JavaScript seems to be disabled in your browser.
You must have JavaScript enabled in your browser to utilize the functionality of this website.

Home
WSQ - Bioinformatics Data Analysis with R Bioconductor

WSQ - Bioinformatics Data Analysis with R Bioconductor

7 Review(s) | Add Your Review

This WSQ Bioinformatics Data Analysis with R Bioconductor course equips learners with essential bioinformatics skills, focusing on using R Bioconductor to analyze biological data. Participants will explore sequence alignment, structural bioinformatics, and variant calling, while applying statistical techniques to uncover trends and interpret complex datasets. The course also covers statistical tests for data acceptability and introduces data visualization tools for bioinformatics.

Learners will dive into advanced topics such as machine learning for predictive modeling, genomic data analysis, and clustering biological data. With practical exercises in transcriptomics, variant detection, and big data analytics, students will gain the ability to develop new bioinformatics methods and facilitate discussions on bioinformatics issues. This course is ideal for professionals aiming to leverage R Bioconductor in solving real-world bioinformatics challenges.

Learning Outcomes

By end of the course, learners should be able to:

LO1: Recognize significant trends and aberrant results in bioinformatics data using statistical techniques.
LO2: Use statistical tests and data analytics tools to estimate uncertainties and determine data acceptability.
LO3: Review datasets to uncover trends or patterns and identify potential causes of unacceptable data.
LO4: Develop new methods for analyzing large, complex bioinformatics datasets using specialized modeling software.
LO5: Facilitate discussions on applying big data analytics to examine bioinformatics issues and derive insights.

Course Brochure

Download WSQ - Bioinformatics Data Analysis with R Bioconductor Brochure

Skills Framework

This course follows the guideline of Data and Statistical Analytics HCE-DAT-4007-1.1 under Healthcare Skills Framework

Certification

Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.
OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is subjected to funding caps.

Effective for courses starting from 1 Jan 2024
Full Fee	GST	Nett Fee after Funding (Incl. GST)
		Baseline	MCES / SME
$2,000.00	$180.00	$1,180.00	$780.00

Baseline: Singaporean/PR age 21 and above
MCES(Mid-Career Enhanced Subsidy): S'porean age 40 & above

Upon registration, we will advise further on how to tap on the WSQ Training Subsidy.

You can pay the nett fee (after the WSQ training subsidy) by the following :

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used. Click here for SkillsFuture Credit submission

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year. Click here to submit UTAP

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2024049780)

Scroll down to “Keyword Tags” to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us.

Course Code: TGS-2024049780

Post-Course Support

We provide free consultation related to the subject matter after the course.
Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Course Cancellation/Reschedule Policy

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
Note the venue of the training is subject to changes due to availability of the classroom

Course Details

Topic 1: Introduction to Bioconductor and Sequence Analysis

Overview of Bioinformatics
Understanding Sequence Alignment
Introduction to Bioconductor
Multiple Sequence Analysis
Interpreting Sequence Similarity Scores

Topic 2: Structural Bioinformatics and Variant Calling

Introduction to Structural Bioinformatics
Analysing Protein Structures
Variant Calling Using Bioconductor
Evaluating Relationships Between Protein Structures and Functions

Topic 3: Transcriptomes, Genomics, and Variant Analysis

Introduction to Transcriptome Data Analysis
Genomic Data Analysis and Visualization
Gene Expression Analysis and Differential Expression
Variant Detection and Annotation in Genomic Data

Topic 4: Machine Learning for Bioinformatics

Introduction to Machine Learning
Machine Learning for Predictive Modelling in Bioinformatics
Clustering and Classification of Biological Data
Predictive Models for Genomic and Transcriptomic Data

Topic 5: Data Visualization for Bioinformatics

Creating Data Visualizations using ggbio
Heatmaps for Transcriptomic and Genomic Data
Visualizing Biological Pathways and Networks
Communicating Biological Insights through Effective Visualizations

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

Able to operate using computer functions
Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

Positive Learning Attitude
Enthusiastic Learner

Experience

Minimum of 1 year of working experience.

Target Age Group: 21-65 years old

Minimum Software/Hardware Requirement

Software: NIL

Hardware: Windows and Mac Laptops

SSG Training Grant

SSG TG is $15 per pax. Net fee after SSG TG is $309.82. Absentee Payroll is not eligible.

