Bioinformatics Training Core

The mission of the Bioinformatics Training Core is to provide resources for bioinformatics education focused on best practices in high-throughput sequencing data analysis and research data management, with the goal to foster independence and knowledge transfer in the HCC community

Publication Acknowledgement

If research supported by this core facility results in publication, please acknowledge this support by including the following in your publication(s):

We thank Harvard Cancer Consortium in Boston, MA, for the use of the Bioinformatics Training Core, which provided ______________________________ service. Harvard Cancer Consortium is supported in part by a NCI Cancer Center Support Grant # NIH 5 P30 CA06516.

• Basic Data Skills (Shell/R)
• Applications of High-throughput sequencing(Transcriptomics, Epigenomics, Genomics)
• Functional Analysis
• Research Data Management
• Reproducibility Tools (Version control, Documentation)
• Consultations/Office Hours
• Educational infrastructure for HCC experts

Visit Upcoming Trainings(opens in new window)

Training Courses Available

• Current Topics in Bioinformatics Series (half-day or less workshops)
• Tools for Reproducible Research
• Introduction to High throughput Sequencing Analysis Series
  • Basic Data Skills (3-4 half-day sessions):
    • Shell for Bioinformatics
    • Introduction to R
    • Introduction to Python
• Advanced Topics: Analysis of High-Throughput Sequencing (3-4 half day sessions:
  • Introduction to Variant Analysis
  • Introduction to Differential Gene Expression Analysis
  • Investigating Chromatin Biology using ChIP-seq and CUT&RUN
  • Introduction to Single Cell RNA-seq Analysis (R-based/Python-based)
  • Introduction to Bulk RNA-seq: From Reads to Count Matrix
  • Tools for Reproducible Research
  • Pseudobulk and Related Approaches for Single Cell RNA-seq Analysis
  • Introduction to Peak Analysis
  • Introduction to Spatial Transcriptomics

New Courses (under development)

• GenAI for Biologists
   

Past Courses

• Gene annotations and functional analysis of gene lists
• Visualizations with ggplot2 and advanced plotting methods
• Big Data? Big Computer! The skill set you need to succeed
  • Basic, Intermediate and Advanced Shell scripting
  • Tips and Tricks on O2 (HMS RC cluster)
• Interact with your data using RShiny
• Publication Perfect: Creating publication-ready figures in R

• In 2024, the BTC collaborated with 258 HCC users from 122 labs from 17 HCC programs.
• Training priority is given to HCC members through dedicated spots in HBC courses.
• One-on-one help (30 min Zoom meetings) was provided to 33 HCC members.
• In exit surveys, trainees are typically “Satisfied” or “Very satisfied.”

1. Peak Analysis - Dec 3, 6, 10
2. Differential expression of single cell RNA-seq - Nov 12, 15, 19
3. Introduction to single-cell RNA-seq - Oct 25, 29, Nov 1
4. Introduction to R - Oct 8, 11, 15, 18
5. Variant Calling ** - Sep 17, 20, 24, 27
6. Shell for Bioinformatics ** - Sep 3, 6, 10
7. Differential Gene Expression (DGE) analysis - Aug 20, 23, 27, 30
8. Tools for Reproducible Research - Aug 6, 9, 13
9. Introduction to single-cell RNA-seq - Jul 26, 30, Aug 2
10. Introduction to R - Jul 23, 26, 30, Aug 2
11. Introduction to R - Jul 9, 12, 16, 19
12. Intro to Chromatin Analysis - Jun 18, 21, 25
13. Variant Calling ** - May 28, 31, Jun 4, 7
14. Introduction to Shell ** - May 17, 21, 24
15. Differential Gene Expression (DGE) analysis - Apr 30, May 3, 7, 10
16. Introduction to R - Apr 9, 12, 16, 19
17. Bulk RNA-seq (Part 1 - FASTQ to counts - Mar 29, Apr 2, Apr 5
18. Introduction to Shell - Mar 5, 8, 12
19. Introduction to single-cell RNA-seq ** - Feb 9, 13, 16
20. Introduction to R ** - Jan 23, 26, 30, Feb 2

**In-person Workshop

Marty Lafleur, Postdoctoral Fellow, Arlene Sharpe Lab, HMS, HCC Cancer Immunology

“My project is focused on performing high-throughput in vivo CRISPR screens to identify novel regulators of tumor immunity. Two keep computational needs I had were to (1) analyze the large arrayed data associated with CRISPR screens and (2) perform differential expression analyses on validated hits from these screens.”

