Fred Hutch, Seattle Cancer Care Alliance, and UW Medicine Complete Restructure of Partnership

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Bioinformatics Services

Bioinformatics Support

Bioinformatics staff are available by appointment for one-on-one consultation. We are happy to discuss experimental design, choice of data analysis strategies and software tools, or to help with advice and troubleshooting as you conduct your own analyses.

We strongly encourage researchers to consult with a bioinformatics specialist at the earliest stages of a project to ensure an appropriate experimental design is in place prior to seeking data analysis support. 

We offer bioinformatics support through several service models.

Standard Workflows: The bioinformatics team provides basic analytical support for data generated by the genomics team. For many common workflows, generation of standard deliverables is included in the sequencing service fee. Please refer to the list of standard services below.

Fee-for-Service Workflows: Certain standard workflows that require manual configuration or significant computation time are available for a nominal fee-for-service. This currently applies to 10x single-cell workflows.

Modified Workflows: We often collaborate with researchers to bring new techniques to the center. Adding new tools, working with non-model organisms, or integrating substantial datasets from external sources may require effort beyond what can be included in our standard service fees. In such cases, support may require an hourly rate fee-for-service structure and be subject to staff availability and project demands. Please contact us to discuss the scope of your project and get an estimate of potential service fees.

Schedule With Us

To schedule bioinformatics services, or to get more information about how we can work with you, contact the bioinformatics team lead:

Matt Fitzgibbon
Director, Bioinformatics

Standard Services

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RNA-Seq – Differential Expression Analysis

Processing of expression data from common, well-annotated organisms (such as human, mouse and yeast), RNA-seq differential expression analysis for model organisms (human and mouse), including QC of raw data, alignment to genome, and generation of tables of differentially expressed genes for typical two-factor experiments.

  • STAR2 aligned reads in BAM format
  • QC reports: aligned reads, ribosomal content, 3’ bias, exonic mapping rate, PCA, MA plots
  • Table of raw per-gene fragment counts across all samples
  • Table of TMM normalized expression values in CPM (counts per million) units
  • Table of differential expression significance testing results for a typical two-factor experiment (tools: edgeR)

Non-model organisms, more complex designs and comparisons, and non-standard library preparation may require more analyst time and incur additional charges. Researchers are encouraged to contact the Genomics & Bioinformatics shared resource during experiment design.

Whole Exome Sequencing Analysis

Analysis and variant calling of human or mouse whole exome sequencing data gathered with standard capture reagents.

  • Sequencing data QC results
  • Original and analysis-ready alignment files (tools: bwa, GATK)
  • Depth coverage of sample and intervals, and overall metrics
  • Variant calling and variant annotation in vcf format (GATK, HaplotypeCaller)
  • Somatic variant calling and variant annotation if paired samples provided (GATK, Mutect2)

Additional deliverables (potentially fee-for-service):

  • CNV analysis
  • Additional data processing and customized figure generation
Targeted Sequencing Analysis

Analysis of sequence variants in targeted genes or intergenic regions of human or mouse.

  • Sequencing data QC results
  • Original and analysis-ready alignment files (tools: bwa, GATK)
  • Depth coverage of sample and intervals, and overall metrics
  • Variant calling and variant annotation in vcf format (GATK)

Additional deliverables (potentially fee-for-service):

  • Additional data processing and custom figure generation
10x Single-cell and Single-nuclei Profiling

As part of the 10x single-cell expression profiling services offered through the Genomics resource, we offer standard cellranger processing of human or mouse scRNA-seq, feature barcoding, and VDJ immune sequencing data. We also support 10x scATAC-seq and combined “multiome” profiling of gene expression and chromatin accessibility on the same nuclei. Given the large number of possible assays and combinations, users are encouraged to contact bioinformatics@fredhutch.org during experimental design to describe species, sequencing strategy, specific antibody-conjugated oligo sequences, and intended analysis goals. Standard deliverables depend on experimental setup and may include:

  • Overall QC summaries in HTML format: numbers of read pairs gathered, percent aligned, number of cells inferred, numbers of genes detected per cell, etc.
  • Experiment summaries for interactive exploration with the 10x Loupe Browser software
  • Gene-barcode expression matrices for analysis with specialized software such as Seurat or Monocle
  • For VDJ sequencing we provide vloupe files for use with the 10x Loupe VDJ Browser (or overlay on a corresponding gene-expression sample). The VDJ workflow also generates tabular and fastq-format summaries of clonotypes and consensus sequences

Additional analyses, such as integration of multiple data sets or construction of customized references (including different species or addition of CAR-T or reporter genes), may be available on fee-for-service basis. Researchers are encouraged to talk with the Genomics & Bioinformatics shared resource during experiment design when custom annotations or additional data analysis are desired.

