...
| Table of Contents |
|---|
Introduction
High-throughput
...
sequencing
...
of
...
cDNA,
...
also
...
called
...
RNA-Seq,
...
can
...
provide
...
many
...
levels
...
of
...
information
...
about
...
gene
...
expression,
...
such
...
as
...
information
...
about
...
previously
...
unannotated
...
genes,
...
expression
...
of
...
pseudogenes,
...
differential
...
expression
...
both
...
within
...
and
...
across
...
samples,
...
and
...
alternative
...
splicing.
...
Making
...
the
...
libraries
...
and
...
sending
...
them
...
out
...
for
...
sequencing
...
is
...
only
...
the
...
first
...
step
...
in
...
performing
...
an
...
RNA-Seq
...
experiment.
...
What
...
most
...
people
...
find
...
is
...
that
...
processing,
...
analyzing,
...
and
...
interpreting
...
the
...
data
...
can
...
often
...
be
...
just
...
as
...
time-consuming.
...
Take
...
heart.
...
These
...
data
...
are
...
sets
...
are
...
so
...
rich
...
that
...
you
...
may
...
never
...
fully
...
exhaust
...
their
...
potential.
...
However,
...
there
...
are
...
a
...
few
...
first
...
steps
...
you'll
...
want
...
to
...
perform
...
right
...
away,
...
as
...
well
...
as
...
some
...
quality
...
control
...
steps
...
that
...
will
...
help
...
you
...
assess
...
how
...
well
...
your
...
experiment
...
worked.
...
What
...
follows
...
is
...
a
...
description
...
of
...
RNA-Seq
...
processing
...
steps
...
we
...
do
...
fairly
...
routinely
...
in
...
the
...
Loraine
...
lab,
...
along
...
with
...
links
...
to
...
software
...
programs
...
we've
...
developed
...
for
...
in-house
...
use.
...
Please
...
be
...
aware
...
that
...
these
...
programs
...
are
...
very
...
much
...
works
...
in
...
progress
...
and
...
so
...
may
...
not
...
always
...
work
...
as
...
advertised.
...
If
...
you
...
find
...
bugs
...
or
...
inconsistencies,
...
please
...
let
...
us
...
know
...
-
...
contact
...
Ann
...
(aloraine@uncc.edu)
...
with
...
feedback,
...
suggestions,
...
and
...
bug
...
reports.
...
RNA-Seq
...
tutorial
...
The
...
following
...
protocol
...
describes
...
processing
...
data
...
from
...
Illumina
...
HiSeq
...
pipeline.
...
Whether
...
you
...
should
...
perform
...
exactly
...
these
...
steps
...
with
...
your
...
data
...
sets
...
will
...
depend
...
on
...
your
...
data
...
-
...
its
...
age,
...
whether
...
you've
...
done
...
single-end
...
or
...
paired-end
...
sequencing,
...
the
...
read
...
lengths,
...
your
...
reference
...
genome,
...
and
...
so
...
on.
...
For
...
example,
...
when
...
you
...
run
...
TopHat,
...
you
...
may
...
need
...
to
...
adjust
...
parameters
...
to
...
accommodate
...
smaller
...
read
...
lengths
...
if
...
you
...
are
...
running
...
data
...
from
...
pre-HiSeq
...
instruments.
...
Check
...
sequence
...
quality.
...
Your
...
first
...
step
...
upon
...
downloading
...
your
...
reads
...
will
...
be
...
to
...
check
...
the
...
quality
...
of
...
your
...
sequence.
...
One
...
of
...
the
...
easiest
...
to
...
use
...
tools
...
we
...
(in
...
the
...
Loraine
...
lab)
...
have
...
found
...
for
...
quality
...
checking
...
is
...
a
...
terrific
...
program
...
called
...
...
,
...
from
...
the
...
Babraham
...
Institute.
...
You
...
can
...
run
...
it
...
interactively
...
or
...
as
...
a
...
command
...
line
...
tool,
...
and
...
it's
...
written
...
in
...
Java,
...
which
...
means
...
you
...
can
...
run
...
it
...
on
...
a
...
Mac,
...
a
...
