The following 121 words could not be found in the dictionary of 615 words (including 615 LocalSpellingWords) and are highlighted below:

abline   Aliquots   aliquots   an   and   at   attachment   available   be   before   by   calculate   can   Category   cells   coef   colnames   columns   cran   culture   Curve   curve   D600   density   derived   determine   diluted   dilution   Doubling   doubling   during   environment   examine   example   exponential   exponentially   factor   figures   file   find   Find   fit   following   from   function   gdata   given   growing   grown   growth   Growth   header   hint   in   innoculation   input   into   line   linear   liquid   lm   log   main   measured   minutes   modeling   names   of   optical   pastoris   pdf   perform   phase   phenotype   Pichia   plot   portion   post   project   quantify   range   rate   read   Read   reading   readings   regression   resulting   sep   slope   spectrophotometer   surpassed   table   taken   text   The   the   they   this   Thus   Time   time   timecourse   times   to   Tutorial   use   used   useful   Using   using   various   versus   was   were   When   which   with   xlab   yeast   ylab  

Clear message

Using R to examine a Growth Curve and calculate Doubling Time

The doubling time of cells growing exponentially in liquid culture can be a useful phenotype to quantify. A plot of the log of the OD (optical density) versus time can be used to determine growth rate. The slope of the fit line is the growth rate: k and the doubling time is given by: log(2)/k. The following is an example using the R environment to plot and fit a growth curve and find doubling time.

Pichia pastoris was grown in liquid culture. Aliquots were taken at various times post-innoculation, and measured by OD600. When the aliquots surpassed the linear range of the spectrophotometer they were diluted before reading. Thus the input data file has 5 columns: time post-innoculation, minutes, dilution factor, OD reading, derived OD.

yeast_timecourse.txt

R_growth_curve_example.pdf (this example with figures)

1.) Read the data into R

# read the data into R from a tab-delimited text file
gdata <- read.table(file="yeast_timecourse.txt", sep="\t", header=T)

# what are the column names?
colnames(gdata)

2.) plot the derived OD600 readings as a function of time

# columns of interest are:
# minutes (2nd column) and dOD600 (5th column, derived OD600)
# examine a plot of OD versus time
plot(gdata[,2], gdata[,5])

# could also use column names to specify columns:
plot(gdata[,"minutes"], gdata[,"dOD600"])

# make the plot look nicer
plot(gdata[,2], gdata[,5], main="OD versus Time", xlab="minutes", ylab="OD600")

3.) Find the portion of the curve which is linear during exponential phase growth

(hint: plot log of OD versus time) 

# since this is a growth curve, we want to plot the log
# of the OD
plot(gdata[,2], log(gdata[,5]), main="OD versus Time", xlab="minutes", ylab="log(OD600)")

# pick the part of the curve that looks linear
# maybe points 3 through 6?

4.) use the linear modeling function to to perform regression

The resulting slope can be used to find the yeast doubling time. 

# use lm() to fit this part of the curve
# fit y as a function of x (or OD as a function of time)
# but only use the points of interest
lm(log(gdata[3:6,"dOD600"]) ~ gdata[3:6,"minutes"])

# save the linear fit to an object called "fit"
fit <- lm(log(gdata[3:6,"dOD600"]) ~ gdata[3:6,"minutes"])

# give the fit to the abline() function to draw a line on the plot
abline(fit)

# the fit object is kind of complicated
# it's got lots of stuff in it
names(fit)

# however the slope of the line can be found by looking
# at the second coefficient
fit$coef[2]

# use the slope to calculate the doubling time of the
# cells during their exponential growth phase
# the formula is log(2)/k where k is the growth rate (slope from the curve)
log(2)/fit$coef[2]

# write the doubling time on the curve
text(800,-2,"Doubling Time = 130 minutes")

R is available from CRAN

CategoryR CategoryRTutorial

R GrowthCurve (last edited 2007-05-02 16:31:16 by ChrisSeidel)