By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Fresh data on Bioinformatics are presented in a new report. According to news reporting out of London, United Kingdom, by VerticalNews editors, research stated, "ImmunoPrecipitation (IP) efficiencies may vary largely between different antibodies and between repeated experiments with the same antibody. These differences have a large impact on the quality of ChIP-seq data: a more efficient experiment will necessarily lead to a higher signal to background ratio, and therefore to an apparent larger number of enriched regions, compared to a less efficient experiment."
Our news journalists obtained a quote from the research from Brunel University, "In this paper, we show how IP efficiencies can be explicitly accounted for in the joint statistical modelling of ChIP-seq data. We fit a latent mixture model to eight experiments on two proteins, from two laboratories where different antibodies are used for the two proteins. We use the model parameters to estimate the efficiencies of individual experiments, and find that these are clearly different for the different laboratories, and amongst technical replicates from the same lab. When we account for ChIP efficiency, we find more regions bound in the more efficient experiments than in the less efficient ones, at the same false discovery rate. A priori knowledge of the same number of binding sites across experiments can also be included in the model for a more robust detection of differentially bound regions among two different proteins. We propose a statistical model for the detection of enriched and differentially bound regions from multiple ChIP-seq data sets."
According to the news editors, the research concluded: "The framework that we present accounts explicitly for IP efficiencies in ChIP-seq data, and allows to model jointly, rather than individually, replicates and experiments from different proteins, leading to more robust biological conclusions."
For more information on this research see: Accounting for immunoprecipitation efficiencies in the statistical analysis of ChIP-seq data. Bmc Bioinformatics, 2013;14():169. (BioMed Central - www.biomedcentral.com/; Bmc Bioinformatics - www.biomedcentral.com/bmcbioinformatics/)
Our news journalists report that additional information may be obtained by contacting Y. Bao, School of Information Systems, Computing and Mathematics, Brunel University, London, UK. Additional authors for this research include V. Vinciotti, E. Wit and P.A 't Hoen.
Keywords for this news article include: Antibodies, London, Europe, Peptides, Immunology, Amino Acids, United Kingdom, Bioinformatics, Blood Proteins, Immunoglobulins.
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