Linux
...
machine,
...
or
...
a
...
Windows
...
computer.
...
Like
...
IGB,
...
any
...
computer
...
that
...
supports
...
Java
...
can
...
run
...
FastQC.
...
What
...
you
...
should
...
be
...
looking
...
for
...
in
...
your
...
data
...
is
...
evidence
...
of
...
poor
...
sequencing
...
quality
...
as
...
well
...
as
...
spots
...
in
...
your
...
sequence
...
where
...
you
...
have
...
lots
...
and
...
lots
...
of
...
N
...
characters
...
-
...
these
...
usually
...
correspond
...
to
...
place
...
with
...
poor
...
quality.
...
If
...
your
...
reads
...
are
...
generally
...
low
...
quality,
...
you
...
should
...
ask
...
your
...
sequencing
...
facility
...
to
...
try
...
again.
...
If
...
your
...
data
...
have
...
many,
...
many
...
over-represented
...
sequences
...
(something
...
FastQC
...
can
...
tell
...
you),
...
then
...
you
...
may
...
want
...
to
...
make
...
another
...
library
...
for
...
that
...
sample.
...
In
...
our
...
experience,
...
low
...
yields
...
and
...
low
...
quality
...
generally
...
happen
...
because
...
something
...
went
...
wrong
...
with
...
sequence.
...
Over-represented
...
sequences
...
and
...
so-called
...
PCR
...
duplicates
...
(many
...
copies
...
of
...
the
...
same
...
sequence)
...
are
...
usually
...
due
...
to
...
problems
...
in
...
library
...
construction.
...
Align your sequence.
Let's
...
assume
...
that
...
(happily)
...
you
...
have
...
good-quality
...
sequence.
...
Your
...
next
...
step
...
should
...
be
...
to
...
align
...
your
...
sequences
...
onto
...
a
...
reference
...
genome
...
or
...
refernece
...
transcriptome.
...
Indeed,
...
even
...
if
...
you
...
haven't
...
got
...
high-quality
...
sequence,
...
you
...
should
...
still
...
try
...
to
...
align
...
it,
...
because
...
the
...
alignments
...
can
...
tell
...
you
...
a
...
lot
...
about
...
what
...
went
...
wrong.
...
For
...
this
...
tutorial,
...
we'll
...
use
...
a
...
spliced
...
alignment
...
tool
...
to
...
align
...
the
...
RNA-Seq
...
reads
...
onto
...
a
...
reference
...
genome.
...
For RNA-Seq
...
data
...
sets,
...
we
...
mainly
...
have
...
used
...
TopHat,
...
from
...
the
...
University
...
of
...
Maryland.
...
Others
...
are
...
available,
...
but
...
since
...
we
...
have
...
the
...
most
...
experience
...
with
...
TopHat
...
and
...
seems
...
to
...
be
...
one
...
of
...
the
...
more
...
widely
...
used
...
programs,
...
the
...
following
...
examples
...
will
...
demonstrate
...
how
...
to
...
run
...
it.
...
TopHat
...
is
...
a
...
spliced
...
alignment
...
tool
...
that
...
first
...
runs
...
BowTie
...
(a
...
non-spliced
...
alignment
...
tool
...
from
...
the
...
same
...
group)
...
and
...
then
...
attempts
...
to
...
align
...
any
...
reads
...
BowTie
...
couldn't
...
align
...
by
...
splitting
...
them
...
across
...
putative
...
introns.
...
For
...
this
...
reason,
...
to
...
run
...
TopHat
...
you'll
...
have
...
to
...
install
...
BowTie.
...
You'll
...
also
...
have
...
to
...
install
...
samtools,
...
a
...
program
...
that
...
TopHat
...
and
...
BowTie
...
use
...
to
...
generate
...
alignment
...
files
...
called
...
"BAM"
...
(binary
...
alignment)
...
files.
...
IGB
...
can
...
display
...
data
...
from
...
BAM
...
files,
...
once
...
you've
...
created
...
an
...
index
...
for
...
them.
...
More
...
on
...
indexing
...
BAM
...
files
...
will
...
come
...
later.
...
Many
...
different
...
versions
...
of
...
