https://www.seqanswers.com/ en Sat, 29 Aug 2026 15:18:15 GMT vBulletin 60 https://www.seqanswers.com/images/misc/rss.png https://www.seqanswers.com/ https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327661-accessible-bioinformatics-for-windows-users-–-livestream-seminar Tue, 25 Aug 2026 05:53:58 GMT Hi everyone Instats is excited to offer a 5-day seminar, Accessible Bioinformatics for Windows Users...
Instats is excited to offer a 5-day seminar, Accessible Bioinformatics for Windows Users, livestreaming October 2nd - 6th and led by Andres Zhou Tsang from Adelaide University. Because many bioinformatics tools are designed for Linux while Windows remains the most common operating system on personal and institutional computers, this workshop provides a practical pathway for researchers who need to run Linux-based bioinformatics workflows without investing in a dedicated Linux machine or relying on cloud services. Participants will learn to install and configure a Windows-based bioinformatics environment using Windows Subsystem for Linux (WSL), while working with tools such as conda, Notepad++, R, Python, IGV, and FastQC to process, visualize, and assess sequencing data. Through hands-on sessions covering FASTA formats, basecalling, genome assembly, sequence alignment, RNA-seq, gene annotation, and differential expression analysis, this seminar equips Windows users with accessible, practical skills for conducting common bioinformatics analyses.

Sign up today to secure your spot, and feel free to share this opportunity with colleagues and students who might benefit!


Best wishes

Michael Zyphur
Professor and Director
Instats | instats.org​]]> Bioinformatics Instats https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327661-accessible-bioinformatics-for-windows-users-–-livestream-seminar https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327660-single-cell-data-analysis-3-0-–-livestream-seminar Tue, 25 Aug 2026 05:40:31 GMT Hi everyone Instats is excited to offer a 1-day seminar, Single Cell Data Analysis 3.0 (https://instats.org/seminar/single-cell-data-analysis-30),...
Instats is excited to offer a 1-day seminar, Single Cell Data Analysis 3.0, livestreaming September 9th and led by Nikolay Oskolkov from Lund University. As single-cell methods become central to biological and health research, mastering computational approaches for single-cell RNA sequencing data is essential for investigating cellular heterogeneity and advancing discovery in areas such as cancer research, developmental biology, and immunology. In this workshop, you’ll gain hands-on experience with state-of-the-art workflows for preprocessing, quality control, normalization, dimensionality reduction, clustering, visualization, differential expression analysis, and dataset integration using key tools in both R and Python. Nikolay Oskolkov’s practical approach emphasizes widely used frameworks such as Seurat and Scanpy, helping PhD students, academic researchers, and professionals develop the skills needed to move from raw single-cell data to meaningful biological interpretation.

Sign up today to secure your spot, and feel free to share this opportunity with colleagues and students who might benefit!


Best wishes

Michael Zyphur
Professor and Director
Instats | instats.org​​]]> Bioinformatics Instats https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327660-single-cell-data-analysis-3-0-–-livestream-seminar https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327658-machine-learning-for-computational-biology-–-livestream-seminar Tue, 25 Aug 2026 05:24:32 GMT Hi everyone Instats is excited to offer a 1-day seminar, Machine Learning for Computational Biology...
Instats is excited to offer a 1-day seminar, Machine Learning for Computational Biology, livestreaming September 8th and led by Nikolay Oskolkov from Lund University. As biological data continue to grow in scale and complexity, machine learning has become essential for analyzing and interpreting data in biostatistics, genetics, bioinformatics, ecology, genomics, and related fields. This workshop introduces key machine learning approaches for computational biology, including neural networks, random forests, k-means clustering, Gaussian Mixture Models, Markov Chain Monte Carlo methods, and autoencoders, while emphasizing practical implementation in R and Python. Through hands-on coding sessions and real-world case studies, participants will learn to build algorithms from scratch, troubleshoot and optimize models, and apply machine learning methods confidently to their own biological research questions.

