Bioinformatics & Biostatistics Core

We offer analysis of all high-throughput data types, including:

• Gene expression data from microarrays, qPCR, and RNA-seq
• Proteomics, phosphoproteomics, metabolomics and lipidomics from mass spectrometry and SomaLogic
• Phylogenetic and metagenomics analysis of DNA sequences
• DNA methylation sequencing data

The typical pipeline includes: normalization, quality control, Principal Component Analysis (PCA), differential expression, pathway analysis, and visualization. A visualization example is shown in Figure 1.

[FIGURE 1]

Figure 1: Gene expression heatmap with UCP1 color bar from Xue et al. (2015)

Additional features:

• Sample size and power calculations for high-throughput studies
• State-of-the-art reproducible workflows
• Analysis and meta-analysis of public data
• Novel network analysis methods
• Integration of multiple data types, including clinical covariates
• Causal inference testing (AKA mediation analysis)
• Global metabolic flux inference from Seahorse assays
• An in-house searchable gene expression database with >75 studies (output from two studies for searching a gene of interest is shown in Figure 2)

Figure 2: Joslin Gene Expression Database Profile Example. Users can search for any gene of interest, and retrieve the profiles for that gene across all studies, with fold-change (FC), p-value (P), and Benjamini-Hochberg (BH) false discovery rate per comparison shown at bottom.

We offer analysis of data from clinical, basic, translational, and epidemiologic research often including comparisons of group means (e.g. t-test, ANOVA, non-parametric tests), measures of association (e.g. correlation, regression), time-to-event analyses (e.g. survival analysis, Cox regression), and mixed models/repeated measures approaches. Projects requiring modern approaches to dealing with missing data, simulation, and machine learning applications may also be accommodated.

During the initial consultation we typically determine the nature of the variables to be analyzed and the experimental design and questions of interest, reaching a consensus with the client regarding specification of tables and figures to be produced with an initial analysis plan to follow. Specifically we can assist with or provide instruction in:

• Sample size and power calculations for clinical, basic science, translational, and observational research
• ANOVA/ANCOVA
• Regression and multiple regression
• Logistic regression, ordinal/polytomous regression
• Non-parametric analyses
• Mixed models including Repeated Measures
• Discrete and continuous time-series
• Survival analysis, Cox proportional hazards regression (Figure 3)
• Simulation
• Bootstrap
• Modern approaches to treating missing data
• Machine learning approaches
• Statistical design of experiments
• Preparation of Methods, Statistical analysis plan for manuscripts and grant applications

Initial brief consultations are provided at no charge through support of the Joslin Core and/or Harvard Catalyst. Additional biostatistics consultation services are available to junior faculty members at no charge. Please contact us for more details.

Subsequently, services are charged at the rate of either $100.00 per hour for Joslin internal and adjunct users and at the hourly rate of $135.00 per hour for non-Joslin users. On average, abstracts require 15-35 hours, manuscripts require 20-80 hours, and grants require 15-60 hours. Joslin Investigators are strongly encouraged to use the iLab Application Suite to order services.

The core members will make the best efforts to accommodate all requests. Please allow sufficient processing time for your project. It should be feasible to accommodate a brief consultation within 3 business days. Any core involvement in preparation of the grant application requires prior notification at least 3 weeks prior to the submission deadline.