TopHat
...
have
...
been
...
released
...
over
...
the
...
past
...
couple
...
of
...
years
...
and
...
each
...
behaves
...
slightly
...
differently.
...
However,
...
a
...
few
...
things
...
seem
...
to
...
remain
...
stable.
...
First,
...
TopHat
...
will
...
typically
...
report
...
multiple
...
alignments
...
for
...
some
...
number
...
of
...
reads.
...
This
...
is
...
to
...
be
...
expected.
...
However,
...
depending
...
on
...
your
...
experimental
...
goals,
...
you
...
may
...
want
...
to
...
focus
...
on
...
the
...
reads
...
that
...
map
...
exactly
...
once
...
onto
...
the
...
genome.
...
You
...
can
...
figure
...
out
...
which
...
reads
...
mapped
...
to
...
multiple
...
locations
...
by
...
looking
...
at
...
the
...
"NH"
...
flag
...
in
...
each
...
alignment.
...
Also,
...
you
...
should
...
determine
...
the
...
minimum
...
and
...
maximum
...
intron
...
sizes
...
for
...
your
...
genome
...
and
...
provide
...
these
...
as
...
parameters
...
to
...
TopHat.
...
For
...
details
...
on
...
running
...
TopHat,
...
see
...
the
...
...
...
.
Here is an example invocation of TopHat, fine-tuned
...
for
...
Arabidopsis
...
thaliana
...
.
...
TopHat
...
is
...
a
...
command
...
line
...
program,
...
which
...
means
...
you
...
run
...
it
...
by
...
typing
...
commands
...
into
...
a
...
Unix
...
terminal.
...
(On
...
Mac,
...
this
...
is
...
the
...
Terminal
...
program
...
from
...
the
...
Applications
...
Utilities.)
...
For
...
the
...
rest
...
of
...
this
...
tutorial,
...
wherever
...
you
...
see
...
a
...
line
...
that
...
starts
...
with
...
a
...
"$"
...
sign,
...
this
...
means
...
you
...
type
...
the
...
command
...
into
...
a
...
terminal.
...
(The
...
"$"
...
means:
...
the
...
Unix
...
prompt.)
...
| Code Block |
|---|
$ tophattophat2 --max-intron-length 2000 /data/bowtieindex/A_thaliana_Jun_2009 Sample.fastq -o Sample {code} |
However,
...
you're
...
probably
...
better
...
off
...
running
...
TopHat
...
on
...
a
...
fairly
...
powerful
...
machine.
...
If
...
you
...
can
...
find
...
a
...
multi-processor
...
server
...
with
...
16
...
or
...
more
...
of
...
RAM,
...
I
...
would
...
strongly
...
recommend
...
using
...
it
...
to
...
run
...
the
...
alignment
...
step.
...
If
...
you
...
do
...
get
...
access
...
to
...
a
...
multi-processor
...
server,
...
you
...
should
...
tell
...
TopHat
...
to
...
take
...
advantage
...
of
...
the
...
extra
...
processing
...
power
...
using
...
the
...
-p
...
parameter
...
that
...
allows
...
you
...
to
...
specify
...
the
...
number
...
of
...
processors
...
TopHat
...
can
...
use.
...
To
...
run
...
bowtie2,
...
you
...
have
...
to
...
first
...
make
...
an
...
index
...
file
...
for
...
your
...
genome.
...
And
...
to
...
make
...
an
...
index
...
for
...
your
...
genome,
...
you'll
...
need
...
a
...
fasta
...
file
...
for
...
your
...
genome.
...
This
...
is
...
easy
...
to
...
get,
...
however.
...
You
...
can
...
either
...
download
...
the
...
fasta
...
files
...
directly
...
from
...
the
...
genome
...
data
...
provider
...
(e.g.,
...
UCSC
...
or
...
NBCI)
...
or
...
you
...
can
...
get
...
a
...
2bit
...
file
...
from
...
the
...
IGBQuickLoad
...
Web
...
site
...
and
...
convert
...
it
...
to
...
fasta.
...
To
...
get
...
a
...
sequence
...
data
...
file
...
from
...
