Course |
RAD-Seq Data Analysis
|
Duration |
15 Days Training [ 2 Hours Daily [ Monday To Friday ] ] |
Slots
|
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
|
Online (one to one individual Focused Training)
π For online training candidate have to install ZOOM (with remote
control on
candidate system which makes 100% interactive)
π Run time video recording candidate can make as well as pdf manual
will be
provided for future reference.
π All our training is 100% practical and 100% industrial and 100%
interactive
which provides same
as offline learning.
π For doubt clear there will be extra support will be provided
based on the
requirement.
π Certificate will be provided
|
Sequencing Platform |
Illumina
| |
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 |
π Introduction to Bioinformatics
- Overview of bioinformatics and its applications
- Key concepts in computational biology
- Role of bioinformatics in genomics, transcriptomics, and proteomics
π 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
π 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
π 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
π 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
π 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
π 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) - RAD-Seq Data Analysis
|
Topics |
π RAD-Seq Basics
- Understanding NGS and Application RAD-Seq and understanding
different data formats
π Linux and Tool Installation
- Linux installation and NGS tools installation
π Quality Control
- Quality control of raw reads: Check the quality
of sequencing reads and detect issues like adapter contamination or
low-quality bases
- Demultiplexing samples by barcode: Separate
sequencing reads into individual samples using sample-specific
barcodes with process_radtags
- Trim adapters and low-quality bases: Remove
adapter sequences and trim poor-quality ends from reads using
Trimmomatic
π Read Alignment and Assembly
- Align reads or assemble loci de novo: Raw reads
were mapped based on reference or denovo based
π SNP Calling and Filtering
- Call SNPs and genotype samples: Identify SNPs and
assign genotypes using Stacks
- Filter SNPs by quality and coverage: SNPs were
filtered based on coverage depth, minor allele frequency, and
missing data
π Population Genomics Analysis
- Population genomics analyses: Post analysis such
as PCA, genetic structure, and diversity studies
π Variation Visualization
- Variation Vizualization: Variation vizualization
using IGV browser
|
Preparation
|
- RAD-Seq : https://en.wikipedia.org/wiki/Restriction_site_associated_DNA_markers
- NCBI : https://pmc.ncbi.nlm.nih.gov/articles/PMC3080771/
|
Instructor
|
Industry Experienced
|
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
offline training or for any custom training based on candidate
reference paper
or candidate own content/tools.
|