Biostatistics and Bioinformatics Core

The Biostatistics and Bioinformatics Core is available to help investigators with grant preparation, study design, statistical and bioinformatics analyses, statistical and bioinformatics education, and creation of bioinformatics pipelines and workflows,

Help to Early Career Investigators (those who have not yet been the PI of a funded NIH grant at the R01 level or higher) with HIV-related projects is generally FREE.

Help to Senior Investigators (those who are or have been the PI of a funded NIH grant at the R01 level or higher) with HIV-related grant preparation and/or design and analysis of a study to obtain preliminary data for an HIV-related grant proposal is generally FREE.  Each Senior Investigator is also entitled to 2 FREE hours per year of consulting from the Biostatistics and Bioinformatics Core.  

Lead Time Guidelines: 

Grant Preparation:
At least 6 weeks before the grant is due at NIH or other external funding source.
At least 5 weeks before the grant is due at the Harvard CFAR Developmental Core.

Analysis for Abstract:
At least 4 weeks before the abstract deadline.


  • Grant submissions:   
    • Help with formulating aims and hypotheses
    • Analysis of pilot data
    • Design of new studies
    • Statistical analysis methods
    • Justification of sample size
    • Help with listing possible limitations and developing alternative approaches to mitigate the limitations
    • General review of logic of proposal 
    • Assistance in understanding and answering grant critiques 
  • Design: 
    • Formulation of hypotheses
    • Sampling schemes
    • Consideration of stratification and random ordering
    • Variability of various possible endpoints
    • Reliability and validity of questionnaires
    • Choice of statistical tests
    • Advice on choice of high through-put technologies
    • Power and sample size for fixed or sequential experiments
    • Advice on data items to be collected in  laboratory, animal, clinical, outcomes, and epidemiologic studies 
  •  Statistical Analysis:
    • Logical checks of data
    • Tests of hypotheses
    • Development of statistical models
    • Testing of statistical assumptions for tests and models
    • Plots illustrating the results of analyses
    • Help with drafting abstracts, talks, posters, and manuscripts
  •  Bioinformatics Analysis 
    • RNA-seq, single cell RNA-seq, small RNA-seq, and ChIP-seq analysis
    • Whole genome sequencing, resequencing, exome-seq, and copy number variation studies for human and viral samples.
  • Training:  
    • Reviews of statistical methods and analyses in relevant literature
    • Education in statistical methods
    • Statistical computer packages.(e.g., STATA and R)