Modules
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