-
使用
ImageJ
分析
Western Blot
2011-11-29 20:13:54|
分类：
Bioinformatics |
标签：
|
字号大中小
订阅
Analyzing gels and western blots with
ImageJ
2011-07-29 18:02
来源：
丁香园
点击次数：
496
关键词：
ImageJ
数据分析
分享到：
收藏夹
腾讯微博
新浪微博
开心网
The
following
information
is
an
updated
version
of
a
method
for
using
ImageJ
to
analyze
western
blots
from
a
now-
deprecated
older
page.
Don’t
use
the
altern
ate
methods
discussed
on
the
old
page,
as
they
are
subject
to
way
too
much
user
bias.
A
pdf
copy
of
this
page
is
available.
ImageJ
(
/ij/
)
can
be
used
to
compare
the
density
(aka
intensity)
of
bands
on
an
agar
gel
or
western
blot.
This
tutorial
assumes
that
you
have
carried
your
gel
or
blot
through
the
visualization
step,
so
that
you
have
a
digital
image
of
your
gel
in .tif, .jpg,
.png
or
other
image
formats
(.tif
would
be
the
preferred
format
to
retain
the
maximum
amount
of
info
rmation
in
the
original
image).
If
you
are
scanning
x-ray
film
on
a
flatbed
scanner,
make
sure
yo
u
use
a
scanner
with
the
ability
to
scan
transparencies
(i.e.
film).
See
the
references
at
the
end
of
this
tutorial
for
a
discussion
of
the
various
ways
that
you
can
screw
this
step
up.
The
method
outlined
here
uses
the
Gel
Analysis
method
outlined
in
the
ImageJ
documentation:
Gel
Analysis.
You
may
prefer
to
use
it
instead
of
the
methods
I
outline
below.
There
should
be
very
little
difference
between
the
results
obtained
from
the
various
methods.
This
version
of
the
t
utorial
was
created
using
ImageJ
1.42q
on
a
Windows
7
64-bit
install.
1.
Open
the
image
file
using
File>Open
in
ImageJ.
2.
The
gel
analysis
routine
requires
the
image
to
be
a
gray-scale
image.
The
simplest
method
to
convert
to
grayscale
is
to
go
to
Image>Type>8-bit.
Your
image
should
look
like
Figure
1.
3.
Choose
the
Rectangular
Selections
tool
from
the
ImageJ
toolbar.
Draw
a
rectangle
around
the
first
lane.
ImageJ
assumes
that
your
lanes
run
vertically
(so
individual
bands
are
horizontal),
so
your
rectangle
should
be
tall
and
narrow
to
enclose
a
single
lane.
If
you
draw
a
rectangle
that
is
short
and
wide,
ImageJ
will
switch
to
assuming
the
lanes
run
horizontally
(individual
bands
are
vertical),
leading
to
much
confusion.
4.
After
drawing
the
rectangle
over
your
first
lane,
press
the
1
key
or
go
to
Analyze>Gels>Select
First
Lane
to
set
the
rectangle
in
place.
The
1st
lane
will
now
be
highlighted
and
have
a
1
in
t
he
middle
of
it.
5.
Use
your
mouse
to
click
and
hold
in
the
middle
of
the
rectangle
on
the
1st
lane
and
drag
it
over
to
the
next
lane.
You
can
also
use
the
arrow
keys
to
move
the
rectangle,
though
this
is
sl
ower.
Center
the
rectangle
over
the
lane
left-to-
right,
but
don’t
worry
ab
out
lining
it
up
perfectly
o
n
the
same
vertical
axis.
Image-J
will
automatically
align
the
rectangle
on
the
same
vertical
axis
as
the
1st
rectangle
in
the
next
step.
6.
Press
2
or
go
to
Analyze>Gels>Select
Next
Lane
to
set
the
rectangle
in
place
over
the
2nd
l
ane.
A
2
will
appear
in
the
lane
when
the
rectangle
is
placed.
7.
Repeat
Steps
5
+
6
for
each
subsequent
lane
on
the
gel,
pressing
2
each
time
to
set
the
re
ctangle
in
place
(Figure
3).
8.
After
you
have
set
the
rectangle
in
place
on
the
last
lane
(by
pressing
2),
press
3,
or
go
to
Analyze>Gels>Plot
Lanes
to
draw
a
profile
plot
of
each
lane.
9.
The
profile
plot
represents
the
relative
density
of
the
contents
of
the
rectangle
over
each
lane.
The
rectangles
are
arranged
top
to
bottom
on
the
profile
plot.
In
the
example
western
blot
imag
e,
the
peaks
in
the
profile
plot
(Figure
4)
correspond
to
the
dark
bands
in
the
original
image
(Fi
gure
3).
Because
there
were
four
lanes
selected,
there
are
four
sections
in
the
profile
plot.
Highe
r
peaks
represent
darker
bands.
Wider
peaks
represent
bands
that
cover
a
wider
size
range
on
t
he
original
gel.
10.
Images
of
real
gels
or
western
blots
will
always
have
some
background
signal,
so
the
peaks
don’t
reach
down
to
the
baseline
of
the
profile
plot.
Figure
5
shows
a
peak
from
a
real
blot
wh
ere
there
was
some
background
noise,
so
the
peak
appears
to
float
above
the
baseline
of
the
p
rofile
plot.
