Closed Physalia86 closed 1 year ago
kozo2
commented
1 year ago @Physalia86 Thank you for sharing the information! I added your event to the "Bioconductor Events" Google Calendar. The website (bioconductor.org) itself (HTML other than embedded Google Calendar) will be updated later.
kozo2
commented
1 year ago @Physalia86 Sorry for the late reply. The event is already on the https://bioconductor.org . Thank you for sharing your event with us.
Physalia86
commented
1 year ago Hi Kozo,
many thanks for this.
Happy New Year, Carlo
-----Original Message----- From: "Kozo Nishida" @.> Sent: Tuesday, January 3, 2023 2:49pm To: "BioconductorBoards/CABWorkingGroups" @.> Cc: "Physalia86" @.>, "Mention" @.> Subject: Re: [BioconductorBoards/CABWorkingGroups] FLOW CYTOMETRY ANALYSIS WITH R/BIOCONDUCTOR course (Issue #47)
@Physalia86 Sorry for the late reply. The event is already on the https://bioconductor.org . Thank you for sharing your event with us. — Reply to this email directly, view it on GitHub , or unsubscribe . You are receiving this because you were mentioned.Message ID: @.***>
Type
course
Description
COURSE OVERVIEW This course introduces what flow cytometry is and why we use it to analyze cell population composition in biological samples. We will learn about best practices for how to analyze flow cytometry data using R/Bioconductor. Said practices include: preprocessing of the data (compensation, transformation, and quality control), multi-dimensional cell population identification via clustering, and visualizing the results in 2D. These tools can be applied to all types of cytometry including flow, mass, and spectral.
TARGET AUDIENCE AND ASSUMED BACKGROUND This course is created for anyone interested in analyzing biological samples with single-cell flow cytometry. Background in flow cytometry and R/Bioconductor is not necessary as we will go over a short introduction to them. However, experience with programming will help greatl
LEARNING OUTCOMES 1- Understand the flow cytometry machinery and its analytical purpose.
2- Be able to set up the infrastructure for and write basic data analytic scripts in R.
3- Describe and execute each step in the flow cytometry data analytics pipeline in R/Bioconductor.
4- Be comfortable with interpreting and eliciting conclusions from the results of the flow cytometry data analytics pipeline.
Location
online
Website
https://www.physalia-courses.org/courses-workshops/flow-cytometry/
Start date and time
January 16th-4-8 pm Berlin time
End date and time
January 19th--4-8 pm Berlin time
Time zone
Berlin time
Contact Details
info@physalia-courses.org
Registration details (if applicable)
Registration details
Sponsor or Organization
Sponsor or organization
Comment field
No response
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