Oliver R Homann1, Alexander D Johnson. 1. Department of Microbiology and Immunology, University of California San Francisco, San Francisco, California, USA. oliver.homann@ucsf.edu
Abstract
BACKGROUND: As high-throughput technologies rapidly generate genome-scale data, it becomes increasingly important to visually integrate these data so that specific hypotheses can be formulated and tested. RESULTS: We present MochiView, a platform-independent Java software that integrates browsing of genomic sequences, features, and data with DNA motif visualization and analysis in a visually-appealing and user-friendly application. CONCLUSIONS: While highly versatile, the software is particularly useful for organizing, exploring, and analyzing large genomic data sets, such as those from deep RNA sequencing, chromatin immunoprecipitation experiments (ChIP-Seq and ChIP-Chip), and transcriptional profiling. MochiView provides an extensive suite of utilities to identify and to explore connections between these data sets and short sequence motifs present in DNA or RNA.
BACKGROUND: As high-throughput technologies rapidly generate genome-scale data, it becomes increasingly important to visually integrate these data so that specific hypotheses can be formulated and tested. RESULTS: We present MochiView, a platform-independent Java software that integrates browsing of genomic sequences, features, and data with DNA motif visualization and analysis in a visually-appealing and user-friendly application. CONCLUSIONS: While highly versatile, the software is particularly useful for organizing, exploring, and analyzing large genomic data sets, such as those from deep RNA sequencing, chromatin immunoprecipitation experiments (ChIP-Seq and ChIP-Chip), and transcriptional profiling. MochiView provides an extensive suite of utilities to identify and to explore connections between these data sets and short sequence motifs present in DNA or RNA.
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