It
will
be
necessary
to
close
off
the
peak
so
that
we
can
measure
its
size.
11.
Choose
the
Straight
Line
selection
tool
from
the
ImageJ
toolbar
(Figure
6).
For
each
peak
yo
u
want
to
analyze
in
the
profile
plot,
draw
a
line
across
the
base
of
the
peak
to
enclose
the
pe
ak
(Figure
5).
This
step
requires
some
subjective
judgment
on
your
part
to
decide
where
the
pea
k
ends
and
the
background
noise
begins.
12.
Note
that
if
you
have
many
lanes
highlighted,
the
later
lanes
will
be
hidden
at
the
bottom
of
the
profile
plot
window.
To
see
these
lanes,
press
and
hold
the
space
bar,
and
use
the
mouse
to
click
and
drag
the
profile
plot
upwards.
13.
When
each
peak
has
been
closed
off
at
the
base
with
the
Straight
Line
selection
tool,
select
the
Wand
tool
from
the
ImageJ
toolbar
(Figure
8).
14.
Using
the
spacebar
and
mouse,
drag
the
profile
plot
back
down
until
you
are
back
at
the
fir
st
lane.
With
the
Wand
tool,
click
inside
the
peak
(Figure
9).
Repeat
this
for
each
peak
as
you
go
down
the
profile
plot.
For
each
peak
that
you
highlight,
measurements
should
pop
up
in
the
Results
window
that
appears.
15.
When
all
of
the
peaks
have
been
highlighted,
go
to
Analyze>Gels>Label
Peaks.
This
labels
each
peak
with
its
size,
expressed
as
a
percentage
of
the
total
size
of
all
of
the
highlighted
pea
ks.
16.
The
values
from
the
Results
window
(Figure
10)
can
be
moved
to
a
spreadsheet
program
by
selecting
Edit>Copy
All
in
the
Results
window.
Paste
the
values
into
a
spreadsheet.
Note:
If
you
accidentally
click
in
the
wrong
place
with
the
Wand,
the
program
still
records
that
cli
cked
area
as
a
peak,
and
it
will
factor
into
the
total
area
used
to
calculate
the
percentage
value
s.
Obviously
this
will
skew
your
results
if
you
click
in
areas
that
aren’t
peaks.
If
you
do
happen
t
o
click
in
the
wrong
place,
simple
go
to
Analyze>Gel>Label
Peaks
to
plot
the
current
results,
whi
ch
displays
the
incorrect
values,
but
more
importantly
resets
the
counter
for
the
Results
window.
Go
back
to
the
profile
plot
and
begin
clicking
inside
the
peaks
again,
starting
with
the
1st
peak
of
interest.
The
Results
window
should
clear
and
begin
showing
your
new
values.
When
you’re
s
ure
you’ve
click
in
all
of
the
correct
peaks
without
accidentally
clicking
in
any
wrong
areas,
you
can
go
back
to
Analyze>Gels>Label
Peaks
and
get
the
correct
results.
Data analysis
With your data
pasted into a spreadsheet, you can now calculate
the relative density of the peaks. As a
reminder, the values calculated by
ImageJ are essentially arbitrary numbers, they
only have meaning
within the context of
the set of peaks that you selected on the
single gel image you’ve been working
on.
They do not have units of μg of
protein or any other real
-world units
that you can think of. The normal
procedure is to express the density of
the selected bands relative to some standard band
that you also
selected during this
process.
1. Place your data in a
spreadsheet. One of the peaks should be your
standard. In this example we’ll use
the
1st peak as the standard.
2. In a new
column next to the Percent column, divide the
Percent value for each sample by the Percent
value for the standard (the 1st peak in
this case, 26.666).
3. The resulting
column of values is a measure of the relative
density of each peak, compared to the
standard, which will obviously have a
relative density of 1.
4.
In this example, the 2nd lane has a higher
Relative Density (1.86), which corresponds well
with the
size and darkness of that band
in the original image (Figure 1). Recall that
these data are for the upper
row of
bands on the original western blot image.
5. If you want to compare the density
of samples on multiple gels or blots, you will
need to use the same
standard sample on
every gel to provide a common reference when you
calculate Relative Density
values. See
the sections below for more detailed discussion of
these requirements.
6. In order to test
for significant differences between treatments in
an experiment, all of your gels or blots
will need to be scanned and quantified
using this method, and the values will be
expressed in terms of
Relative Density,
or you can treat Relative Density as a fold-change
value (i.e. a Relative Density
difference of 2 between a control and
treatment would indicate a 2-fold change in
expression). If you will
be using
analysis of variance techniques to test your data,
you may need to ensure that your Relative
Density values are normally distributed
and that there is homogeneity of variance among
the different
treatments.
7.
It should be noted here that some researchers make
the extra effort to include a set of serial
dilutions
of a known standard on each
blot. Using the serial dilution curve and the
quantification techniques
outlined
above, it should be possible to express your
sample bands in terms of picograms or nanograms
of protein.
A more involved
example using loading-controls.