Steps to Apply Skills Future Claim

The staff will send you an invoice with the fee breakdown.
Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
Upload your invoice and click ‘Submit’

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

Note

SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

The candidate has the right to disagree with the assessment decision made by the assessor.
When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
The candidate must lodge the appeal within 7 days, giving reasons for appeal
The assessor can help the candidate with writing and lodging the appeal.
he assessment manager will collect information from the candidate & assessor and give a final decision.
A record of the appeal and any subsequent actions and findings will be made.
An Assessment Appeal Panel will be formed to review and give a decision.
The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Bioinformatics Analyst
Data Scientist (Bioinformatics)
Computational Biologist
Biostatistician
Genomics Data Scientist
Bioinformatics Research Scientist
Molecular Data Analyst
Proteomics Data Analyst
Genomic Data Analyst
Clinical Bioinformatics Specialist
Bioinformatics Software Developer
Machine Learning Engineer (Bioinformatics)
Bioinformatics Consultant
Biotechnologist
Biomedical Data Scientist
R Programmer (Bioinformatics)
Big Data Analyst (Life Sciences)
Research Associate (Genomics)
Systems Biologist
Healthcare Data Scientist

Trainers

Dwight Nuwan Fonseka: Dwight Nuwan Fonseka is a data scientist and AI researcher with extensive experience in computational biology, data engineering, and applied machine learning. As Head of Data Science at Plano Pte Ltd, he has led projects in predictive analytics, healthcare data modeling, and biomedical informatics. Dwight holds advanced certifications in data science, AI engineering, and analytics, with a strong focus on applying R, Python, and cloud-based platforms for research and enterprise applications. His background in data architecture and statistical modeling enables him to bridge biological data interpretation with computational efficiency.

In this course, Dwight guides learners through the fundamentals of bioinformatics data analysis using R and Bioconductor. His sessions emphasize workflow design, genomic data processing, and statistical interpretation for biological datasets. Learners gain practical experience in applying Bioconductor tools for sequence analysis, gene expression profiling, and biological network visualization. With his applied, research-driven approach, participants learn to harness R for advanced biological data analytics and scientific discovery.

Dr. Alfred Ang: Dr. Alfred Ang is a technology innovator, educator, and researcher with more than 25 years of experience in data analytics, computational systems, and applied engineering. He holds a PhD in Electrical Engineering from the National University of Singapore, an MEng from NTU, and an MBA from Universitas 21 Global. As Founder and Managing Director of Tertiary Infotech Pte. Ltd., Dr. Ang has led R&D initiatives and training programs in data science, AI, and bioinformatics applications, contributing to Singapore’s talent development in high-technology and research sectors. His academic and industry background uniquely positions him to bridge the gap between theoretical bioinformatics concepts and real-world implementation.

In this course, Dr. Ang provides learners with a deep understanding of data-driven bioinformatics analysis using R and Bioconductor. His sessions focus on data preprocessing, visualization, and statistical modeling for genomics and proteomics research. Learners gain a comprehensive view of how R-based analytical workflows support precision medicine, biomarker discovery, and computational biology innovation. Through his structured and research-oriented instruction, participants build the capability to conduct reproducible and insightful biological data analysis using modern R frameworks.

Customer Reviews (7)

Average Rating: 3.7/5 Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/15/2026)

Average Rating: 4.3/5 Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/15/2026)

Average Rating: 3.3/5 Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/15/2026)

will recommend Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

. (Posted on 2/2/2025)

will recommend Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

. (Posted on 1/31/2025)

might recommend Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

Course duration is too short to handle the heavy content (Posted on 2/28/2023)

might recommend Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

More exercises and case studies/practical examples. (Posted on 6/26/2022)

Write Your Own Review

You're reviewing: WSQ - Bioinformatics Data Analysis with R Bioconductor

How do you rate this product? *

	1 star	2 stars	3 stars	4 stars	5 stars
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

*Nickname
*Summary of Your Review
*Review
*Please type the letters below

$784.80 (GST-inclusive)

About Us

Tertiary Infotech Academy, established in 2012, is a leading skills-based training provider dedicated to supporting Singapore’s Industry 4.0 transformation. We are a registered Private Education Institute (PEI), offering Diploma and Advanced Certificate programs in Cyber Security and Artificial Intelligence.

As a strong advocate for professional and lifelong learning, we are a WSQ and IBF Approved Training Organisation (ATO). We also serve as an Authorized Training Partner for major global technology and certification bodies, including Microsoft, CompTIA, AWS, Pearson VUE, Autodesk, Linux Foundation.

In addition, our academy is both a Pearson VUE, Kryterion, PSI Authorized Test Centers enabling learners to access industry-recognized examinations in a convenient and professional environment.

Training Grants and Subsidies

WSQ: Company and Singaporeans/PR can apply WSQ 70-90% funding depending on eligibility
SkillsFuture Enterprise Credit (SFEC) - Eligible Singapore-registered companies can tap on $10000 SFEC to cover up to 90% of out-of-pocket expense
SkillsFuture Credit: All Singaporeans aged 25 and above can use their $500 SkillsFuture Credit from the government to pay for a wide range of approved skills-related courses.
IBF-STS Companies and Singaporeans/PR can apply IBF-STS 70-90% funding depending on eligibility
UTAP: NTUC members enjoy 50% subsidy for unfunded course fee support for up to $250 each year when you sign up for courses supported under UTAP
PSEA: Individual can pay using using their Post Secondary Education Account