Sign up today to secure your spot, and feel free to share this opportunity with colleagues and students who might benefit!



Best wishes

Michael Zyphur
Professor and Director
Instats | instats.org]]> Bioinformatics Instats https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327658-machine-learning-for-computational-biology-–-livestream-seminar https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327654-ancient-environmental-metagenomics-aemg01-–-live-online-bioinformatics-course Thu, 20 Aug 2026 12:42:39 GMT Ancient Environmental Metagenomics (AEMG01) – Live Online Bioinformatics Course ... Ancient Environmental Metagenomics (AEMG01) – Live Online Bioinformatics Course

https://prstats.org/course/ancient-e...nomics-aemg01/

Learn how to analyse ancient environmental DNA (aeDNA) and metagenomic sequencing data using modern bioinformatics workflows for quality control, taxonomic profiling, authentication, decontamination, assembly, and genomic analysis.

Ancient environmental DNA recovered from sediments, ice cores, archaeological deposits, and other environmental archives provides unique opportunities to reconstruct past ecosystems, biodiversity, and environmental change.

However, these datasets present substantial computational challenges, including highly fragmented DNA, low sequencing coverage, complex mixtures of organisms, incomplete reference databases, post-mortem DNA damage, and modern contamination.

This practical course provides hands-on training in the bioinformatics methods needed to move from raw ancient environmental sequencing reads to authenticated taxonomic and genomic results.

WHAT YOU'LL GAIN

• Understanding of ancient environmental DNA and metagenomic sequencing workflows
• Practical experience with quality control, adapter trimming, host removal, and read processing using fastp and cutadapt
• Taxonomic profiling using Kraken and sourmash
• Skills in constructing and optimising reference databases for mammals, plants, microbes, fungi, and invertebrates
• Methods for authenticating ancient environmental DNA and taxonomic assignments
• Experience using mapDamage and PMDtools to assess post-mortem DNA damage
• Strategies for detecting and removing contamination using decontam, negative controls, and Recentrifuge
• Experience with metagenome de novo assembly and authentication of assembled contigs
• Practical use of the aeMeta workflow for ancient environmental metagenomics
• Application of PCA and UMAP to population genomic and ancient environmental datasets

COURSE FORMAT

• 25 hours of training
• Live online
• Hands-on bioinformatics using real-world datasets
• Practical exercises throughout
• Strong focus on complete, research-ready workflows

WHO IS THIS COURSE FOR?

• Bioinformaticians and computational biologists
• Ancient DNA and palaeogenomics researchers
• Metagenomics and environmental DNA researchers
• Evolutionary biologists and population genomic researchers
• Ecologists and palaeoecologists
• Microbiologists
• PhD students and researchers working with ancient or environmental sequencing data

WHY TAKE THIS COURSE?

Ancient environmental metagenomic data require specialised bioinformatics approaches that go beyond conventional metagenomic analysis.

Researchers must distinguish authentic ancient DNA from modern contamination, account for post-mortem damage and fragmented sequences, construct appropriate reference databases, and validate taxonomic assignments before drawing biological conclusions.

This course provides practical experience across the complete computational workflow, giving participants the skills needed to process, authenticate, analyse, and interpret ancient environmental metagenomic datasets.

COURSE DETAILS

Course dates: 23–27 November 2026

Duration: 25 hours

Format: Live online

Registration: £400

LEARN MORE & ENROL

https://prstats.org/course/ancient-e...nomics-aemg01/

QUESTIONS?

Email: oliver@prstats.org
]]> Bioinformatics PR Stats https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327654-ancient-environmental-metagenomics-aemg01-–-live-online-bioinformatics-course https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327653-genome-wide-association-studies-gwas-live-online-course Thu, 20 Aug 2026 10:49:29 GMT Genome-Wide Association Studies (GWAS) for Evolutionary Biology (GWAS01) – Live Online Course ... Genome-Wide Association Studies (GWAS) for Evolutionary Biology (GWAS01) – Live Online Course

https://prstats.org/course/genome-wi...iology-gwas01/

Learn how to perform genome-wide association studies (GWAS), from genomic data processing and quality control through to association testing, population structure correction, meta-analysis, visualisation, and polygenic prediction.

