Bioinformatics workshops - Fall 2025
We continuously organize basic and advanced workshops on a wide range of bioinformatics topics. These workshops are designed to address practical issues often encountered in bioinformatics work. They are designed to help users understand and work with the CRCD clusters.
Free and open to everyone at University of Pittsburgh and its affiliates.
Participants must be physically present in order to participate. The conference room can accommodate ~30 attendees. Attendees are seated on a first-come, first-served basis. To ensure a high-quality experience for all participants and instructors, remote attendance is not accommodated.
Please note that you will need to bring your own laptop to connect to CRCD clusters. Access to CRCD clusters requires an account. If you do not yet have an account on CRCD clusters, we will create a temporary account for you. You will connect to Pitt wireless from your own laptop. You will logon ondemand.htc.crc.pitt.edu and run RStudio server, Jupyter Notebooks or submit batch jobs during the workshop. You do not need to install any software on your own laptop.
Some basic understanding of R or Python programming and the Linux environment will be advantageous, but is not required. All scripts will be carefully explained to allow all attendees understanding the rationale.
Visium spatial transcriptomics data analysis
Date: Wednesday, Oct. 1, 2025, 1:00pm – 4:00pm
To register: https://pitt.co1.qualtrics.com/jfe/form/SV_5mzILOhOvzEFi6O
1:00pm – 2:00pm Dhivyaa Rajasundaram will overview Visium data analysis
2:00pm – 2:15pm, break, RStudio or Jupyter notebook setup
2:15pm – 3:00pm, Silvia Liu will go through Seurat pipeline from raw counts to cell annotation.
3:00pm – 3:30pm, Cell-type deconvolution methods for spatial transcriptomics, Paul Cantalupo
3:30pm – 4:00pm, an advanced session, TBD, Dhivyaa Rajasundaram
Birds-of-a-Feather sessions gather community members to discuss a topic of shared interest without a pre-planned agenda. Each panelist will give a short presentation up to 30 minutes. Please bring your open problems to analyze spatial transcriptomics data to the BoF sessions, we'd like to discuss open problems, challenges and future directions in spatial transcriptomics data analysis.
Birds-of-a-Feather Session 1: Analysis of 10X Visium spatial transcriptomics data
Date: Wednesday, October 15, 2025, 1:00pm – 4:00pm
Panelists: Jishnu Das, Paul Cantalupo, Jiefei Wang
To register: https://pitt.co1.qualtrics.com/jfe/form/SV_9oQLnGCjcBsZlHg
Analyzing spatial transcriptomics data involves several key steps and requires specialized bioinformatics tools and pipelines. This BoF focus on secondary analysis of 10X Visium spatial transcriptomics data. The steps include Cellular Interaction Analysis, Data Integration with scRNA-seq, Spatial Trajectory Analysis and Differential analysis of spatial transcriptomic experiments. This BOF will provide an opportunity to review current practices and Challenges in spatial transcriptomics data analysis, including Data Size and Complexity, Reproducibility, etc. solicit feedback on past efforts, and brainstorm a roadmap for future activities to further strengthen reproducibility practices in 10X Visium spatial transcriptomics secondary data analysis.
Birds-of-a-Feather Session 2: CosMx Spatial Molecular Imaging data analysis
Date: Wednesday, Oct. 22, 2025, 1:00pm - 4:00pm
Panelists: Huma Asif, Brian Isett, Jie Chen
To register: https://pitt.co1.qualtrics.com/jfe/form/SV_3DlwMq2S0wSNiCO
CosMx Spatial Molecular Imaging (SMI) data analysis involves visualizing, quantifying, and interpreting spatial gene and protein expression patterns within tissue samples at single-cell resolution. This BoF focuses on Key aspects of CosMx SMI data analysis. The steps include Data Acquisition and Preprocessing, Spatial Visualization, Cell Type Identification, Spatial Clustering and Domain Analysis, and Pathway Analysis and Ligand-Receptor Interactions. This BOF will provide an opportunity to review current strategies or best practices to speed up the analysis, particularly regarding memory usage and computational efficiency, and brainstorm a roadmap for future activities to analyze CosMx SMI data.
Questions:
How can we best utilize HTC OnDemand RStudio for CosMx analysis in terms of cores and memory particularly for functions in Seurat that cannot be parallelized using future.