IGBQuickLoad.org,
...
go
...
to
...
the
...
genome
...
directory
...
and
...
download
...
the
...
"2bit"
...
file
...
you
...
find
...
there.
...
Then
...
use
...
Jim
...
Kent's
...
2bit2
...
In
...
this
...
example,
...
I'll
...
run
...
bowtie2-build
...
using
...
a
...
fasta
...
file
...
A_thaliana_Jun_2009.fa
...
to
...
create
...
index
...
files
...
bowtie2 uses
...
to
...
speed
...
up
...
the
...
alignment
...
process.
...
We
...
TopHat
...
will
...
created
...
a
...
directory
...
called
...
Sample
...
(the
...
-o
...
parameter).
...
In
...
IGB,
...
we
...
use
...
files
...
in
...
"2bit"
...
format
...
to
...
represent
...
genomic
...
sequence
...
data.
...
It's
...
easy
...
to
...
convert
...
a
...
2bit
...
file
...
into
...
a
...
fasta
...
file
...
and
...
back
...
again.
...
To
...
create
...
a
...
fasta
...
file,
...
do something like:
| Code Block |
|---|
twoBitToFa A_thaliana_Jun_2009.2bit A_thaliana_Jun_2009.fa
|
Please note that you need to make sure that the names of chromosomes in the fasta file (and hence the BowTie index files) match with what IGB uses. For Arabidopsis, chromosome names are chr1, chr2, chr3, chr4, chr5, chrC, and chrM.
IGB has a synonyms system that allows it to "understand" that chr1 and Chr1 are really the same thing, but other programs you will run into might not be able to match names in this way. For this reason, it's a good idea to use the same names for chromosome throughout all the different steps of processing data.
Process output files
Index (and rename) your alignment file
When TopHat finishes, it will have created a file called "accepted_hits.bam"
...
that
...
contains
...
your
...
alignments.
...
Your
...
next
...
step
...
in
...
the
...
process
...
will
...
be
...
to
...
index
...
this
...
file,
...
creating
...
what's
...
called
...
a
...
"bai"
...
index
...
file.
...
For
...
this,
...
you'll
...
use
...
samtools,
...
a
...
freely
...
available
...
command-line
...
tool
...
with
...
many
...
useful
...
functions.
...
You
...
can
...
learn
...
about
...
samtools
...
at
...
...
...
...
and
...
download
...
the
...
code
...
from
...
...
...
hosted
...
at
...
sourceforge.net.
...
Why
...
make
...
an
...
index?
...
This
...
is
...
a
...
crucial
...
step
...
because
...
it
...
allows
...
programs
...
like
...
IGB
...
to
...
do
...
what
...
is
...
called
...
a
...
"region-based
...
query."
...
That
...
is,
...
once
...
you've
...
started
...
IGB,
...
you
...
can
...
load
...
the
...
BAM
...
file,
...
zoom
...
in
...
on
...
a
...
region,
...
and
...
then
...
ask
...
IGB
...
to
...
load
...
in
...
just
...
the
...
reads
...
that
...
overlap
...
your
...
region
...
of
...
interest.
...
This
...
works
...
because
...
IGB
...
reads
...
the
...
index
...
file,
...
which
...
tells
...
IGB
...
exactly
...
where
...
to
...
look
...
in
...
the
...
larger
...
BAM
...
file
...
(which
...
may
...
be
...
1
...
gig
...
or
...
more
...
!)
...
for
...
just
...
the
...
subset
...
of
...
reads
...
that
...
are
...
relevant
...
to
...
the
...
region
...
in
...
view.
...
To
...
make
...
an
...
index
...
(.bai)
...
file
...
for
...
a
...
BAM
...
file,
...
you
...
typically
...
would
...
first
...
have
...
to
...
sort
...
the
...
BAM
...
file
...
first.
...
However,
...
the
...
"accepted_hits.bam"
...
file
...
from
...
TopHat
...
should
...
already
...
be
...
sorted.
...