Genome-wide association studies are a cornerstone of modern genetics and genomics, enabling researchers to identify genetic variants associated with complex traits and investigate the genetic architecture of phenotypic variation.

This practical course provides hands-on training in complete GWAS workflows using widely adopted bioinformatics and statistical tools, including PLINK, SNPTEST, GATK, GWAMA, METAL, and LocusZoom.

WHAT YOU'LL GAIN

• Understanding of genetic variation and the principles of genome-wide association studies
• Practical experience with genotype quality control and filtering
• Skills in genotype phasing and imputation
• Association testing using PLINK and SNPTEST
• Genomic data processing and variant calling using GATK workflows
• Population structure analysis and correction using PCA
• GWAS meta-analysis using GWAMA and METAL
• Visualisation of association results using Manhattan plots and LocusZoom
• Construction and validation of polygenic risk scores
• Understanding of missing heritability and current approaches to complex trait genetics

COURSE FORMAT

• 5 days, 5 hours per day
• Live, instructor-led online training
• Hands-on genomic and bioinformatics analysis
• Practical exercises using real-world datasets
• Strong focus on complete, research-ready GWAS workflows

WHO IS THIS COURSE FOR?

• Bioinformaticians and computational biologists
• Population geneticists and evolutionary genomic researchers
• Researchers working with genotype and sequencing datasets
• Quantitative and statistical geneticists
• PhD students and researchers interested in GWAS and complex trait genetics

WHY TAKE THIS COURSE?

GWAS requires the integration of genomic data processing, rigorous quality control, population structure analysis, statistical association testing, and biological interpretation.

This course provides practical experience across the complete workflow, helping participants move from raw genomic data through variant processing and association testing to the interpretation and visualisation of genome-wide results.

COURSE DETAILS

Course dates: 9–13 November 2026

Duration: 25 hours

Format: Live online

Registration: £400

LEARN MORE & ENROL

https://prstats.org/course/genome-wi...iology-gwas01/

QUESTIONS?

Email: oliver@prstats.org]]> Bioinformatics PR Stats https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327653-genome-wide-association-studies-gwas-live-online-course https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327652-metagenomic-data-analysis-of-microbial-communities-mgmc01-–-live-online-course Thu, 20 Aug 2026 10:39:14 GMT Metagenomic Data Analysis of Microbial Communities (MGMC01) – Live Online Course ... Metagenomic Data Analysis of Microbial Communities (MGMC01) – Live Online Course

https://prstats.org/course/metagenom...nities-mgmc01/

Learn how to analyse shotgun metagenomic sequencing data using modern bioinformatics workflows for taxonomic profiling, functional analysis, and characterisation of complex microbial communities.

Shotgun metagenomics provides powerful approaches for investigating microbial communities directly from sequencing data, but analysing these datasets presents substantial computational and bioinformatic challenges.

This live online course provides practical, hands-on training in metagenomic data analysis, taking participants through the workflow from sequencing data processing and quality control to taxonomic and functional profiling and biological interpretation.

WHAT YOU'LL GAIN

• Understanding of shotgun metagenomic sequencing and analysis workflows
• Practical experience processing metagenomic sequencing datasets
• Skills in quality control and preparation of sequencing data
• Taxonomic profiling and characterisation of microbial communities
• Functional profiling of microbial genes and pathways
• Analysis and visualisation of microbial diversity and community composition
• Experience interpreting metagenomic outputs and biological patterns
• Confidence applying metagenomic workflows to your own sequencing datasets

COURSE FORMAT

• 5 days, 5 hours per day
• Live, instructor-led online training
• Hands-on bioinformatics and data analysis
• Practical exercises using metagenomic datasets
• Strong focus on applied, research-ready workflows

WHO IS THIS COURSE FOR?

