Bioinformatics Workshops | crc.pitt.edu | University of Pittsburgh

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Bioinformatics workshops - Fall 2024

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 CRC 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 CRC clusters. Access to CRC clusters requires an account. If you do not yet have an account on CRC 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.

Spatial Transcriptomics WORKSHOP 1

Sep. 30, Monday, 1:00pm - 4:00pm

10X Spatial Transcriptomics (Visium)- Sample requirements, evaluate sample quality, tissue optimization, sample and library preparation, and library QC and sequencing. Presented by Amanda Poholek

Demo on 10X genomics cloud analysis: From FASTQs to biological information with Space Ranger

Running Space Ranger using the CRC cluster: For fresh frozen samples and formalin fixed paraffin embedded samples Presented by Dhivyaa Rajasundaram

Spatial Transcriptomics WORKSHOP 2

Oct. 1, Tuesday, 1:00pm - 4:00pm

Introduction to 10X Visium and Visium HD Data Analysis - Step by step analysis to correct batch effects between datasets, pre-processing spatial transcriptomics data, identification of spatial features, and spatially variable genes identification.

Basic R knowledge required. Presented by Silvia Liu

Spatial Transcriptomics WORKSHOP 3

Oct. 2, Wednesday, 1:00pm - 4:00pm

Exploring Visium data: Deconvolution and Mapping Methods: Integrating scRNA-seq and spatial data. Cell-type deconvolution of the spatially resolved transcriptome and visualization.

Basic R knowledge required. Presented by Jiefei Wang

Spatial Transcriptomics WORKSHOP 4

Oct. 3, Thursday, 1:00pm - 4:00pm

Cell-Cell Communication Analysis: Uncover cell-cell communications for spot-based spatially resolved transcriptomics data. Spatially informed ligand-receptor and ligand-receptor-target analysis.

Basic R knowledge required. Presented by Dhivyaa Rajasundaram

Spatial Transcriptomics WORKSHOP 5

~~Oct. 4, Friday, 1:00pm - 4:00pm~~

Oct. 15, Tuesday, 1:00pm-4:00pm (rescheduled)

Gene Co-expression Network Estimation for Spatial Transcriptomics: Cover basics of WGCNA and perform co-expression network analysis on spot-based spatial transcriptomics data.

Basic R knowledge required. Presented by Jishnu Das

Spatial Transcriptomics WORKSHOP 6

Oct. 7, Monday, 1:00pm - 4:00pm

The Single-Cell Spatial Transcriptomics Analysis (ScSTA) Cookbook

This workshop aims to provide attendees with comprehensive knowledge and hands-on experience in the data analysis of sub-cellular resolution single-cell spatial transcriptomics (ScST) technologies such as Nanostring CosMx and 10X Genomics Xenium. We will start with an introduction to the components of ScST, including image registration, cell segmentation, cell type identification, spatial gene expression analysis, and more. A hands-on guided tutorial using real-world lung adenocarcinoma and COVID-19 datasets will follow. Presented by Arun Das

Spatial Transcriptomics WORKSHOP 7

Oct. 8, Tuesday, 1:00pm - 4:00pm

10X Genomics Xenium data analysis

The hands-on session will provide a solid foundation for handling and analyzing 10x Genomics Xenium datasets. We will begin with the Xenium onboard analysis ranger to conduct initial data exploration and quality assessment. Following this, we will move on to a downstream analysis pipeline using the Seurat workflow, which includes data import, quality control, dimension reduction and clustering, visualization and integration. We will also briefly cover advanced topics including cell segmentation, cell type deconvolution and integration with single cell data. Presented by Dhivyaa Rajasundaram

Monai for biomedical image analysis

Nov. 14, Thursday, 1:00pm - 4:00pm

This workshop will explore Project MONAI, a set of open-source, freely available collaborative frameworks built for accelerating research and clinical collaboration in Medical Imaging. The goal of MONAI is to accelerate the pace of innovation and clinical translation by building a robust software framework that benefits nearly every level of medical imaging, deep learning research, and deployment.
Prerequisite: Introductory deep learning knowledge, with comfort with PyTorch and transfer learning preferred. Intermediate Python experience, including object-oriented programming and libraries. Presented by Yassin Khalifa

Leveraging large language models for single-cell and biomedical research

Dec. 10, Tuesday, 1:00pm - 4:00pm

This workshop will introduce emerging large language models (LLMs), including GPT-4 developed by OpenAI. We will discuss “prompt engineering” techniques to efficiently and effectively use these LLMs for biomedical research, such as cell type annotation for scRNA-seq data and the inference of gene-gene regulatory mechanisms and gene-drug relationships using scientific publications. Attendees will have hands-on experience with open-source LLMs and prompt engineering using CRC clusters. Presented by Yu-Chiao Chiu