We’ll
use Figure 12 as a representative western blot. On
this blot, we will pretend that we loaded four
replicate samples of protein (four
pipette loads out of the same vial of homogenate),
so we expect the
densities in each lane
to be equivalent. The upper row of bars will
represent our protein of interest. The
lower set of bars will represent our
loading-control protein, which is meant to ensure
that an equal
amount of total protein
was loaded in each lane. This loading-control
protein is a protein that is
presumably
expressed at a constant level regardless of the
treatment applied to the original organisms,
such as actin (though many people will
question the assertion that actin will be
expressed equivalently
across
treatments).
Looking at
Figure 12, we had hoped to load equivalent amounts
of total protein in each lane, but after
running the western blot, the size and
intensity of the lower bars in each lane varies
quite a lot. The two
left lanes appear
equivalent, but the 3rd lane has half the density
(gray value) compared to lanes 1+2,
while lane 4 has half the density and
half the size compared to lanes 1+2. Because our
loading controls
are so different, the
density values of the upper set of bands may not
be directly comparable.
We’ll use
ImageJ’s gel analysis routine to quantify the
density and size of the bl
ots, and use
the results
from our loading-controls
(lower bands) to scale the values for our protein
of interest (upper bands).
1. Open the
western blot image in ImageJ.
2. Make
sure that the image is in 8-bit mode: go to
Image>Type>8-bit.
3. Use the rectangle
tool to draw a box around the entire 1st lane
(both upper and lower bars included.
4.
Press “1″ to set the rectangle. A “1″ should
appear in the middle of the rectangle.
5. Click and hold in the middle of the
rectangle and drag it over the 2nd lane.
6. Press “2″ to set the rectangle for
lane 2. A “2″ should appear in the middle of the
re
ctangle.
7. Repeat steps 5
+ 6 for each subsequent lane, pressing “2″ to set
the rectangle over each subsequent
lane
(see Figure 13).
8. When
you hav
e placed the last lane (and
pressed “2″ to set it in place), you can press “3″
to produce a
plot of the selected lanes
(see Figure 14).
9.
The
profile
plot
essentially
represents
the
average
density
value
across
a
set
of
horizontal
slic
es
of
each
lane.
Darker
blots
will
have
higher
peaks,
and
blots
that
cover
a
larger
size
range
(k
D)
will
have
wider
peaks.
In
our
example
western
blot,
the
bands
are
perfect
rectangles,
but
you
will
notice
some
slope
in
the
profile
plot
peaks,
as
ImageJ
is
applying
a
bit
of
averaging
of
den
sity
values
as
it
moves
from
top
to
bottom
of
each
lane.
As
a
result,
the
sharp
transition
from
p
erfect
white
to
perfect
black
on
the
bands
of
lane
1
is
translated
into
a
slight
slope
on
the
profil
e
plot
due
to
the
averaging.
10.
On
our
idealized
western
blot
used
here,
there
is
no
background
noise,
so
the
peak
reaches
all
the
way
down
to
the
baseline
of
the
profile
plot.
In
real
western
blots,
there
will
be
some
ba
ckground
noise
(the
background
will
not
be
perfectly
white),
so
the
peaks
won’t
reach
the
baselin
e
of
the
profile
plot
(see
figure
5
above).
As
a
result,
each
plot
will
need
to
have
a
line
drawn
across
the
base
of
the
peak
to
close
it
off.
11.
Choose
the
Straight
Line
selection
tool
from
the
ImageJ
toolbar.
For
each
peak
you
want
to
analyze
in
the
profile
plot,
draw
a
line
across
the
base
of
the
peak
to
enclose
the
peak
(Figure
7).
This
step
requires
some
subjective
judgment
on
your
part
to
decide
where
the
peak
ends
an
d
the
background
noise
begins.
12.
When
each
peak
of
interest
is
closed
off
with
the
straight
line
tool,
switch
to
the
Wand
tool.
We
will
use
the
wand
tool
to
highlight
each
peak
of
interest
so
that
Image-J
can
calculate
its
rel
ative
area+density.
13.
We
will
start
by
highlighting
the
loading-control
bands
(lower
row)
on
our
example
western
bl
ot.
Beginning
at
the
top
of
the
profile
plot,
use
the
wand
to
click
inside
the
1st
peak
(Figure
15).
The
peak
should
be
highlighted
after
you
click
on
it.
Continue
clicking
on
the
loading-control
pe
aks
for
the
other
lanes.
If
a
lane
is
not
visible
at
the
bottom
of
the
profile
plot,
hold
down
the
s
pace
bar
and
click-
and-drag
the
profile
plot
upwards
to
reveal
the
remaining
lanes.
14.
When
the
loading
control
peak
for
each
lane
has
been
highlighted
with
the
wand,
go
to
Anal
yze>Gel>Label
Peaks.
Each
highlighted
peak
will
be
labeled
with
its
relative
size
expressed
as
a
percentage
of
the
total
area
of
all
the
highlighted
peaks.
You
can
go
to
the
Results
window
an
d
choose
Edit>Copy
All
to
copy
the
results
for
placement
in
a
spreadsheet.
15.
Repeat
steps
13
+
14
for
the
real
sample
peaks
now.
We
are
selecting
these
peaks
separat
ely
from
the
loading-control
peaks
so
that
those
areas
are
not
factored
into
the
calculation
of
the
density
of
our
proteins-of-interest.
