MolBio Classes and Customized Trainings

To request a class, please contact MolBio.

Participants will learn how to access the CLC Genomics Server hosted on the HTC Cluster by Pitt CRC; import RNA-Seq FASTQ reads from a GEO dataset; assess the quality of RNA-Seq data; align reads to a reference genome; estimate known gene and transcript expression; perform differential expression analysis; and visualize data by generating PCA, volcano plot and heatmaps.
This is a 4-hour workshop. The morning session (10am - 12pm) provides a brief introduction to techniques, platforms, and methods used in chromatin profiling experiments, including Transcription Factor / Histone ChIP-Seq and ATAC-Seq. The afternoon session (1pm - 3pm) focuses on hands-on data analysis practice using HSLS-licensed CLC Genomics Workbench, Partek Flow, and TRANSFAC/Match software.
In this workshop, we will cover such multiomics data analysis - CITE Seq and Spatial Transcriptomics. Participants will learn how to import 10x Genomics CITE-Seq and Spatial Transcriptomics (Visium) data to PartekFlow; merge expression data with histological information; filter and normalize the data; and generate PCA, t-SNE, and UMAP plots to visualize data.
During the class, participants will learn how to: (1) access Center for Research Computing (CRC) clusters via Unix/Linux shell, (2) transfer files to CRC using FileZilla software, (3) create and manage files and directories, (4) edit files using vi text editor, and (5) access CRC-installed open source bioinformatics software such as FastQC, STAR, HISAT
This hands-on workshop will cover the creation of data visualizations using the ggplot2 package in R. Upon completion, participants will be able to create various graphical summaries of data, describe the “grammar” of ggplot2 functions, and build custom visualizations with ggplot2.
This is a flipped class and the third part of a series: Introduction to R; Data Wrangling in R, and Data Visualization in R. Upon registration, you will receive links to workshop materials (PowerPoint slides, lecture videos, and practice exercises) that you can view on your schedule. During the in-person hands-on session, you will learn how to solve the exercise problems. 

This is a flipped class covering the more advanced topics in R programming for data analysis and the second part of a three-part series: Introduction to R; Data Wrangling in R, and Data Visualization in R. Upon registration, you will receive links to workshop materials (PowerPoint slides, lecture videos, and practice exercises) that you can view on your own schedule. During the hands-on in-person session, you will learn how to solve the exercise problems. 

This workshop will focus on Gene Expression Omnibus (GEO) repository. We will learn how to find high throughput gene expression studies - bulk RNA-seq/ scRNA-seq /microarray from GEO, retrieve gene expression count data, and generate a list of differentially expressed genes (DEG) between two conditions (disease state vs. normal, drug treatment vs. control, virus infection vs. mock treatment). We will use a variety of bioinformatics tools such as BioJupies, Correlation engine, GEO2R, etc. Additionally, best practices and guidelines on how to submit your own high throughput gene expression data to GEO will also be discussed.
This workshop will cover gene expression visualization techniques using Partek flow and Cytoscape.
This workshop provides an overview of resources and search strategies on transcriptional regulation. Emphasis will be given to HSLS-licensed TRANSFAC/Match and Correlation Engine software and open-access tools such as the UCSC genome browser and Cistrome data browser.
This is a 4-hour workshop. The morning session (10 am - 12 pm) provides a brief overview of human genetic variations with the introduction to various genetic variation databases (dbSNP, ClinVar, HGMD, COSMIC, TumorPortal, gnomAD, and RegulomeDb). The afternoon session (1 pm - 3:00 pm) covers variant identification using the HSLS-licensed software CLC Genomics Workbench, how to use bioinformatics tools for functional analysis of mutations, and open-access web tools such as Ensembl Variant Effect Predictor and wANNOVAR.
This hands-on workshop focuses on a variety of genome biology resources. Learn to (1) identify and retrieve whole genome sequence information by searching databases (NCBI Genome, Integrated Microbial Genome), (2) navigate genome sequences and extract information from annotated genome data (UCSC Genome Browser), (3) construct complex queries and retrieve large-scale genome data (Table Browser), and (4) create custom genome browser tracks from users’ own uploaded data (UCSC Custom Track tool).
This is a flipped class; links to PowerPoint slides, lecture videos, and practice exercises that you can view on your schedule are available upon registration. During the session, you will learn how to solve the exercise problems.
This class will cover the basics of R programming for data analysis and graphics. This is a flipped class; links to PowerPoint slides, lecture videos, and practice exercises that you can view on your schedule are available upon registration. During the class, you will learn how to solve the exercise problems.
This workshop focuses on uncovering the biology hidden behind the extracted differentially expressed gene list by searching publicly available pathway enrichment analysis resources, including Gene Ontology (GO), Molecular Signature Database (MsigDB), Reactome, KEGG, and WikiPathways using GSEA and g: Profiler. How to generate enrichment maps from GSEA and g: Profiler results in Cytoscape will also be covered.

This workshop uses two library-licensed software - Ingenuity Pathway Analysis (IPA) and Illumina's Correlation Engine (CE)  to teach biological pathway enrichment analysis. Upon registration, you will receive links to workshop materials (PowerPoint slides, lecture videos, and practice exercises) that you can view on your schedule. During the class, you will learn how to solve exercise problems. 

Participants will learn how to:

The workshop provides a brief overview of bioinformatics concepts and software used for interpreting a gene list using pathway and network information, followed by a step-by-step guide on pathway enrichment analysis using two HSLS-licensed tools: Correlation Engine, and Ingenuity Pathway Analysis (IPA)
This workshop provides a brief overview of bioinformatics concepts and software used for interpreting a gene list using pathway and network information and focuses on software demonstration and hands-on exercise using HSLS-licensed tools: Correlation Engine, and Ingenuity Pathway Analysis (IPA).
This workshop will cover the more advanced topics in R programming for data analysis and graphics. Upon completion participants will be able to import and export data, merge datasets, transform data, and create basic summaries of data.
This workshop briefly introduces techniques, platforms, and methods used in bulk RNA-Seq experiments, followed by a step-by-step guide for a bulk RNA-Seq data analysis using the HSLS licensed CLC Genomics Workbench software.
This workshop briefly introduces techniques, platforms, and methods used in bulk RNA-Seq experiments, followed by a step-by-step guide for a bulk RNA-Seq data analysis using the HSLS licensed CLC Genomics Workbench software.
This workshop introduces the techniques, platforms, and methods used in generating single-cell RNA-Seq data, followed by a software demonstration on data analysis using HSLS-licensed Partek Flow.
This workshop briefly introduces the techniques, platforms, and methods used in generating single-cell RNA-Seq data, followed by a step-by-step guide on scRNA-seq data analysis using HSLS-licensed Partek Flow software. 
This workshop will teach how to analyze, annotate and identify cell types in single-cell NGS data using the HSLS licensed CLC Genomics Workbench.