Investigators who are writing grants can find below a description of the Hutch Data Core and its services for their grant applications. Descriptions of the overall Fred Hutchinson Cancer Center Shared Resources program are available on the main Shared Resources grant information page.
Examples of publications made possible by Hutch Data Core staff are listed below.
The Hutch Data Core provides services to support the efficient and reproducible analysis of large-scale datasets for biomedical research, including next-generation genome sequencing, high-throughput microscopy, mass spectrometry and single-cell analysis. Staff within the Data Core include computational biologists, bioinformaticians, software engineers and cloud architects with extensive experience transforming raw data into scientific insight. Services include: project-based scientific analysis by expert bioinformaticians, automation of analytical pipelines using modern workflow management platforms, and publication of complex datasets with web-accelerated graphics. Additional expertise is available to help support the use of cloud computing technologies for novel research approaches, as well as training and documentation to help support the use of reproducible, open science approaches across the domain of bioinformatics.
Data analysis and consulting services are offered by an experienced team of bioinformatics specialists who provide support in experimental design, data analysis and programming for center investigators and members of the Fred Hutch/University of Washington Cancer Consortium. Staff have experience with a broad range of assays, with particular emphasis on massively parallel next-generation and third-generation sequencing. Assays routinely supported by core staff include bulk and single-cell expression profiling, single-cell immune receptor sequencing, CUT&RUN, ChIP-seq, ATAC-seq, whole-exome variant calling and targeted amplicon sequencing. Staff also conduct analysis of high-throughput CRISPR screens and data generated in the center’s unique and recently introduced AutoCUT&RUN facility. The level of support provided is customized to each project following initial consultation with the investigator and may include programming advice, assistance with troubleshooting R or Python code, guidance using commercial or academic analytical tools, and implementation of a full range of data analysis strategies that encompass data quality assessment, various statistical analyses, and generation of summary reports and figures.