As
before,
use
the
Wand
tool
to
click
inside
the
area
of
the
p
eak
in
the
1st
lane,
then
continue
clicking
inside
the
peaks
of
the
remaining
lanes.
When
finishe
d,
go
to
Analyze>Gel>Label
Peaks
to
show
the
results.
Copy
the
results
to
a
spreadsheet
alongs
ide
the
data
for
the
loading-control
bands
(Figure
17).
Data
Analysis
with
loading-control
bands
1.
With
all
of
the
relative
density
values
now
in
the
spreadsheet,
we
can
calculate
the
relative
a
mounts
of
protein
on
the
western
blot.
Remember
that
the
“Area”
and
“Percent”
values
returned
by
ImageJ
are
expressed
as
relative
values,
based
only
on
the
peaks
that
you
highlighted
on
th
e
gel.
Start
the
analysis
by
calculating
Relative
Density
values
for
each
of
the
loading-standard
b
ands.
In
this
case,
we’ll
pretend
that
Lane
1
is
our
control
that
we
want
to
compare
the
other
3
lanes
to.
Divide
the
Percent
value
for
each
lane
by
the
Percent
value
in
the
control
(Lane
1
he
re)
to
get
a
set
of
density
values
that
is
relative
to
the
amount
of
protein
in
Lane
1′s
loading
-co
ntrol
band
(Figure
18).
2.
Next
we’ll
calculate
the
Relative
Density
values
for
our
sample
protein
bands
(upper
row
on
th
e
example
western
blot).
We
carry
out
a
similar
calculation
as
step
1,
dividing
the
Percent
value
in
each
row
by
the
Percent
value
of
our
control’s
protein
band
(Lane
1
here).
Note:
Recall
that
because
some
of
our
loading-control
bands
were
wildly
different
on
the
original
western
blot,
we
can’t
simply
use
the
Relative
Density
values
from
our
Samples
calculated
in
Ste
p
2
as
the
final
results.
Now
it
is
necessary
to
scale
the
Relative
Density
values
for
the
Sample
s
by
the
Relative
Density
of
the
corresponding
loading-
control
bands
for
each
lane.
We
do
this
b
ased
on
the
assumption
that
the
proportional
differences
in
the
Relative
Densities
of
the
loading-
control
bands
represent
the
proportional
differences
in
amounts
of
total
protein
we
loaded
on
the
gel.
In
our
example
western
blot,
we
have
evidence
of
massively
different
amounts
of
total
prot
ein
in
each
sample
(poor
pipetting
practice,
probably).
3.
The
final
step
is
to
scale
our
Sample
Relative
Densities
using
the
Relative
Densities
of
the
lo
ading-controls.
On
the
spreadsheet,
divide
the
Sample
Relative
Density
of
each
lane
by
the
loadi
ng-control
Relative
Density
for
that
same
lane.
9.
The
profile
plot
essentially
represents
the
average
density
value
across
a
set
of
horizontal
slic
es
of
each
lane.
Darker
blots
will
have
higher
peaks,
and
blots
that
cover
a
larger
size
range
(k
D)
will
have
wider
peaks.
In
our
example
western
blot,
the
bands
are
perfect
rectangles,
but
you
will
notice
some
slope
in
the
profile
plot
peaks,
as
ImageJ
is
applying
a
bit
of
averaging
of
den
sity
values
as
it
moves
from
top
to
bottom
of
each
lane.
As
a
result,
the
sharp
transition
from
p
erfect
white
to
perfect
black
on
the
bands
of
lane
1
is
translated
into
a
slight
slope
on
the
profil
e
plot
due
to
the
averaging.
10.
On
our
idealized
western
blot
used
here,
there
is
no
background
noise,
so
the
peak
reaches
all
the
way
down
to
the
baseline
of
the
profile
plot.
In
real
western
blots,
there
will
be
some
ba
ckground
noise
(the
backg
round
will
not
be
perfectly
white),
so
the
peaks
won’t
reach
the
baselin
e
of
the
profile
plot
(see
figure
5
above).
As
a
result,
each
plot
will
need
to
have
a
line
drawn
across
the
base
of
the
peak
to
close
it
off.
11.
Choose
the
Straight
Line
selection
tool
from
the
ImageJ
toolbar.
For
each
peak
you
want
to
analyze
in
the
profile
plot,
draw
a
line
across
the
base
of
the
peak
to
enclose
the
peak
(Figure
7).
This
step
requires
some
subjective
judgment
on
your
part
to
decide
where
the
peak
ends
an
d
the
background
noise
begins.
12.
When
each
peak
of
interest
is
closed
off
with
the
straight
line
tool,
switch
to
the
Wand
tool.
We
will
use
the
wand
tool
to
highlight
each
peak
of
interest
so
that
Image-J
can
calculate
its
rel
ative
area+density.
13.
We
will
start
by
highlighting
the
loading-control
bands
(lower
row)
on
our
example
western
bl
ot.
Beginning
at
the
top
of
the
profile
plot,
use
the
wand
to
click
inside
the
1st
peak
(Figure
15).
The
peak
should
be
highlighted
after
you
click
on
it.
Continue
clicking
on
the
loading-control
pe
aks
for
the
other
lanes.
If
a
lane
is
not
visible
at
the
bottom
of
the
profile
plot,
hold
down
the
s
pace
bar
and
click-
and-drag
the
profile
plot
upwards
to
reveal
the
remaining
lanes.
