Bioinformatics HUB Workshop Series I
Microbiome Data AnalysisThe Bioinformatics Hub is pleased to launch the first HUB (Hands-on Understanding of Bioinformatics) Workshop Series with Microbiome Data Analysis. This workshop will introduce foundational concepts and practical approaches for analyzing microbiome sequencing data, including data processing, taxonomic profiling, and basic downstream analyses. This workshop is designed to provide participants with practical, hands-on skills in microbiome data analysis using reproducible, containerized workflows. Participants will be introduced to our end-to-end analysis approach, including quality control, taxonomic profiling, and downstream statistical interpretation. We will also discuss how we evaluate and benchmark widely used microbiome analysis tools to ensure robust and reproducible results, and highlight version-controlled frameworks and best practices that support transparent and scalable microbiome research.  Workshop InformationThe workshop will combine short lectures with hands-on tutorials to introduce participants to standard workflows for microbiome data analysis, with a focus on 16S rRNA sequencing data. Topics will include raw data preprocessing and quality control, feature table construction, taxonomic assignment, normalization, visualization, and downstream statistical analysis using R. Commonly used microbiome analysis tools and packages will be introduced, and their strengths and limitations will be discussed in the context of reproducible research practices. The goal is to provide comprehensive analysis schemes for microbiome data preprocessing, analysis, and other bioinformatic tasks. Venue
Registration
PrerequisitesThis workshop is intended for beginners, and no prior experience with microbiome analysis is required. Basic familiarity with R is helpful but not mandatory. Foundational Linux concepts will not be covered; however, participants will be guided through a small number of command-line steps to launch Docker-based analysis environments. The instructors will use macOS and Linux-based systems during the sessions. Participants using Windows machines are welcome, provided that Docker and R are installed and functional prior to the workshop. MaterialsAll workshop materials, including example datasets, analysis scripts, and documentation, will be distributed electronically prior to the workshop. Participants will be provided with access to containerized workflows and sample 16S rRNA sequencing datasets to support hands-on exercises during the sessions. Detailed setup instructions will be shared in advance to ensure participants are prepared. Schedule
ObjectivesThis workshop is designed to build both conceptual understanding and practical proficiency in microbiome data analysis. By the end of this workshop, participants will be able to:
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Bioinformatics HUB Workshop Series II
Bulk RNA-seq Data AnalysisThe Bioinformatics Hub is pleased to present the second installment of the HUB (Hands-on Understanding of Bioinformatics) Workshop Series: Bulk RNA-seq Data Analysis. Building on the principles of reproducible and scalable bioinformatics workflows, this hands-on workshop will focus on end-to-end transcriptomic analysis using bulk RNA-seq data. This workshop is designed to equip participants with practical skills for analyzing bulk RNA-seq experiments, from raw data to biological interpretation. Through a combination of short lectures and guided tutorials, participants will learn how to perform data preprocessing and quality assessment, read quantification and normalization, differential expression analysis, and downstream functional interpretation. Emphasis will be placed on experimental context, transparent reporting, and reproducible execution using well-established tools and best practices. The workshop is intended to provide a strong foundation in transcriptomics in preparation for future single-cell RNA-seq training.  Workshop InformationThe workshop will be delivered as a hands-on, end-to-end training in bulk RNA-seq data analysis. Topics will include sequencing data quality control, read quantification, normalization strategies, differential expression testing, functional annotation, and result interpretation using R-based workflows. Participants will be introduced to commonly used RNA-seq analysis tools and packages, with discussion of their assumptions, strengths, and limitations in the context of reproducible research. The overall goal is to provide a coherent and practical framework for bulk RNA-seq data analysis and reporting. Venue
Registration
PrerequisitesThis workshop is intended for beginners, and no prior experience with microbiome analysis is required. Basic familiarity with R is helpful but not mandatory. Foundational Linux concepts will not be covered; however, participants will be guided through a small number of command-line steps to launch Docker-based analysis environments. The instructors will use macOS and Linux-based systems during the sessions. Participants using Windows machines are welcome, provided that Docker and R are installed and functional prior to the workshop. MaterialsAll workshop materials, including example bulk RNA-seq datasets, analysis scripts, and documentation, will be distributed electronically prior to the workshop. Participants will be provided with access to reproducible, containerized workflows to support hands-on exercises. Detailed setup and installation instructions will be shared in advance to ensure participants are fully prepared for the sessions. Schedule
ObjectivesThis workshop is designed to build both conceptual understanding and practical proficiency in bulk RNA-seq data analysis. By the end of this workshop, participants will be able to:
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Bioinformatics HUB Workshop Series III
Single-Cell RNA-seq Data AnalysisThe Bioinformatics Hub is pleased to present the third installment of the HUB (Hands-on Understanding of Bioinformatics) Workshop Series: Single-Cell RNA-seq Data Analysis. This workshop will provide a practical introduction to the analysis of single-cell transcriptomic data, building on core transcriptomics concepts and extending them to single-cell–specific analytical challenges. This hands-on workshop is designed to guide participants through the essential steps of single-cell RNA-seq data analysis, from data import and preprocessing to biological interpretation. Participants will learn how to perform quality control and filtering, normalization with consideration of batch effects, dimensionality reduction, clustering, and marker-based cell-type annotation. The workshop will also introduce common strategies for exploratory downstream analyses and reproducible reporting, enabling participants to confidently interpret and communicate single-cell RNA-seq results.  Workshop InformationThe workshop will combine short lectures with hands-on tutorials to introduce standard single-cell RNA-seq analysis workflows using widely adopted tools and R-based frameworks. Topics will include data ingestion and preprocessing, quality control metrics, normalization and batch-effect correction strategies, dimensionality reduction, clustering approaches, cell-type identification, and exploratory downstream analyses. Best practices for reproducible and transparent reporting of single-cell analyses will be emphasized throughout the workshop. The overall goal is to equip participants with an end-to-end, reproducible framework for single-cell RNA-seq analysis and reporting, enabling confident interpretation and communication of cellular heterogeneity and biological insights. Venue
Registration
PrerequisitesThis workshop is intended for beginners, and no prior experience with microbiome analysis is required. Basic familiarity with R is helpful but not mandatory. Foundational Linux concepts will not be covered; however, participants will be guided through a small number of command-line steps to launch Docker-based analysis environments. The instructors will use macOS and Linux-based systems during the sessions. Participants using Windows machines are welcome, provided that Docker and R are installed and functional prior to the workshop. MaterialsAll workshop materials, including example single-cell RNA-seq datasets, analysis scripts, and documentation, will be distributed electronically prior to the workshop. Participants will be provided with access to reproducible, containerized single-cell analysis workflows to support hands-on exercises. Detailed setup instructions will be shared in advance to ensure participants are fully prepared for the workshop sessions. Schedule
ObjectivesThis workshop is designed to build both conceptual understanding and practical proficiency in single-cell RNA-seq data analysis. By the end of this workshop, participants will be able to:
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