| Course |
RNASeq - Denovo RNASeq / Differential expression / Bulk RNA analysis
|
| Duration |
online 15 Days Training [ 2 Hours Daily [ Monday To Friday ] ] |
|
Slots
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Our working Time is 9:00 AM to 6:00 PM Indian Time
Available slots - 9:00 AM to 11:00 AM / 11:00 AM to 1:00 PM / 2:00
PM to 4:00 PM
/ 4:00 PM to 6:00 PM
For training slots after 6 PM or before 9
am as well as
weekends training kindly mention during registration accordingly it
will be
scheduled.
|
|
Mode
|
👉 For online training candidate have to install ZOOM (with remote control on
candidate system which makes 100% interactive)
👉 Run time video recording candidate can make as well as pdf manual
will be
provided for future reference.
👉 All our training is 100% practical and 100% industrial and 100%
interactive
which provides same
as offline learning.
👉 For doubt clear there will be extra support will be provided
based on the
requirement.
👉 Certificate will be provided
|
| Sequencing Platform |
Illumina /Ion Torrent/PacBio/Nanopore |
| Raw data |
Candidate can include maximum 4 datasets of their own during training.
Publication standards figures and tables will be generated.
|
| Training Fees |
|
|
Support
|
Candidate can also discuss and possible implementation with their
own genomic
data or any data too during the course.
|
| Module-I |
Advanced Bioinformatics & basic programming |
| Topics |
📘 Introduction to Bioinformatics
- Overview of bioinformatics and its applications
- Key concepts in computational biology
- Role of bioinformatics in genomics, transcriptomics, and proteomics
📘 Understanding NGS and Genomics Bioinformatics
- Basics of Next-Generation Sequencing (NGS)
- Types of NGS data (RNA-seq, WGS, WES)
- Overview of NGS data formats: FASTQ, BAM, VCF
- Introduction to pipelines and tools for NGS data analysis
📘 Databases & Data Retrieval (NCBI and UCSC)
- Learning how to retrieve biologically correct data
- Performing complete batch retrieval (e.g., whole exome)
- NCBI: understanding gene-level data retrieval
- UCSC: handling large-scale data retrieval
- UCSC Genome Browser and Table Browser usage
- Batch Coordinate Retrieval and Genomic Data downloads
- GFF/GTF gene annotation formats and how to retrieve them
- Using BLAT for sequence-based search and alignment
📘 Gene Prediction and Functional Annotation
- Gene prediction approaches and tools
- Functional annotation using Gene Ontology (GO)
- Pathway analysis using KEGG, Reactome
- Interpreting gene sets and biological relevance
📘 Standalone/Offline BLAST for Large-Scale Genomic Data
- Installing and setting up standalone BLAST
- Running local BLAST for batch sequence alignment
- Applications in genome-wide homology searches
- Custom BLAST databases and performance optimization
📘 PCR Primer Designing and Specificity Check
- Designing accurate primers for PCR amplification
- Tools: Primer3, NCBI Primer-BLAST
- Checking primer specificity using genome-wide BLAST
- Avoiding non-target amplification through design best practices
📘 Understanding Python Programming
- Introduction to Python for bioinformatics
- Scripting basics: variables, loops, functions
- Libraries like Biopython, pandas for biological data handling
- Automating genomic workflows with Python scripts
|
| AND |
| Module-II |
Next Generation Sequencing (NGS) - RNASeq (Denovo based) Data Analysis
|
| Topics |
📘 Introduction to Bioinformatics and NGS
- Definition and scope of Bioinformatics
- NGS Technologies: Illumina, PacBio, Nanopore
- Types of NGS Applications: RNA-Seq, De novo, ChIP-seq, WGS,
Metagenomics, etc.
- Overview of De novo based NGS data analysis algorithms and
pipelines
📘 Linux Basics and Tool Installation
- Basic Linux commands for bioinformatics
- Installing tools using conda, apt, or source
- Setup and installation of essential NGS tools
📘 Data Retrieval and File Types
- Download data from NCBI SRA or EBI SRA using SRA Toolkit
- Understanding key file formats: FASTQ, SAM/BAM, GTF/GFF,
FASTA
📘 Read Quality Control
- Assessing raw read quality
- Trimming adapters and low-quality bases
📘 Transcriptome Assembly
- Calculating assembly statistics
- Coverage calculation and evaluation
📘 Transcriptome Functional Annotation
- Gene description assignment
- Functional annotation with GO terms and pathways
📘 Gene Expression Quantification
- Calculating read coverage and gene counts
- Compute expression levels (RPKM, FPKM, TPM)
📘 Differential Expression Analysis
- Differential expression calculation
- Obtain log fold changes, p-values, and adjusted p-values
📘 Enrichment Analysis
- Gene Ontology and pathway enrichment analysis
- GSEA (Gene Set Enrichment Analysis)
📘 Network Analysis (PPI)
- Explore protein-protein interaction networks using STRINGdb
- Visualize interaction networks in Cytoscape with plugins
📘 Pathway Mapping using KEGG Mapper
- Map differentially expressed genes (DEGs) to KEGG pathways
- Visualize active pathways (upregulated/downregulated
genes)
📘 Basics of R Programming
- Understand data types, control structures, and packages in R
- Installing and using Bioconductor tools
📘 Coexpression Analysis
- Introduction to coexpression analysis concepts and tools
📘 Data Visualization with R
- Generate heatmaps, volcano plots, and PCA plots
- Tools: ggplot2, DESeq2, ComplexHeatmap
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|
Preparation
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- RNAseq Denovo : https://en.wikipedia.org/wiki/De_novo_transcriptome_assembly
- NCBI : https://pubmed.ncbi.nlm.nih.gov/20935650/
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Instructor
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Industry Experienced
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Target Audiance
|
This course is designed for graduate students, postdoctoral
researchers, and
professionals working in the fields of conservation biology,
evolutionary
genomics, and population genetics or any life sciences who are
interested in
applying genomic tools to real-world conservation challenges.
|
|
Contact
|
Please write us at
info@arraygen.com or call
or whatsapp us on mobile +91-9673625446 if you need any
clarification or for any custom training based on candidate
reference paper
or candidate own content/tools.
|