figure 1
Figure 1
Flow of information, and steps taken, when analyzing pathogen detection microarray data using DetectiV.
Figure 2
Figure 2
GSM40814 by family. Example barplot from DetectiV showing data from a virus detection microarray. The sample included amplified RNA from nasal lavage, positive for respiratory syncytial virus by DFA. Oligos have been averaged over replicates and grouped according to virus family. Each unique oligo is represented by a single bar. Each virus family has a unique background color. The y-axis is raw intensity.
Figure 3
Figure 3
GSM40814 Paramyxoviridae by species. Example barplot from DetectiV showing data from a virus detection microarray. The sample included amplified RNA from nasal lavage, positive for respiratory syncytial virus by DFA. Only oligos representing species from the Paramyxoviridae family are shown. Oligos have been averaged over replicates and grouped according to virus species. Each unique oligo is represented by a single bar. Each virus species has a unique background color. The y-axis is raw intensity.

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