Publication | Open Access
seqMINER: an integrated ChIP-seq data interpretation platform
414
Citations
28
References
2010
Year
EngineeringGeneticsHigh ThroughputComputer ArchitectureBioinformatics DatabaseGene Expression ProfilingEpigeneticsHardware ArchitectureComputational GenomicsData IntegrationComputer EngineeringOmicsSingle ExperimentBioinformaticsFunctional GenomicsCell BiologySystem On ChipChromatinComputational BiologyCovalent Histone ModificationSystems BiologyMedicine
ChIP‑seq generates genome‑wide data on histone marks or transcription factor binding, yet efficient bioinformatics tools for interpreting these large datasets are often lacking. The authors developed seqMINER, an integrated portable platform for efficient interpretation of multiple genome‑wide ChIP‑seq datasets. seqMINER integrates and compares multiple ChIP‑seq datasets, extracts qualitative and quantitative information, classifies data based on features, and visualizes and models patterns through graphical representations. Using seqMINER, the authors performed a comprehensive analysis of mouse embryonic stem cell chromatin modifications, revealing the global epigenetic landscape and its changes during differentiation.
In a single experiment, chromatin immunoprecipitation combined with high throughput sequencing (ChIP-seq) provides genome-wide information about a given covalent histone modification or transcription factor occupancy. However, time efficient bioinformatics resources for extracting biological meaning out of these gigabyte-scale datasets are often a limiting factor for data interpretation by biologists. We created an integrated portable ChIP-seq data interpretation platform called seqMINER, with optimized performances for efficient handling of multiple genome-wide datasets. seqMINER allows comparison and integration of multiple ChIP-seq datasets and extraction of qualitative as well as quantitative information. seqMINER can handle the biological complexity of most experimental situations and proposes methods to the user for data classification according to the analysed features. In addition, through multiple graphical representations, seqMINER allows visualization and modelling of general as well as specific patterns in a given dataset. To demonstrate the efficiency of seqMINER, we have carried out a comprehensive analysis of genome-wide chromatin modification data in mouse embryonic stem cells to understand the global epigenetic landscape and its change through cellular differentiation.
| Year | Citations | |
|---|---|---|
Page 1
Page 1