14.
When
the
loading
control
peak
for
each
lane
has
been
highlighted
with
the
wand,
go
to
Anal
yze>Gel>Label
Peaks.
Each
highlighted
peak
will
be
labeled
with
its
relative
size
expressed
as
a
percentage
of
the
total
area
of
all
the
highlighted
peaks.
You
can
go
to
the
Results
window
an
d
choose
Edit>Copy
All
to
copy
the
results
for
placement
in
a
spreadsheet.
15.
Repeat
steps
13
+
14
for
the
real
sample
peaks
now.
We
are
selecting
these
peaks
separat
ely
from
the
loading-control
peaks
so
that
those
areas
are
not
factored
into
the
calculation
of
the
density
of
our
proteins-of-interest.
As
before,
use
the
Wand
tool
to
click
inside
the
area
of
the
p
eak
in
the
1st
lane,
then
continue
clicking
inside
the
peaks
of
the
remaining
lanes.
When
finishe
d,
go
to
Analyze>Gel>Label
Peaks
to
show
the
results.
Copy
the
results
to
a
spreadsheet
alongs
ide
the
data
for
the
loading-control
bands
(Figure
17).
Data
Analysis
with
loading-control
bands
1.
With
all
of
the
relative
density
values
now
in
the
spreadsheet,
we
can
calculate
the
relative
a
mounts
of
protein
on
the
western
blot.
Remember
that
the
“Area”
and
“Percent”
values
returned
by
ImageJ
are
expressed
as
relative
values,
based
only
on
the
peaks
that
you
highlighted
on
th
e
gel.
Start
the
analysis
by
calculating
Relative
Density
values
for
each
of
the
loading-standard
b
ands.
In
this
case,
we’ll
pretend
that
Lane
1
is
our
control
that
we
want
to
compare
the
other
3
lanes
to.
Divide
the
Percent
value
for
each
lane
by
the
Percent
value
in
the
control
(Lane
1
he
re)
to
g
et
a
set
of
density
values
that
is
relative
to
the
amount
of
protein
in
Lane
1′s
loading
-co
ntrol
band
(Figure
18).
2.
Next
we’ll
calculate
the
Relati
ve
Density
values
for
our
sample
protein
bands
(upper
row
on
th
e
example
western
blot).
We
carry
out
a
similar
calculation
as
step
1,
dividing
the
Percent
value
in
each
row
by
the
Percent
value
of
our
control’s
protein
band
(Lane
1
here).
Note:
Recall
that
because
some
of
our
loading-control
bands
were
wildly
different
on
the
original
western
blot,
we
can’t
simply
use
the
Relative
Density
values
from
o
ur
Samples
calculated
in
Ste
p
2
as
the
final
results.
Now
it
is
necessary
to
scale
the
Relative
Density
values
for
the
Sample
s
by
the
Relative
Density
of
the
corresponding
loading-
control
bands
for
each
lane.
We
do
this
b
ased
on
the
assumption
that
the
proportional
differences
in
the
Relative
Densities
of
the
loading-
control
bands
represent
the
proportional
differences
in
amounts
of
total
protein
we
loaded
on
the
gel.
In
our
example
western
blot,
we
have
evidence
of
massively
different
amounts
of
total
prot
ein
in
each
sample
(poor
pipetting
practice,
probably).
3.
The
final
step
is
to
scale
our
Sample
Relative
Densities
using
the
Relative
Densities
of
the
lo
ading-controls.
On
the
spreadsheet,
divide
the
Sample
Relative
Density
of
each
lane
by
the
loadi
ng-control
Relative
Density
for
that
same
lane.
9.
The
profile
plot
essentially
represents
the
average
density
value
across
a
set
of
horizontal
slic
es
of
each
lane.
Darker
blots
will
have
higher
peaks,
and
blots
that
cover
a
larger
size
range
(k
D)
will
have
wider
peaks.
In
our
example
western
blot,
the
bands
are
perfect
rectangles,
but
you
will
notice
some
slope
in
the
profile
plot
peaks,
as
ImageJ
is
applying
a
bit
of
averaging
of
den
sity
values
as
it
moves
from
top
to
bottom
of
each
lane.
As
a
result,
the
sharp
transition
from
p
erfect
white
to
perfect
black
on
the
bands
of
lane
1
is
translated
into
a
slight
slope
on
the
profil
e
plot
due
to
the
averaging.
10.
On
our
idealized
western
blot
used
here,
there
is
no
background
noise,
so
the
peak
reaches
all
the
way
down
to
the
baseline
of
the
profile
plot.
In
real
western
blots,
there
will
be
some
ba
ckground
noise
(the
background
will
not
be
perfectly
white),
so
the
peaks
won’t
reach
the
baselin
e
of
the
profile
plot
(see
figure
5
above).
As
a
result,
each
plot
will
need
to
have
a
line
drawn
across
the
base
of
the
peak
to
close
it
off.
11.
Choose
the
Straight
Line
selection
tool
from
the
ImageJ
toolbar.
For
each
peak
you
want
to
analyze
in
the
profile
plot,
draw
a
line
across
the
base
of
the
peak
to
enclose
the
peak
(Figure
7).
