Single Cell RNA-seq Workshop (Online)

  • Mon, Nov 4, 2024 - Sat, Oct 26, 2024
  • Online
  • Mr. Arian Amani & Mr. Adib Mirki
  • RSG Iran
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The Iranian Student Branch of the International Society for Computational Biology proudly announces its third workshop.


This workshop, taught by Mr. Adib Mirki and Mr. Aryan Amani (Computational Biologist Researchers and Research Assistants at the Wellcome Sanger Institute/University of Cambridge), will be held at Lotfollahi La in Tehran.  It offers both in-person and online participation opportunities.


In-Person Workshop with Mr. Adib Mirki:


  • Dates: Monday, October 22nd and Tuesday, October 23rd
  • Time: 9:00 AM to 1:30 PM
  • Location: Tehran, Karger Shomali Street, Farshi Moghadam Street, North Campus of University of Tehran, University of Tehran Science and Technology Park


Online Workshop with Mr. Aryan Amani:


  • Date: Saturday, October 27th
  • Time: 4:00 PM to 8:00 PM


Online Q&A Session:

  • Date: Thursday, November 6th
  • Time: 3:00 PM to 5:00 PM


**Limited Capacity**

  • 25 in-person spots
  • 20 online spots


Regular Registration Fee:

  • In-person: 1,100,000 Tomans
  • Online: 1,000,000 Tomans


Discounted Registration (valid until October 15th):

 Early Bird (Registration by October 15th):

    * In-person: 950,000 Tomans

    * Online: 850,000 Tomans

 Student Early Bird (Registration by October 15th):**

    * In-person: 920,000 Tomans

    * Online: 820,000 Tomans

 HBC Attendee Early Bird (Registration by October 15th):**

    * In-person: 900,000 Tomans

    * Online: 800,000 Tomans


All discounts are valid only until October 15th.  After this date, the regular price will apply. 

Mr, Adib Mirkis Workshop Topics

Session1: How to find an idea for analysis?, Resources, Data structure, Data Acquisition, Quality Control,  Log1p and Normalization,  Highly Variable Gene, PCA - 90+90 minutes

Session2: Batch Effect Correction Concept, scArches Pipeline, scVI usage, Expimap usage, scPoli usage, Visualization, Manual Annotation, Classification methods for cell type identification , DEG analysis ( rank_genes_group and edgeR) ,Enrichment analysis - 90+90 minutes

Session3: Cell-cell interaction, Pseudo-time and trajectory, RNA Velocity analysis (cell rank and scVelo), Pertpy pipeline, DecoupleR pipeline, GSEAPY pipeline,  Squidpy pipeline, CPA, NicheCompass pipeline - 90+90 minutes

Mr. Arian Amanis Workshop Topics

Introduction to Machine Learning (What is a Machine Learning?, Supervised vs. Unsupervised ML, Why ML for Single-Cell Biology?) - 10 minutes

Key Machine Learning Concepts (Features and Labels, Training vs. Testing Data, Overfitting and Underfitting) - 10 minutes

Data Representation and Preprocessing (Overview of Single-Cell Data as High-Dimensional Input, Feature Selection, Data Normalization and Preprocessing Steps for Single-Cell Data) - 10 minutes 

Supervised Learning (Logistic regression classification, Decision Trees/ Random Forests, Linear regression, Exercise: Build a Simple Classifier to Predict Cell Types) - 30 minutes

Unsupervised Learning: Clustering (K-Means, Evaluating Clustering Results: Silhouette Score, Elbow Method, Exercise: Apply Clustering to a Single-Cell Dataset) - 20 minutes 

Introduction to Deep Learning (Neural Networks, Deep Learning vs Traditional ML, How DL is good in handling large-scale high-dimensional data - 15-20 minutes 

Deep Learning Architectures in Single-Cell Biology ( Simple MLP (gene expression prediction or classification), AutoEncoders and Variational AutoEncoders (scVI overview),GANs if time allows, Exercise: Build a Simple VAE or GAN for Generating Single-Cell Data ) - 30-45 Minutes

 Applications of Deep Learning in Single-Cell Biology (Cell Type Classification Using Deep Learning, Integration of Single-Cell Datasets with VAEs, Perturbation Prediction Models) - 10 Minutes

Case Study (GEARS,CPA ,Hyperparameter Tuning) - 30 Minutes

 Foundation Models (Geneformer, scGPT, Fine-Tuning Foundation Models) - 15 Minutes

Challenges, Trends, Ethical Considerations (Computation (GPU, Foundation Models), Importance of interpretability in biology and health , Trends: multimodal data integration, anything else?, Ethics: Bias and use of personal information) - 15 minutes