• Bioinformaticians and computational biologists
• Metagenomics and microbiome researchers
• Genomics and NGS researchers
• Microbial ecologists and environmental microbiologists
• Researchers working with environmental or host-associated microbiomes
• PhD students and researchers wanting practical experience analysing shotgun metagenomic sequencing data

WHY TAKE THIS COURSE?

Metagenomic sequencing generates complex datasets requiring specialised computational approaches for quality control, taxonomic classification, functional profiling, diversity analysis, and downstream interpretation.

This course provides practical experience with the bioinformatics workflows needed to move from shotgun sequencing data to biologically meaningful descriptions of microbial community composition and functional potential.

COURSE DETAILS

Course dates: 26–30 October 2026

Duration: 5 days, 5 hours per day

Format: Live online

Registration: £400

LEARN MORE & ENROL

https://prstats.org/course/metagenom...nities-mgmc01/

QUESTIONS?

Email: oliver@prstats.org]]> Bioinformatics PR Stats https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327652-metagenomic-data-analysis-of-microbial-communities-mgmc01-–-live-online-course https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327639-single-cell-rna-seq-analysis-scrn03-–-live-online-course Thu, 06 Aug 2026 19:59:14 GMT Single-cell RNA-Seq Analysis (SCRN03) – Live Online Course https://prstats.org/course/single-cell-rna-seq-analysis-scrn03/ Delivered by... Single-cell RNA-Seq Analysis (SCRN03) – Live Online Course

https://prstats.org/course/single-ce...alysis-scrn03/

Delivered by experienced bioinformaticians with expertise in single-cell transcriptomics, RNA sequencing, and computational biology.

Learn how to analyse single-cell RNA-Seq (scRNA-seq) data in R using Seurat, covering modern workflows for quality control, normalisation, clustering, dimensionality reduction, integration, differential expression, and cell type annotation.

Single-cell RNA sequencing has transformed transcriptomics by enabling gene expression to be measured at cellular resolution. This course provides practical, hands-on training in analysing scRNA-seq datasets using Seurat, from raw count matrices through to biological interpretation. Participants will work through complete analysis pipelines widely used in genomics and bioinformatics research. What you'll gain

• Understanding of single-cell RNA-Seq technologies and experimental design
• Practical experience using Seurat for end-to-end scRNA-seq analysis
• Skills in quality control, filtering, normalisation, feature selection, clustering, and dimensionality reduction
• Experience performing differential expression analysis, dataset integration, and cell type annotation
• Confidence interpreting and visualising single-cell transcriptomic datasets

Course format

• Live, instructor-led online training
• Hands-on coding in R using Seurat
• Real single-cell RNA-Seq datasets
• Interactive practical exercises throughout
• Research-focused workflows suitable for publication-quality analyses

Who is this course for?

• Bioinformaticians
• Computational biologists
• Genomics researchers
• RNA-Seq users moving into single-cell analysis
• PhD students and researchers working with sequencing data

Why take this course?

Single-cell RNA-Seq has rapidly become a standard technology across genomics, with Seurat established as one of the most widely used analysis frameworks. Researchers increasingly require robust computational skills to process large-scale single-cell datasets, integrate experiments, identify cell populations, and extract biologically meaningful insights.

This course provides practical experience with the complete Seurat workflow, enabling participants to confidently analyse their own single-cell RNA-Seq datasets using current best practices employed across academia and industry. Learn more & enrol

https://prstats.org/course/single-ce...alysis-scrn03/

Questions?

Email: oliver@prstats.org]]> Bioinformatics PR Stats https://www.seqanswers.com/forum/bioinformatics/bioinformatics-aa/327639-single-cell-rna-seq-analysis-scrn03-–-live-online-course