This
step
requires
some
subjective
judgment
on
your
part
to
decide
where
the
peak
ends
an
d
the
background
noise
begins.
12.
When
each
peak
of
interest
is
closed
off
with
the
straight
line
tool,
switch
to
the
Wand
tool.
We
will
use
the
wand
tool
to
highlight
each
peak
of
interest
so
that
Image-J
can
calculate
its
rel
ative
area+density.
13.
We
will
start
by
highlighting
the
loading-control
bands
(lower
row)
on
our
example
western
bl
ot.
Beginning
at
the
top
of
the
profile
plot,
use
the
wand
to
click
inside
the
1st
peak
(Figure
15).
The
peak
should
be
highlighted
after
you
click
on
it.
Continue
clicking
on
the
loading-control
pe
aks
for
the
other
lanes.
If
a
lane
is
not
visible
at
the
bottom
of
the
profile
plot,
hold
down
the
s
pace
bar
and
click-
and-drag
the
profile
plot
upwards
to
reveal
the
remaining
lanes.
14.
When
the
loading
control
peak
for
each
lane
has
been
highlighted
with
the
wand,
go
to
Anal
yze>Gel>Label
Peaks.
Each
highlighted
peak
will
be
labeled
with
its
relative
size
expressed
as
a
percentage
of
the
total
area
of
all
the
highlighted
peaks.
You
can
go
to
the
Results
window
an
d
choose
Edit>Copy
All
to
copy
the
results
for
placement
in
a
spreadsheet.
15.
Repeat
steps
13
+
14
for
the
real
sample
peaks
now.
We
are
selecting
these
peaks
separat
ely
from
the
loading-control
peaks
so
that
those
areas
are
not
factored
into
the
calculation
of
the
density
of
our
proteins-of-interest.
As
before,
use
the
Wand
tool
to
click
inside
the
area
of
the
p
eak
in
the
1st
lane,
then
continue
clicking
inside
the
peaks
of
the
remaining
lanes.
When
finishe
d,
go
to
Analyze>Gel>Label
Peaks
to
show
the
results.
Copy
the
results
to
a
spreadsheet
alongs
ide
the
data
for
the
loading-control
bands
(Figure
17).
Data
Analysis
with
loading-control
bands
1.
With
all
of
the
relative
density
values
now
in
the
spreadsheet,
we
can
calculate
the
relative
a
mounts
of
pro
tein
on
the
western
blot.
Remember
that
the
“Area”
and
“Percent”
values
returned
by
ImageJ
are
expressed
as
relative
values,
based
only
on
the
peaks
that
you
highlighted
on
th
e
gel.
Start
the
analysis
by
calculating
Relative
Density
values
for
each
of
the
loading-standard
b
ands.
In
this
case,
we’ll
pretend
that
Lane
1
is
our
control
that
we
want
to
compare
the
other
3
lanes
to.
Divide
the
Percent
value
for
each
lane
by
the
Percent
value
in
the
control
(Lane
1
he
re)
to
get
a
set
of
density
values
that
is
rel
ative
to
the
amount
of
protein
in
Lane
1′s
loading
-co
ntrol
band
(Figure
18).
2.
Next
we’ll
calculate
the
Relative
Density
values
for
our
sample
prote
in
bands
(upper
row
on
th
e
example
western
blot).
We
carry
out
a
similar
calculation
as
step
1,
dividing
the
Percent
value
in
each
row
by
the
Percent
value
of
our
control’s
protein
band
(Lane
1
here).
Note:
Recall
that
because
some
of
our
loading-control
bands
were
wildly
different
on
the
original
western
blot,
we
can’t
simply
use
the
Relative
Density
values
from
our
Samples
calculated
in
Ste
p
2
as
the
final
results.
Now
it
is
necessary
to
scale
the
Relative
Density
values
for
the
Sample
s
by
the
Relative
Density
of
the
corresponding
loading-
control
bands
for
each
lane.
We
do
this
b
ased
on
the
assumption
that
the
proportional
differences
in
the
Relative
Densities
of
the
loading-
control
bands
represent
the
proportional
differences
in
amounts
of
total
protein
we
loaded
on
the
gel.
In
our
example
western
blot,
we
have
evidence
of
massively
different
amounts
of
total
prot
ein
in
each
sample
(poor
pipetting
practice,
probably).
3.
The
final
step
is
to
scale
our
Sample
Relative
Densities
using
the
Relative
Densities
of
the
lo
ading-controls.
On
the
spreadsheet,
divide
the
Sample
Relative
Density
of
each
lane
by
the
loadi
ng-control
Relative
Density
for
that
same
lane.
9.
The
profile
plot
essentially
represents
the
average
density
value
across
a
set
of
horizontal
slic
es
of
each
lane.
Darker
blots
will
have
higher
peaks,
and
blots
that
cover
a
larger
size
range
(k
D)
will
have
wider
peaks.
In
our
example
western
blot,
the
bands
are
perfect
rectangles,
but
you
will
notice
some
slope
in
the
profile
plot
peaks,
as
ImageJ
is
applying
a
bit
of
averaging
of
den
sity
values
as
it
moves
from
top
to
bottom
of
each
lane.
As
a
result,
the
sharp
transition
from
p
erfect
white
to
perfect
black
on
the
bands
of
lane
1
is
translated
into
a
slight
slope
on
the
profil
e
plot
due
to
the
averaging.
