RNA-Seq Analysis
RNA-Seq analysis training ? live online course covering experiment design,
data QC, alignment, gene expression, DESeq2 differential expression, PCA,
visualisation, and functional analysis.
*ONLY 7 PLACES LEFT!*
https://prstats.org/course/rna-seq-analysis-rnaa01/
Join our four-day live online workshop: *RNA-Seq Analysis (RNAA01)*. If
you?re working with RNA-Seq or planning to generate bulk transcriptome
data, and you want to take your analysis from raw reads through to
biological insight, this is the course for you.
*What you will learn*
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How to design a robust RNA-Seq experiment and avoid common pitfalls.
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How to perform quality control on raw RNA-Seq data, align reads, and
assess alignment quality.
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How to quantify gene expression and apply the widely-used DESeq2
workflow for differential expression analysis.
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How to visualise high-throughput data using principal component analysis
(PCA), volcano plots, MA plots and other techniques.
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How to perform functional interpretation of differential expression
results, turning numbers into biological insight.
*Who should attend*
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Researchers, postgraduate students and industry professionals working
with bulk RNA-Seq data.
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Anyone who has basic experience with R, RStudio and the fundamentals of
molecular biology or transcriptomics.
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Those who want to move from raw sequence data to actionable biological
conclusions with confidence.
*Course format*
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Four days of live online sessions (approximately 3? hours each day) in a
UK / Western European time zone.
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Interactive lectures, hands-on practical exercises and dedicated
discussion time.
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Course materials, code and datasets will be provided, and participants
are encouraged to bring their own data for discussion when possible.
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Recordings of sessions available after each day for participants across
different time zones.
*Why this course stands out*
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It offers an end-to-end workflow from design through QC, alignment,
differential expression and functional analysis ? designed specifically for
researchers working in transcriptomics.
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It emphasises not just how to run the tools, but how to interpret
results, understand the assumptions and recognise where things can go wrong.
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Designed by experienced bioinformaticians, the course balances theory,
practice and discussion in an accessible live-online format.
*How to register / next steps*
Visit the PR Stats website for full course details, upcoming dates and
registration information. Early registration is advisable, as places may be
limited. For any questions about suitability, prerequisites or logistics,
please contact the course organisers.
https://prstats.org/course/rna-seq-analysis-rnaa01/
Oliver Hooker PhD.
PR stats
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