Data Analysis Support
Our team of bioinformatics specialists provide support in experimental design, data analysis and programming. We take a customer-centered approach, whether advising a new user learning an unfamiliar assay or supporting an established researcher who is developing new cutting-edge methods.
Our data analysis and consultation team members are available to engage during all experimental phases, from planning to implementation, and can discuss technology selection, experimental design and choice of data analysis strategies. We also perform data analysis using reproducible workflows.
We work closely with other Fred Hutch shared resources, including the Cellular Imaging and Proteomics & Metabolomics cores. To ensure an appropriate experimental design is in place prior to seeking bioinformatics support, we strongly encourage researchers to consult with a bioinformatics specialist in a project’s earliest stages.
Schedule With Us
To schedule consultation or data analysis services with the Hutch Data Core, or to get more information about how we can work with you, contact the data analysis and consultation team lead:
Matt Fitzgibbon
Bioinformatics Director
Single-cell RNA-seq of peripheral blood mononuclear cells with clusters labeled by inferred cell type.
Clustergram displaying gene-level abundance information from metagenomic analysis of microbiome data. (Minot and Willis, 2019. doi: 10.1186/s40168-019-0722-6)
Left: Brightfield still image of live spheroids derived from pediatric brain tumors. Right: Cells escaping the spheroid identified, with migration paths followed over time. Courtesy of Dr. Dayoung Kim / Cooper Lab
Single-cell RNA-seq of peripheral blood mononuclear cells with clusters labeled by inferred cell type.
Clustergram displaying gene-level abundance information from metagenomic analysis of microbiome data. (Minot and Willis, 2019. doi: 10.1186/s40168-019-0722-6)
Left: Brightfield still image of live spheroids derived from pediatric brain tumors. Right: Cells escaping the spheroid identified, with migration paths followed over time. Courtesy of Dr. Dayoung Kim / Cooper Lab
Modern imaging systems provide an unprecedented capability to observe biological structures, but the size, depth and complexity of these image datasets challenge even top-rated commercial image analysis software.
Our dedicated scientific staff can assist in developing customized image analysis pipelines and algorithms. Our expertise allows us to create the flexible, sophisticated and high-throughput analysis workflows needed to analyze rich imaging datasets by combining data I/O, image pre-processing, image segmentation and feature extraction, metrics collection, display and export.
We also provide consultation to help select the most appropriate imaging techniques and to plan post-acquisition analyses. We work closely with colleagues in the Cellular Imaging shared resource throughout planning and image acquisition to ensure a seamless transfer of data from instruments to our analysis resources.
We perform analysis on a wide range of data types generated by light or electron microscopy, including 2D images, 3D stacks and time series. Example metrics for which we have developed versatile quantitative pipelines include cell/object counting, subcellular localization, signal colocalization, cell tracking and spatial distribution, including crowding or neighbor occupancy. Please see the Cellular Imaging shared resource’s image analysis page for more information.
For further information or to schedule consultation please contact Dr. Julien Dubrulle, image analysis staff scientist in the Cellular Imaging core.
Our bioinformatics staff have considerable experience analyzing proteomics data and are available to assist with downstream analysis for various mass spectrometry-based techniques. In close partnership with members of the Proteomics & Metabolomics shared resource, bioinformatics staff have developed custom deconvolution methods for labeled peptides, helped identify long-lived proteins in yeast through analysis of metabolically labeled peptides, searched for specific secondary structure motifs in the proteomes of non-model organisms, and taught introductory courses on the interpretation of tandem mass spectra.
For assistance analyzing proteomics data please contact Dr. Chenwei Lin, staff scientist in the Proteomics & Metabolomics core.