10.
On
our
idealized
western
blot
used
here,
there
is
no
background
noise,
so
the
peak
reaches
all
the
way
down
to
the
baseline
of
the
profile
plot.
In
real
western
blots,
there
will
be
some
ba
ckground
noise
(the
background
will
not
be
perfectly
white),
so
the
peaks
won’t
reach
the
baselin
e
of
the
profile
plot
(see
figure
5
above).
As
a
result,
each
plot
will
need
to
have
a
line
drawn
across
the
base
of
the
peak
to
close
it
off.
11.
Choose
the
Straight
Line
selection
tool
from
the
ImageJ
toolbar.
For
each
peak
you
want
to
analyze
in
the
profile
plot,
draw
a
line
across
the
base
of
the
peak
to
enclose
the
peak
(Figure
7).
This
step
requires
some
subjective
judgment
on
your
part
to
decide
where
the
peak
ends
an
d
the
background
noise
begins.
12.
When
each
peak
of
interest
is
closed
off
with
the
straight
line
tool,
switch
to
the
Wand
tool.
We
will
use
the
wand
tool
to
highlight
each
peak
of
interest
so
that
Image-J
can
calculate
its
rel
ative
area+density.
13.
We
will
start
by
highlighting
the
loading-control
bands
(lower
row)
on
our
example
western
bl
ot.
Beginning
at
the
top
of
the
profile
plot,
use
the
wand
to
click
inside
the
1st
peak
(Figure
15).
The
peak
should
be
highlighted
after
you
click
on
it.
Continue
clicking
on
the
loading-control
pe
aks
for
the
other
lanes.
If
a
lane
is
not
visible
at
the
bottom
of
the
profile
plot,
hold
down
the
s
pace
bar
and
click-
and-drag
the
profile
plot
upwards
to
reveal
the
remaining
lanes.
14.
When
the
loading
control
peak
for
each
lane
has
been
highlighted
with
the
wand,
go
to
Anal
yze>Gel>Label
Peaks.
Each
highlighted
peak
will
be
labeled
with
its
relative
size
expressed
as
a
percentage
of
the
total
area
of
all
the
highlighted
peaks.
You
can
go
to
the
Results
window
an
d
choose
Edit>Copy
All
to
copy
the
results
for
placement
in
a
spreadsheet.
15.
Repeat
steps
13
+
14
for
the
real
sample
peaks
now.
We
are
selecting
these
peaks
separat
ely
from
the
loading-control
peaks
so
that
those
areas
are
not
factored
into
the
calculation
of
the
density
of
our
proteins-of-interest.
As
before,
use
the
Wand
tool
to
click
inside
the
area
of
the
p
eak
in
the
1st
lane,
then
continue
clicking
inside
the
peaks
of
the
remaining
lanes.
When
finishe
d,
go
to
Analyze>Gel>Label
Peaks
to
show
the
results.
Copy
the
results
to
a
spreadsheet
alongs
ide
the
data
for
the
loading-control
bands
(Figure
17).
Data
Analysis
with
loading-control
bands
1.
With
all
of
the
relative
density
values
now
in
the
spreadsheet,
we
can
calculate
the
relative
a
mounts
of
protein
on
the
western
blot.
Remember
tha
t
the
“Area”
and
“Percent”
values
returned
by
ImageJ
are
expressed
as
relative
values,
based
only
on
the
peaks
that
you
highlighted
on
th
e
gel.
Start
the
analysis
by
calculating
Relative
Density
values
for
each
of
the
loading-standard
b
ands.
In
this
case,
we’ll
pretend
that
Lane
1
is
our
control
that
we
want
to
compare
the
other
3
lanes
to.
Divide
the
Percent
value
for
each
lane
by
the
Percent
value
in
the
control
(Lane
1
he
re)
to
get
a
set
of
density
values
that
is
relative
to
the
amount
of
protein
in
Lane
1′s
loading
-co
ntrol
band
(Figure
18).
2.
Next
we’ll
calculate
the
Relative
Density
values
for
our
sample
protein
bands
(upper
row
on
th
e
example
western
blot).
We
carry
out
a
similar
calculation
as
step
1,
dividing
the
Percent
value
in
each
row
by
the
Percent
value
of
our
control’s
protein
band
(Lane
1
here).
Note:
Recall
that
because
some
of
our
loading-control
bands
were
wildly
different
on
the
original
western
blot,
we
can’t
simply
use
the
Relative
Density
values
from
our
Samples
calculated
in
Ste
p
2
as
the
final
results.
Now
it
is
necessary
to
scale
the
Relative
Density
values
for
the
Sample
s
by
the
Relative
Density
of
the
corresponding
loading-
control
bands
for
each
lane.
We
do
this
b
ased
on
the
assumption
that
the
proportional
differences
in
the
Relative
Densities
of
the
loading-
control
bands
represent
the
proportional
differences
in
amounts
of
total
protein
we
loaded
on
the
gel.
In
our
example
western
blot,
we
have
evidence
of
massively
different
amounts
of
total
prot
ein
in
each
sample
(poor
pipetting
practice,
probably).
3.
The
final
step
is
to
scale
our
Sample
Relative
Densities
using
the
Relative
Densities
of
the
lo
ading-controls.
