Tue, 08/19/2014
Tue, 08/19/2014 at 1:50 PM
Customer: Do you have experience with other types of high-throughput data analyses (real-time, microarray)? What about cross-platform analyses (sequencing, RNA, methylation, protein, etc.)?
Tue, 09/19/2014 at 3:07 PM
AccuraScience LB: Each of our Lead Bioinformaticians started working as a bioinformatician long before NGS became available. So yes, we have had extensive experience with analyzing and interpreting other types of high-throughput data. And indeed, inquiries on integrated analysis of multiple types of data have been on the rise in recent months. Processing various types of data (including microarray, sequencing (both gene expression and ChIP-type of data (DNA methylation included) as well as proteomic data) is more or less routine. Integrating them could be tricky. Some of the common strategies include (1) Network-based strategies which, after integrating multiple types of data in a network, focus is put on identifying specific topological features, e.g., network hubs, (2) Bayesian-inference based strategies, the objective of which is to identify causal relationships between events, and (3) Machine learning-based integration methods focusing on identifying specific patterns hidden in the data. Besides data newly produced in researchers' own labs, it is often possible to identify other data in the public domain, e.g., public protein-protein interaction data could be a great supplement to network-based integration approaches.
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Note: LB stands for Lead Bioinformatician. An AccuraScience LB is a senior bioinformatics expert and leader of an AccuraScience data analysis team.
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