Due to lack of trained personnel for NGS(Next-Generation Sequencing) analysis in Pakistan and around the globe, BioCode is conducting an in-person workshop in cancer genomics that will help the attendees to conduct industrial, real life analysis of cancer dataset to identify differentially expressed genes.

The study of cancer genomes has revealed abnormalities in genes that drive the development and growth of many types of cancer. This knowledge has improved our understanding of the biology of cancer and led to new methods of diagnosing and treating the disease.

Cancer genomics is the study of the totality of DNA sequence and gene expression differences between tumour cells and normal host cells. Next-generation sequencing (NGS) is a massively parallel sequencing technology that offers ultra-high throughput, scalability, and speed. The technology is used to determine the order of nucleotides in entire genomes or targeted regions of DNA or RNA. RNA-Seq is an exciting and in-demand next-generation sequencing (NGS) method used for identifying genes and pathways underlying certain diseases or conditions.

You don’t need any prior knowledge in order to attend this workshop. Each and everything related to NGS, RNA-Seq & cancer genomics will be taught in this workshop, followed by analysis on real life dataset. BioCode’s next-generation cancer genomics workshop will be hands-on which means you will learn every little thing about the theoretical as well as the practical aspect of NGS analysis.

This workshop will include the following sessions:

Session 1: In-depth Introduction to NGS, RNA-Seq and Cancer Genomics

Description: This session will focus on making sure that the attendees grasp the basic concepts of Next-Generation Sequencing, RNA-Sequencing and Cancer Genomics.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Explain Next-Generation Sequencing and its importance in diagnosing clinical cancer.
2. Describe RNA-Sequencing and how it is useful in cancer research.
3. Discuss Cancer Genomics and how it is transforming diagnosis and treatment
4. Use Linux Operating System for Genomics Analysis.
5. Write Python scripts in order to automate the pipeline.

Session 2 : Data Retrieval: Raw FASTQ Files

Description: In this session participants will perform data retrieval where they will retrieve real life cancer dataset in the form of fastq/bam files.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Use ArrayExpress or other cancer genomics databases.
2. Download the raw cancer dataset in fastq/bam file format.

Session 3 : Quality Control: FASTQC, FASTP, Cutadapt

Description: In this session participants will perform preprocessing and quality control on the already downloaded cancer datasets which are in the fastq/bam file formats. This will include checking the quality of the data and trimming the low quality reads so that the data is free from adaptor contaminated sequence reads.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Understand the purpose of quality control
2. Use FastQC tool to do quality assessment of NGS data
3. Use Fastp tool to perform quality control, trimming of adapters, filtering by quality, read pruning & multi-threading.
4. Use Cutadapt tool to do quality control, trimming of adapters, filtering by quality, read pruning & multi-threading.

Session 4 : Read Mapping: HISAT2, STAR, BWA, BowTie2

Description: In this session participants will perform alignment because these filtered sequenced reads have no value until they are mapped/aligned against a reference genome or assembled into a genome using de novo assembly.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Discuss Alignment/Read-Mapping.
2. Get aligned reads in BAM files.
3. Understand the working of HISAT2, STAR, BWA, BowTie2.
4. Generate Python scripts for alignment.

Session 5 : Quality Check: Recalibration, Duplicate Removal

Description: In this session participants will perform a quality check on genomics data which includes recalibration and duplicate removal.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Understand the purpose of Quality Check.
2. Use the Picard tool.
3. Remove duplicates from data using the MarkDuplicate function in Picard tool.

Session 6: Visualization: IGV

Description: In this session participants will be able to do the visualization of the genomic data on IGV (Integrative Genomics Viewer) tool.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Learn the importance of visualization.
2. Use IGV tool to perform visualization.

Session 7: Assembly & Quantification: Stringtie

Description: In this session participants will be able to perform the next step which is assembly and quantification using StringTie.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Understand the reason for performing assembly and quantification.
2. Use StringTie assembler for assembly and quantification.

Session 8: Differential Gene Expression Analysis: DESEQ2, Ballgown, edgeR

Description: In this session participants will finally be able to do the differential gene expression analysis.

Learning Outcomes: Upon completion of this session, participants will be able to:

1. Discuss the purpose of performing Differential Gene Expression Analysis.
2. Introduction to R language.
3. Perform Differential Gene Expression analysis using DESEQ2.
4. Perform Differential Gene Expression analysis using Ballgown.
5. Perform Differential Gene Expression analysis using edgeR.