On
the
spreadsheet,
divide
the
Sample
Relative
Density
of
each
lane
by
the
loadi
ng-control
Relative
Density
for
that
same
lane.
9.
The
profile
plot
essentially
represents
the
average
density
value
across
a
set
of
horizontal
slic
es
of
each
lane.
Darker
blots
will
have
higher
peaks,
and
blots
that
cover
a
larger
size
range
(k
D)
will
have
wider
peaks.
In
our
example
western
blot,
the
bands
are
perfect
rectangles,
but
you
will
notice
some
slope
in
the
profile
plot
peaks,
as
ImageJ
is
applying
a
bit
of
averaging
of
den
sity
values
as
it
moves
from
top
to
bottom
of
each
lane.
As
a
result,
the
sharp
transition
from
p
erfect
white
to
perfect
black
on
the
bands
of
lane
1
is
translated
into
a
slight
slope
on
the
profil
e
plot
due
to
the
averaging.
10.
On
our
idealized
western
blot
used
here,
there
is
no
background
noise,
so
the
peak
reaches
all
the
way
down
to
the
baseline
of
the
profile
plot.
In
real
western
blots,
there
will
be
some
ba
ckground
noise
(the
background
will
not
be
perfectly
white),
so
the
peaks
won’t
reach
the
baselin
e
of
the
profile
plot
(see
figure
5
above).
As
a
result,
each
plot
will
need
to
have
a
line
drawn
across
the
base
of
the
peak
to
close
it
off.
11.
Choose
the
Straight
Line
selection
tool
from
the
ImageJ
toolbar.
For
each
peak
you
want
to
analyze
in
the
profile
plot,
draw
a
line
across
the
base
of
the
peak
to
enclose
the
peak
(Figure
7).
This
step
requires
some
subjective
judgment
on
your
part
to
decide
where
the
peak
ends
an
d
the
background
noise
begins.
12.
When
each
peak
of
interest
is
closed
off
with
the
straight
line
tool,
switch
to
the
Wand
tool.
We
will
use
the
wand
tool
to
highlight
each
peak
of
interest
so
that
Image-J
can
calculate
its
rel
ative
area+density.
13.
We
will
start
by
highlighting
the
loading-control
bands
(lower
row)
on
our
example
western
bl
ot.
Beginning
at
the
top
of
the
profile
plot,
use
the
wand
to
click
inside
the
1st
peak
(Figure
15).
The
peak
should
be
highlighted
after
you
click
on
it.
Continue
clicking
on
the
loading-control
pe
aks
for
the
other
lanes.
If
a
lane
is
not
visible
at
the
bottom
of
the
profile
plot,
hold
down
the
s
pace
bar
and
click-
and-drag
the
profile
plot
upwards
to
reveal
the
remaining
lanes.
14.
When
the
loading
control
peak
for
each
lane
has
been
highlighted
with
the
wand,
go
to
Anal
yze>Gel>Label
Peaks.
Each
highlighted
peak
will
be
labeled
with
its
relative
size
expressed
as
a
percentage
of
the
total
area
of
all
the
highlighted
peaks.
You
can
go
to
the
Results
window
an
d
choose
Edit>Copy
All
to
copy
the
results
for
placement
in
a
spreadsheet.
15.
Repeat
steps
13
+
14
for
the
real
sample
peaks
now.
We
are
selecting
these
peaks
separat
ely
from
the
loading-control
peaks
so
that
those
areas
are
not
factored
into
the
calculation
of
the
density
of
our
proteins-of-interest.
As
before,
use
the
Wand
tool
to
click
inside
the
area
of
the
p
eak
in
the
1st
lane,
then
continue
clicking
inside
the
peaks
of
the
remaining
lanes.
When
finishe
d,
go
to
Analyze>Gel>Label
Peaks
to
show
the
results.
Copy
the
results
to
a
spreadsheet
alongs
ide
the
data
for
the
loading-control
bands
(Figure
17).
Data
Analysis
with
loading-control
bands
1.
With
all
of
the
relative
density
values
now
in
the
spreadsheet,
we
can
calculate
the
relative
a
mounts
of
protein
on
the
western
blot.
Remember
that
the
“Area”
and
“Percent”
values
retu
rned
by
ImageJ
are
expressed
as
relative
values,
based
only
on
the
peaks
that
you
highlighted
on
th
e
gel.
Start
the
analysis
by
calculating
Relative
Density
values
for
each
of
the
loading-standard
b
ands.
In
this
case,
we’ll
pretend
that
Lane
1
is
our
contr
ol
that
we
want
to
compare
the
other
3
lanes
to.
Divide
the
Percent
value
for
each
lane
by
the
Percent
value
in
the
control
(Lane
1
he
re)
to
get
a
set
of
density
values
that
is
relative
to
the
amount
of
protein
in
Lane
1′s
loading
-co
ntrol
band
(Figure
18).
2.
Next
we’ll
calculate
the
Relative
Density
values
for
our
sample
protein
bands
(upper
row
on
th
e
example
western
blot).
We
carry
out
a
similar
calculation
as
step
1,
dividing
the
Percent
value
in
each
row
by
the
Percent
value
of
our
control’s
protein
band
(Lane
1
here).