Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.

EBImage--an R package for image processing with applications to cellular phenotypes.

SUMMARY: EBImage provides general purpose functionality for reading, writing, processing and analysis of images. Furthermore, in the context of microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and use of existing tools in the R environment for signal processing, statistical modeling, machine learning and data visualization. AVAILABILITY: EBImage is free and open source, released under the LGPL license and available from the Bioconductor project (http://www.bioconductor.org/packages/release/bioc/html/EBImage.html).

Ringo--an R/Bioconductor package for analyzing ChIP-chip readouts.

BACKGROUND: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a high-throughput assay for DNA-protein-binding or post-translational chromatin/histone modifications. However, the raw microarray intensity readings themselves are not immediately useful to researchers, but require a number of bioinformatic analysis steps. Identified enriched regions need to be bioinformatically annotated and compared to related datasets by statistical methods. RESULTS: We present a free, open-source R package Ringo that facilitates the analysis of ChIP-chip experiments by providing functionality for data import, quality assessment, normalization and visualization of the data, and the detection of ChIP-enriched genomic regions. CONCLUSION: Ringo integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It facilitates the construction of programmed analysis workflows, offers benefits in scalability, reproducibility and methodical scope of the analyses and opens up a broad selection of follow-up statistical and bioinformatic methods.

CoCo: a web application to display, store and curate ChIP-on-chip data integrated with diverse types of gene expression data.

MOTIVATION: CoCo, ChIP-on-Chip online, is an open-source web application that supports the annotation and curation of regulatory regions and associated target genes discovered in ChIP-on-chip experiments. CoCo integrates ChIP-on-chip results with diverse types of gene expression data (expression profiling, in situ hybridization) and displays them within a genomic context. Regulatory relationships between the transcription factor-bound regions and putative target genes can be stored and expanded throughout different sessions. AVAILABILITY: http://furlonglab.embl.de/methods/tools/coco.

Modeling steady-state experiments with a scanning electrochemical microscope involving several independent diffusing species using the boundary element method.

The BEM algorithm developed earlier for steady-state experiments in the scanning electrochemical microscopy (SECM) feedback mode has been expanded to allow for the treatment of more than one independently diffusing species. This allows the treatment of substrate-generation/tip-collection SECM experiments. The simulations revealed the interrelation of sample layout, local kinetics, imaging conditions, and the quality of the obtained SECM images. Resolution in the SECM SG/TC images has been evaluated, and it depends on several factors. For most practical situations, the resolution is limited by the diffusion profiles of the sample. When a dissolved compound is converted at the sample (e.g., oxygen reduction or enzymatic reaction at the sample), the working distance should be significantly larger than in SECM feedback experiments (ca. 3 r(T) for RG = 5) in order to avoid diffusional shielding of the active regions on the sample by the UME body. The resolution ability also depends on the kinetics of the active regions. The best resolution can be expected if all the active regions cause the same flux. In one simulated example, which might mimic a possible scenario of a low-density protein array, considerable compromises in the resolving power, were noted when the flux from two neighboring spots differs by more than a factor of 2.

Numerical simulation of scanning electrochemical microscopy experiments with frame-shaped integrated atomic force microscopy--SECM probes using the boundary element method.

Integrated submicroelectrodes for combined AFM-SECM measurements are characterized with numerical simulations using the boundary element method. SECM approach curves and SECM images are calculated and analyzed for a model substrate containing pronounced topographical and electrochemical features. The theoretically calculated image has been compared to the experimental data and shows excellent quantitative agreement. Hence, the applicability of integrated AFM-SECM electrodes for combined electrochemical and topographical imaging and a profound theoretical description including quantification of the obtained results are demonstrated.