Most are written in efficient programming languages such as Fortran or C, but often require additional code efforts to plug in to more user-friendly data analysis and/or visualization tools to ease interpretation and scientific insight.
We employed a user-friendly data analysis pipeline (khmer-protocols, see Methods) to perform de novo transcriptome assembly and annotation entirely in the cloud [ 43].
In the near future, we anticipate that rapidly falling sequencing costs and development of user-friendly data analysis tools will soon make RNA-Seq the preferred alternative for transcriptome studies.
The general availability of transcriptomics, proteomics and metabolomics platforms, together with the development of user-friendly data analysis solutions (Da Wei Huang and Lempicki, 2008; Medina et al., 2010) has boosted the adoption of high-throughput approaches towards the understanding of the relationships between the genome and the phenotype.
Although amplicons obtained by LM-PCR could be processed into sequencing libraries, we opted for microarray-based identification, which is more restrictive (being limited to the probes printed on the array) but has the major benefit of compatibility with an established, robust and user-friendly data analysis pipeline.
Challenges in data integration and synchronization remain, but, ultimately, this concept should provide real-time, user-friendly advanced data analysis that, when applied at the bedside, could improve treatment.
Thus, we will provide user-friendly CLIP-seq data analysis pipelines for users, including pre-processing, mapping, peak calling and motif identification.
Further improvement of the system includes the development of user-friendly software for modeling, data analysis tools, and packaging suitable for field transportation.
Software developed with tools in the ISAW workbench provides graphical manipulation of three-dimensional arrays of data in histogram coordinates and in reciprocal space, and user-friendly wizards for routine data analysis.
This Bass Connections project aims to curate available data into an online, user-friendly tool, apply advanced data analysis techniques and develop methods for collecting big data to provide dynamic information on contraceptive discontinuation to family planning researchers and advocates.
We designed a user-friendly and comprehensive bioinformatics data analysis pipeline to complement our developed platform (EDMA).