Resources to assist in interpretation of standard 10x cellranger deliverables include:

Spatial Gene Expression Deliverables

The Genomics shared resource, in partnership with Experimental Histopathology, offers comprehensive end-to-end spatial transcriptomics services. Bioinformatics can assist with standard analyses of these experiments at no additional charge when data are generated in the Genomic resource.

The 10x Visium platform allows expression profiling of intact tissue sections, overlaying high-resolution expression measurements on H&E stained images to reveal expression patterns in spatial context. We apply the “spaceranger” software, optimized by 10x for the Visium platform, with default parameters to H&E stained slide images and sequencing data from the Illumina NextSeq or NovaSeq instruments. Standard deliverables for human or mouse tissues include:

  • Overall QC summaries in HTML format: numbers of read pairs gathered, percent aligned, number of spots under tissue, clustering of spots according to expression patterns, etc. Summaries include slide images with numbers of transcripts and cluster identities overlaid.
  • Experiment summaries for interactive exploration with the 10x Loupe Browser software including tissue images.
  • Spot-barcode expression matrices for analysis with specialized software such as Seurat or Monocle
    Registration of immunofluorescence images, application to other species, or customized downstream analysis are also available on a fee-for-service basis. Users are encouraged to consult the Bioinformatics team at bioinformatics@fredhutch.org during experiment design.

10x provides additional information on standard spaceranger software deliverables, click here to learn more.

Data analysis for the GeoMx multi-cell profiler is conducted using on-instrument software optimized for this platform by NanoString. We can assist users with data preprocessing and QC from both nCounter and NGS readouts; normalization & background correction; comparing different conditions & structures; and export of visualizations. Additional analysis, using Seurat and R packages developed by the NanoString Biostatistics group, is available on a fee-for-service basis.

Users are encouraged to consult the Bioinformatics team at bioinformatics@fredhutch.org during experiment design.

CUT&RUN Analysis

A refined, highly sensitive method to assess chromatin features and histone or transcription factor binding. Developed by the Henikoff Lab at Fred Hutch and implemented in the by the genomics team in the core’s AutoCUT&RUN service. Standard results include:

  • Sequencing data QC results
  • Read alignments, in standard BAM format, using bowtie2
  • Fragment-level genome coverage in bedgraph format, with optional scaling by exogenous DNA spike-in or E. coli carry-over (where available). Suitable for input to the SEACR peak caller
  • Fragment-level genome coverage is also provided in bigwig format, for visualization in the UCSC Genome Browser or Integrative Genomics Viewer (IGV)
  • MACS2 called peaks in BED format

Additional deliverables (potentially fee-for-service):

  • Differential peak binding
  • Customized figures to indicate binding
  • Transcription factor motif analysis 

 

CRISPR Screens
  • Table of sgRNA counts (tools: bowtie, R custom scripts)
  • QC reports: summary of total counts and number of detected guides in each sample, PCA, replicate correlation matrix, box plots of sample guide expression (tool: R)
  • Differential guide expression: gene and guide level significance summary (tools: mageck, edgeR, if explicitly requested by user)

Non-standard analyses including sgRNA library design, generation of synthetic NTCs, etc., may be performed for an additional fee.

ChIP-Seq Analysis

Analyze DNA “tags” bound to proteins of interest over long regions (e.g. histones) or shorter regions (e.g. transcription factors). Our ChIP-seq workflow is based on the ENCODE project's ChIP-seq data standards and processing pipeline.

  • Sequencing data QC results
  • Aligned reads in standard bam format (tools: bwa or bowtie)
  • Control-normalized tag density in bigwig format for visualization (tools: Homer, UCSC tools)
  • MACS2 called peaks in BED format

Additional deliverables (potentially fee-for-service):

  • Differential peak binding
  • Customized figures to indicate binding
  • Transcription factor motif analysis
ATAC-Seq Analysis – DNA Accessibility

Assessment of chromatin accessibility. Our ATAC-seq workflow is based on the ENCODE project's data standards and processing pipeline.

  • Sequencing data QC results
  • Alignment files
  • Peak calling files
  • BigWig files for visualization
  • Detailed reports
PhIP-Seq
  • Alignment to reference library in BAM format (tool: bowtie)
  • Table of viral counts with annotations (tool: samtools, R)
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Questions about our bioinformatics services or how to schedule with us?