DNA-Seq in Cancer Genomics: Variant Detection in Breast Cancer
Unlock the secrets of the cancer genome in this intensive, hands-on crash course. Transition from raw FASTQ files to identifying actionable mutations (SNVs, Indels, and CNVs) specifically in Breast Cancer datasets. Whether you are a biologist looking to go dry-lab or a data scientist entering oncology, this course provides the industry-standard pipeline (GATK, BWA, VEP) needed to drive precision medicine.
Course Description
Course Overview
Breast cancer is a highly heterogeneous disease driven by a complex landscape of genetic alterations. This course focuses on the DNA-Seq bioinformatics pipeline, specifically tailored for identifying somatic variants in breast cancer. Using real-world datasets (such as TCGA or matched tumor-normal pairs), participants will learn to navigate the computational challenges of tumor purity, heterogeneity, and subclonal evolution.
Why This Matters
Identifying mutations like BRCA1/2, PIK3CA, or HER2 amplifications is no longer just "research"—it is the backbone of Precision Oncology. This course equips you with the skills to turn massive sequencing data into a roadmap for targeted therapy and personalized patient care.
What You'll Learn
By the end of this course, you will be able to:
Independenty build a complete DNA-Seq pipeline for cancer research.
Distinguish between Germline and Somatic mutations with high confidence.
Identify "Driver" vs. "Passenger" mutations in breast cancer samples.
Interpret Variant Allele Frequency (VAF) to understand tumor purity.
Curriculum
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"1= Introduction to NGS and DNAseq
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2= Basic Terminologies in NGS
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3= Understanding of SRA database
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4= Tools installation in Linux for Variation Calling
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5= Quality control
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6= Trimming of Reads
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7= Indexing of Genome and Alignment of Reads
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8= Variation calling using GATK
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9= Variant Effect Prediction(VEP)
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10= Variation Visualization (IGV)"
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