Module 1.RNAseq data analysis course includes:
  • Overview of NGS
  • Retrieval of NGS data (NCBI SRA)
  • Quality Check of reads (FastQC & Cutadapt)
  • De-novo transcriptome assembly (Trinity) / Alignment with the reference Genome (Tophat / STAR)
  • Visualization of mapped reads (UCSC & IGV)
  • Quantification of gene expression (Coverage, FPKM)
  • Differential expression analysis (Cufflink, cuffmerge & cuffdiff)
  • KEGG Pathway & Gene ontology (GO) enrichment analysis
  • Network analysis using string DB (PPI) & Cytoscape
  • Graphical representation of results (Heat map, volcano plot etc.)
Module 2.DNAseq data analysis course includes:
  • NGS introduction
  • Retrieval of NGS data (NCBI SRA)
  • Quality Check of reads (FastQC & Cutadapt)
  • Reads alignment using reference Genome (BWA/Bowtie)
  • Mapping Output (SAM/BAM, Samtools & Bedtools)
  • Variant detection & visualization (GATK & Samtools, IGV)
  • Variant effect prediction (SNPEff, SNPDB etc)
  • Predict the effects of coding non-synonymous variants on protein function
Module 3. miRNAseq analysis course includes:
  • NGS introduction
  • Retrieval of NGS data (NCBI SRA)
  • Alignment of reads using reference Genome (miRDeep2)
  • Known & Novel miRNA Detection (miRDeep2)
  • miRNA Target prediction (in-house script plus online tools)
  • Differential expression analysis (edgeR)
  • KEGG & GO analysis
  • Different plots (heatmap, volcano etc)
Module 4.Whole genome de-novo assembly course includes:
  • NGS introduction
  • Retrieval of NGS data (NCBI SRA)
  • Contig Assembly(SPAdes/SOAPdenovo/velvet/Masurca/Canu)
  • Scaffolding, Gap Closure & repeat masking
  • Gene/Orf prediction(prodigal/prokka/orf finder/Glimmer3/GeneMarkHMM/
  • Gene Ontology & KEGG Pathway analysis
  • Genome and Gene representation using circus
  • Phylogenetic Analysis
  • Comparative genomics / Synteny Analysis
Module 5. Metagenomics data analysis course includes:
  • Basics of Metagenomics
  • Data quality Check & trimming (FastQC, Cutadapt)
  • Demultiplexing and quality filtering sequence reads
  • OTUs identification (Qiime)
  • liersity Analysis (Alpha, Beta liersity)
  • Taxonomic composition and relative abundance plots
  • Heatmap, KRONA plot etc
Module 6. Microarray data analysis course includes:
  • Data retrieval
  • Gene expression analysis using R / Online tools
  • Quality control & normalization
  • DEG analysis (UP/DOWN-regulated genes)
  • KEGG & GO analysis
  • Graphical representation of results
Module 7: Codon usage bias (CUB) analysis course includes:
  • Basic concept of Codons
  • Data retrieval from NCBI
  • RSCU analysis
  • ENC analysis
  • Correspondence analysis
  • Codon context analysis
  • Generation of plots (ENC, Neutrality, parity etc.)
Module 8: Computer Aided Drug designing course includes:
  • Introduction to Structure based Drug Designing
  • Data mining, literature study and acquisition of target structure
  • Homology modelling
  • Server based –PHYRE, RaptorX, SWISSMODEL, I-TASSER, etc.
  • Protein structure validation (ProSA)
  • Ramachandran plot assessment(RAMPAGE,Pdbsum,Procheck)
  • Active site/ Pocket identification –MetaPocket,CastP,Active site identification using PyMol
  • Molecular Docking (AutoDock vina/AutoDock Tools)
  • Protein and ligand preparation for MD simulation
  • Building protein-ligand complex and visualization(publication standard)
  • Report construction
Module 9: Advanced Bioinformatics training course includes:
  • Basic concepts in Bioinformatics
  • Databases & tools (NCBI,UCSC,BLAST,BLAT etc)
  • ORF/Gene Prediction
  • Genome Annotation
  • Functional Annotation
  • Primer design & validation
  • Genome Vizualization
  • Hands on practical for Perl / BioPython
  • Basic Unix based commands