Computational Genomics 

Day 1: Introduction to Computational genomics, Transcriptomics, Proteomics, Epigenomics, Metagenomics and their applications, The BIG data of biological sciences

Day 2: Organization of genetic information in prokaryotic and eukaryotic cell, genome maps, Eukaryotic genome structure, High-throughput technologies to translate this information into genomic data

Day 3: How genomic data is organized in public databases, Genomics web resources, Nucleic acid and protein sequence databases, gene expression databases, Metabolic and metabolomic databases. Examples: NCBI GenBank and Expasy, EBI, Ensembl, UCSC, KEGG

Day 1: First, second generation sequencing technologies including Sanger and Illumina and their data output

Day 2: Long read sequencing and linked read sequencing (Nanopore, PacBio, TELL-Seq)

Day 3: Sequence formats: FASTA, GenBank, EMBL, XML, Fastq, fast5, etc., genomic database versions and archives, NCBI SRA, bio-project, accessions, data retrieval using wget, FTP, FileZilla, and scripts provided by the database team for genomic analysis

Day 1: Introduction to Linux, basic commands for file handling

Day 2: Running jobs on Linux, processing, installation of genomic packages

Day 3: Introduction to R, commonly used packages, applications in genomic analysis

Day 1: Introduction to genomes and packages for genomic analysis such as EMBOSS; Specifications of workstations needed for genomic analysis, Introduction to High Performance Computing and servers, and their need in genomic analysis

Day 2 : Overview and concepts in genomic and transcriptomic analysis of an organism with examples and case studies

Day 3: Sample collection, DNA extraction and quantification, and species identification of the species to be sequenced. RNA extraction and transcriptome sequencing approaches

Day 1: Methods to estimate the amount of sequencing coverage needed for genomic assembly, use of hybrid sequencing approaches for appropriate coverage and assembly

Day 2: Short and long reads, paired-end reads, quality filtering of sequence data, Genome complexity assessment, Jellyfish and GenomeScope for generating k-mer count histograms and calculating genomic heterozygosity

Day 3: Concept of genome assembly, contigs, scaffolds, complete genome, draft genome, chromosomal level assembly, Genome assembly algorithms such as De-Bruijn graph, Overlap layout consensus (OLC), Hybrid assembly

Day 1: Introduction to common assembly tools ABySS, SOAPdeneno, Flye, Supernova

Day 2: 10X genomic linked-read sequencing, use of proc10xG set of python scripts to pre-process the 10x Genomics raw reads, removal of barcode sequences

Day 3: Nanopore long reads analysis: Guppy for base calling of raw reads, adaptor removal using Porechop, Genome assembly workflow using three different assemblers: wtdbg, SMARTdenovo, and Flye, parameters for assembly

Day 1: de novo assembly using Supernova, parameters, usage of genomic and transcriptomic reads to increase assembly contiguity

Day 2: Merging assemblies to create hybrid assembly, gap closing of assembly and polishing, fixation of small indels, base errors, and local misassemblies, determining the quality of assembly using N50, BUSCO scores, coverage etc.,

Day 3: Chromosomal level assembly using Hi-C, concept of reference genome, finished genome, draft genome, case studies

Day 1: Annotation of repeats in final genome assembly using RepeatMasker, Determining the simple and complex repeat content of a genome

Day 2: de novo transcriptome assembly, Determining the coding gene set using MAKER pipeline

Day 3: Prediction of tRNA, rRNA and miRNA in a genome, Identification of metabolic pathways by KEGG

Day 1: Comprehensive functional annotation of predicted genes or protein sequences by homology-based alignment using Blast or Blat, COGs, Gene ontology based annotation, Interproscan, PROSITE, Pfam, prints, patterns, motifs and fingerprints

Day 2: Evolutionary analysis using homologs, paralogs and orthologs, Multiple signs of adaptation, gene family expansion and contraction

Day 3: Taxonomic classification, marker sequences such as 16S rDNA and ITS, taxonomic hierarchy, Phylogeny reconstruction using multiple sequence alignment, Distance based approaches such as Neighbour joining, Character based approaches such as Maximum parsimony, Maximum likelihood, RAxML

Day 1: Epigenetics, ChIp-seq, transcriptome and microarrays for regulation of expression

Day 2: Single cell genomics, 10X Chromium linked-reads and Illumina sequencing, single cell gene expression

Day 3: Application of multiomics approaches in human health and diseases such as cancer, diabetes, etc.

Day 1: Prokaryotic genome sequencing and assembly approaches, draft and complete genomes, taxonomic identification

Day 2: Gene prediction approaches and common methods, annotation of a bacterial genome, t-RNA, rRNA, operon prediction

Day 3: Phylogenetic, metabolic and comparative analysis

Day 1: Microbiome and Metagenome, Human, organismal and environmental microbiomes

Day 2: Sequencing and assembly of metagenomes, gene prediction, annotation, MAGs

Day 3: Taxonomic analysis using amplicon sequence variants, Statistical analysis