Dear all,
there are still a few seats available for our upcoming online course, "FLOW CYTOMETRY ANALYSIS WITH R/BIOCONDUCTOR" (2nd edition) taking place from January 15th to January 18th, 2024.
In this course, you will learn the fundamentals of flow cytometry and why it is indispensable for understanding cell population composition. We will delve into the best practices for flow cytometry data analysis using R/Bioconductor, covering data preprocessing (compensation, transformation, and quality control), multi-dimensional cell population identification through clustering, and visualizing results in 2D. These skills are applicable to various cytometry techniques, including flow, mass, and spectral.
This course is tailored for anyone interested in analyzing biological samples with single-cell flow cytometry. No prior background in flow cytometry or R/Bioconductor is required, as we will provide a brief introduction.
By the end of this course, you will:
- Gain a deep understanding of flow cytometry and its analytical purpose.
- Be able to set up the infrastructure for R and write basic data analytic scripts.
- Describe and execute each step in the flow cytometry data analytics pipeline using R/Bioconductor.
- Be comfortable interpreting and drawing conclusions from flow cytometry data analytics results.
For more information about the course, please check it out: https://www.physalia-courses.org/cou...flow-cytometry
For the full list of our courses and workshops, please check it out: https://www.physalia-courses.org/courses-workshops
Best regards,
Carlo
--------------------
Carlo Pecoraro, Ph.D
Physalia-courses DIRECTOR
[email protected]
there are still a few seats available for our upcoming online course, "FLOW CYTOMETRY ANALYSIS WITH R/BIOCONDUCTOR" (2nd edition) taking place from January 15th to January 18th, 2024.
In this course, you will learn the fundamentals of flow cytometry and why it is indispensable for understanding cell population composition. We will delve into the best practices for flow cytometry data analysis using R/Bioconductor, covering data preprocessing (compensation, transformation, and quality control), multi-dimensional cell population identification through clustering, and visualizing results in 2D. These skills are applicable to various cytometry techniques, including flow, mass, and spectral.
This course is tailored for anyone interested in analyzing biological samples with single-cell flow cytometry. No prior background in flow cytometry or R/Bioconductor is required, as we will provide a brief introduction.
By the end of this course, you will:
- Gain a deep understanding of flow cytometry and its analytical purpose.
- Be able to set up the infrastructure for R and write basic data analytic scripts.
- Describe and execute each step in the flow cytometry data analytics pipeline using R/Bioconductor.
- Be comfortable interpreting and drawing conclusions from flow cytometry data analytics results.
For more information about the course, please check it out: https://www.physalia-courses.org/cou...flow-cytometry
For the full list of our courses and workshops, please check it out: https://www.physalia-courses.org/courses-workshops
Best regards,
Carlo
--------------------
Carlo Pecoraro, Ph.D
Physalia-courses DIRECTOR
[email protected]