Learn NGS Variant Calling: A Hands-on Bioinformatics Course

Explore Linux basics for bioinformatics, including command-line workflows, Ubuntu as a beginner-friendly option, and scripting to automate analyses with tools like blast, Hisat2, and Maxquant on HPC systems.

Set up the Windows Subsystem for Linux (WSL) on Windows, install Ubuntu, run PowerShell as administrator to enable WSL 2, then update packages and configure GUI apps via X server.

Master navigation of the Linux file system by understanding the root, absolute versus relative paths, and essential commands (pwd, ls, cd). Organize bioinformatics data with mkdir -p and structured directories.

Learn basic Linux commands for bioinformatics, including file and directory management, copying, moving, renaming, and deleting files, viewing content, and applying these to fastq, bam, and tiff datasets and workflows.

Process large bioinformatics text files in linux using grep, awk, and other tools to extract fasta headers, filter gff and gtf entries, and automate bkf and sam data manipulation.

Learn how to compress, decompress, and archive large bioinformatics data on Linux using gzip, gunzip, tar, tar.gz, and zip, enabling efficient storage and seamless data transfer.

Learn to perform variant calling from NGS data using Linux and R, understanding depth and coverage, and how germline and somatic variants differ, including SNVs, indels, and CNVs.

Learn to confidently identify SNPs and indels in NGS data using a five-step pipeline: data acquisition, alignment to the reference, variant calling, filtering, and visualization in R, with vcf/vqf formats.

Perform a hands-on ngs variant calling workflow from quality control to variant annotation, using fast QC, multi QC, BWA, Free Bias, and bkf tools to produce reproducible results.

Set up a linux environment for a variant calling workflow by installing wget, curl, MultiQC, samtools, bwa, freebayes, and porkchop, and configuring conda environments with Anaconda or Miniconda.

Learn a practical workflow for downloading public ngs data for variant calling, including quality control, trimming, alignment to a reference genome, depth analysis, and germline variant identification.

Perform quality control on raw fastq reads using fastqc and multiqc, assess per base quality and adapters, then trim with fastp before alignment to the reference genome and variant calling.

Learn how to index a reference genome and align reads with BWA, map reads to the reference, and prepare BAM files for variant calling, including read groups and quality checks.

Learn to filter and sort BAM files with samtools, fix coordinates, mark duplicates, index the final BAM, and call variants to generate a VCF in a practical NGS workflow.

Learn to call and filter variants from aligned reads, generate and index VCF files, compress and index with bkf tools, and visualize SNPs and indels for practical NGS variant calling.

Master R for bioinformatics—from installation and RStudio setup to core data structures and basic analysis. Apply Bioconductor packages and ggplot2 visualizations to identify differential expression and enrichment.

Learn to install and configure R and the RStudio IDE across Windows, macOS, and Linux, create projects, and enable optional Git version control for a bioinformatics workflow.

Install and manage R packages in RStudio using CRAN, Bioconductor, and GitHub; troubleshoot installations and update dependencies for reproducible bioinformatics workflows.

Visualize called variants from a VCF file in R using the plot VCF package, configuring quality thresholds, and highlighting samples, genes, and exons with color-coded plots.