About this internship
The 6 Month NGS Bioinformatics Internship and Research Paper Guidance at Dr. Omics Edu is a 6-month live, mentor-supervised internship in next generation sequencing (NGS) and genomics under NEP 2020. Across ten modules it pairs full NGS pipeline training with guidance on turning results into a research paper. You work on a real dataset and a defined research question, and you finish with a genomics or transcriptomics project from raw reads to interpreted results that you can show to an admissions panel, a guide or an employer.
In this internship you move through linux, r and reproducible analysis environments, rna-seq, dna-seq and variant calling pipelines and differential expression and functional enrichment, then apply them in your own project. The programme runs live online with 10 modules, so you can ask your mentor questions as you work. It is open to learners at every level, and mentors adjust the pace to your background.
What you will achieve
Linux, R and reproducible analysis environments
RNA-seq, DNA-seq and variant calling pipelines
Differential expression and functional enrichment
Variant annotation and interpretation
Figure preparation and statistical reporting
Manuscript structure, writing and submission guidance
For careers: Bioinformatics analyst, genomics data analyst, NGS data scientist, research associate, and a stronger profile for M.Sc, MS or PhD admissions in genomics.
The project work
Hands-on implementation of everything covered in the sessions
Industry-standard tools and workflows
Project documentation and a final presentation
Code review and optimisation sessions with your mentor
Skills you will gain
Linux
FastQC
fastp
HISAT2/STAR
BWA
SAMtools
GATK
DESeq2
R
Certification
Available
Issued by Dr. Omics Edu
Internship curriculum
9 modules
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1) = Overview and Installation of Linux
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2) = Basic Linux Commands
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3) = Advanced Linux Commands
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4) = Package Management using Repository
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5) = Package Management using Source Code
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1) = Introduction to Python
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2)= Data Types
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3= String Handling
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4)= Data Structure
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5)=Control Structure
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6) = Function
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7)= File Handling
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8)= Data Manipulation
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9)= Data Visualization
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10)= Biopython
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1) = Introduction and Installation of R
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2)= Data Types in R
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3)= Data Structure
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4)= File Handling
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5)=Control Structure
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6) = Function
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7)= Package Management
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8)= Data Manipulation
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9)= Data Visualization
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10)= Statistical Analysis
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1)= Introduction to NGS and DNAseq
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2)= Basic Terminologies in NGS
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3)= Understanding of SRA database
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4)= Tools installation in Linux for Variation Calling
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5)= Quality control
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6)= Trimming of Reads
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7)= Indexing of Genome and Alignment of Reads
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8)= Variation calling using GATK
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9)= Variant Effect Prediction(VEP)
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10)= Variation Visualization (IGV)
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1)=Introduction to RNAseq and it’s basic terminologies
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2)=Tools installation in Linux for Gene Expression analysis
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3)=Quality control and Trimming of reads
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4)=Indexing of Genome and Alignment of Reads
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5)=Normalization of Data (Cufflinks)
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6)=Merging of Data and Differential expression of genes
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7)=Understanding of DEG results
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8)=Annotation of DEG
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9)=Functional and Pathway Enrichment Analysis
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10)=Network Analysis
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1)= Tools installation for De-novo RNAseq
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2)= Tools installation for De-novo RNAseq
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3)= Data downlading and Quality control
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4)= Assembly Creation
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5)= Abundance count estimation
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6) = Generation of count matrix and DEG
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7)= BLAST
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8)= Understanding the DEG results
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9)= Annotation of DEGs
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10)= Encrichment Analysis
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1)= Introduction to metagenomics
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2)= Tools installation for metagenomics
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3)= Data Downloading
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4)= Quality control & Trimming
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5)= Data importing in Qimme2
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6)= Data quality check using DADA2
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7)= Phylogentic Analysis
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8)= Taxonomy Analysis
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9)= Krona Plot
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10)= Phylogenetic tree construction
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1)= Introduction to MIcroarray
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2)= Introduction to Microarray
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3)= Data Downloading
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4)= Microarray Pipeline upto Normalization
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5)= Microarray Pipeline till DEG
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6)= Annotation of DEG
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7)= Encrichment Analysis
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8)= Network Analysis
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9)= Volcano Plot
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10)= Heatmap
What you need to start
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Basic understanding of Molecular Biology and Genetics.
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Familiarity with any programming language (Python or R is a plus but not mandatory).
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A laptop with a minimum of 8GB RAM for running local bioinformatics simulations.
Who this internship is for
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B.Sc, M.Sc, B.Tech, M.Tech and PhD students in biotechnology, genetics, microbiology, biochemistry, life sciences or bioinformatics, plus early-career researchers.