Courses: Shell for Bioinformatics, Introduction to R, Intro to bulk RNAseq, differential expression analysis, Intro to single-cell RNAseq, Pseudobulk, Intro to R markdown, Intro to GitHub, and resolving conflicts in GitHub.

“I found these classes to be a great jumpstart into bioinformatics, offering the perfect balance of theory with actual practical coding . This provided me the foundation I was looking for to be able to actually start doing analyses and then build on this as I gain independent experience.”

LaFleur MW, Milling LE, Prathima P, Li V, Lemmen AM, Streeter ISL, Heisig PKS, Derosia NM, Riffo E, Xu H, Nguyen TH, Kolengaden A, Markson SC, Doench JG, Sharpe AH. A STUB1-CHIC2 complex inhibits CD8+ T cells to restrain tumor immunity. Nat Immunol. 2025 Sep;26(9):1476-1487. doi: 10.1038/s41590-025-02231-6. Epub 2025 Aug 12. PMID: 40796662; PMCID: PMC12483072.

Alexandra Indeglia, Postdoctoral Fellow, Karen Cichowski Lab, BWH, HCC Cancer Genetics and Epigenetics

“The training workshops held by HBC have been instrumental in my research and my development as a scientist. My projects are heavily reliant on genomics and transcriptomics techniques, which include ChIP-seq, RNA-seq, CUT&RUN, CUT&Tag, and scRNA-seq experiments.”

“I truly cannot speak highly enough of the training workshops in getting me to a point where I can confidently analyze the output of these experiments on my own. The workshops are led by fantastic teachers, all of whom are eager to help beyond the scope of the training session and go the extra mile to ensure everyone fully understands the lessons in the workshop. The courses are designed to gain a considerable amount of experience in a short amount of time, and I left each workshop with a framework for analyzing f uture experiments.”

“I have taken many bioinformatics workshops, and I can confidently state that these workshops are the most effective at teaching wet-lab scientists the skills needed to competently analyze and understand the results of their work .”

A Indeglia, AE Schade, S Sharma, A Gardner, A Yoshinaga, R Sahu, A Miller, K Cichowski. Targeting transcriptional drivers of plasticity and resistant cell states in triple negative breast cancer (in prep).

Muqing Li, Postdoctoral Fellow, Jia Li Lab, BWH, HCC Prostate Cancer

“I’ve taken nearly all of the workshops offered by the HMS/Harvard Chan Bioinformatics Core, and I genuinely believe this is the best open, practical bioinformatics training program in the world , especially for researchers like me who come from a biology background rather than a formal bioinformatics major. The workshops explained complex methods clearly and practically, and the O2 platform made it easy to use these skills directly in my work.”

“As a result, I now serve as the lead analyst for all sequencing-related projects in our lab, including RNA-seq, ChIP-seq, ATAC-seq, CUT&RUN, and single-cell data. The workshops have greatly improved my daily research work — it almost feels like I completed an additional degree in bioinformatics. It also built a strong foundation that has helped me continue learning on my own, including Python and even introductory machine learning, and has made it much easier to communicate with research collaborators.

“Several manuscripts and posters are currently in preparation that include analyses I performed using skills learned through the workshops, and I would be happy to share citations once they are public.

Thank you again to you and the whole team for your continued work to make this program stronger every year. I’m excited to see the new workshops and the growing online resources next year.”