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VERSION:2.0
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:STANDARD
DTSTART:20241103T020000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
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BEGIN:DAYLIGHT
DTSTART:20250309T020000
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
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BEGIN:VEVENT
DESCRIPTION:Registration is required\, visit RSVP link above for more even
 t information. Registration required* and In-Person Summary: In this sess
 ion\, we will walk you through intermediate RNA-seq differential expressi
 on analysis in R using the popular DESeq2 package. You will learn the sta
 tistical foundations of experimental design and model specification in DE
 Seq2 so you can obtain and interpret results that are robust and biologic
 ally meaningful for your study. Participants should be comfortable with R
  basics (e.g.\, working with data frames and factors). We will be using P
 ositron to run our code. You will learn how to: Connect research question
  with metadata file Assemble a DESeq2 dataset Design and explore a model 
 matrix Perform basic data visualization (e.g. PCA plot\, MA plot) Save an
 d organize processed data files and results Requirements: Basic knowledge
  of R programming language You may use your favorite IDE but if you would
  like to use Positron please be sure to have it installed before the clas
 s (please see registration link for more information and to download).\n\
 nSpeakers:\nSofia Fertuzinhos\; Ted Ellsworth\n\nAdmission:\nFree\n\nDeta
 ils URL:\nhttps://medicine.yale.edu/event/getting-deseq2-right-experiment
 al-design-and-the-stats-that-power-differential-expression/\n
DTEND;TZID=America/New_York:20261012T120000
DTSTAMP:20261006T183301Z
DTSTART;TZID=America/New_York:20261012T100000
GEO:41.303333;-72.933741
LOCATION:Harvey Cushing/John Hay Whitney Medical Library \, 111\, 333 Ceda
 r Street\, New Haven\, CT\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:Getting DESeq2 right: Experimental Design and the Stats that Power
  Differential Expression.
UID:a945d9f4-34d6-4cda-a8c4-2b702fae9837
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