So
...
all
...
you
...
should
...
need
...
to
...
do
...
next
...
is
...
rename
...
it
...
and
...
make
...
an
...
index
...
for
...
it,
...
like
...
so:
...
| Code Block |
|---|
$ mv accepted_hits.bam Sample.bam
$ samtools index Sample.bam
{code}
|
which
...
will
...
create
...
an
...
index
...
file
...
named
...
Sample.bam.bai.
...
Make
...
a
...
bedgraph
...
(wiggle)
...
genome
...
coverage
...
file
...
A
...
genome
...
coverage
...
(or
...
depth)
...
file
...
reports
...
the
...
number
...
of
...
reads
...
overlapping
...
regions
...
or
...
individual
...
bases
...
of
...
the
...
reference
...
genome.
...
Older
...
versions
...
of
...
TopHat
...
used
...
to
...
create
...
a
...
coverage
...
file,
...
but
...
more
...
recent
...
versions
...
of
...
Tophat
...
no
...
longer
...
do
...
this.
...
However,
...
you
...
can
...
create
...
coverage
...
graphs
...
using
...
bedtools
...
...
command.
...
For
...
information
...
on
...
where
...
to
...
get
...
bedtools
...
and
...
how
...
to
...
install
...
it,
...
visit
...
the
...
...
...
.
To create a genome coverage bedgraph file from your BAM alignments file on a Linux machine, do this:
| Code Block |
|---|
$ genomecov -ibam Sample.bam -split -bg > Sample.bedgraph {code} |
What
...
should
...
happen
...
next
...
is
...
that
...
a
...
new
...
file
...
should
...
appear
...
named
...
Sample.bedgraph,
...
which
...
will
...
have
...
a
...
structure
...
that
...
looks
...
a
...
bit
...
like:
| Code Block |
|---|
chr1 3667 3697 2 {code} fill in {code} At this point, you should be able to open the "bedgraph" file directly in IGB. However, IGB will work better if you sort the file, compress it using bgzip, and then make an index for the file using tabix. {code}chr1 3697 3707 3 chr1 3707 3726 5 chr1 3726 3742 6 chr1 3742 3744 4 chr1 3744 3749 5 chr1 3749 3755 6 |
At this point, you should be able to open the "bedgraph" file directly in IGB. However, IGB will work better if you sort the file, compress it using bgzip, and then make an index for the file using tabix.
| Code Block |
|---|
$ sort -k1,1 -k2,2n Sample.bedgraph | bgzip > Sample.bedgraph.gz $ tabix -s 1 -b 2 -e 3 Sample.bedgraph.gz {code} The sort command will read the entire gz |
The sort command will read the entire Sample.bedgraph
...
file
...
into
...
memory,
...
sort
...
the
...
data,
...
and
...
then
...
output
...
the
...
data
...
in
...
sorted
...
order.
...
The
...
sorted
...
data
...
will
...
first
...
be
...
ordered
...
by
...
chromosome
...
name
...
(field
...
1)
...
and
...
then
...
by
...
interval
...
start
...
position
...
(field
...
2).
...
In
...
the
...
command
...
above,
...
the
...
sorted
...
data
...
are
...
piped
...
into
...
the
...
bgzip
...
compression
...
tool
...
and
...
then
...
the
...
compressed,
...
sorted
...
data
...
are
...
saved
...
to
...
a
...
file
...
called
...
Sample.bedgraph.gz
...
.
...
The
...
tabix
...
command
...
then
...
creates
...
an
...
index
...
file
...
(extension
...
.tbi
...
)
...
for
...
the
...
newly
...
compressed,
...
sorted
...
Sample.bedgraph.gz
...
file.
...
Note
...
:
...
To
...
view
...
Sample.bedgraph.gz
...
file
...
in
...
IGB,
...
you
...
should
...
always
...
keep
...
the
...
index
...
file
...
(named
...
Sample.bedgraph.gz.tbi
...
)
...
in
...
the
...
same
...
folder.
...
To
...
get
...
a
...
copy
...
of
...
bgzip
...
and
...
tabix
...
,
...
go
...
to
...
...
...
...
...
.
...
Note
...
that
...
development
...
of
...
tabix
...
has
...
moved
...
to
...
...
View data in IGB
Once you've created the files, you should then be able to open them in IGB. However, be sure to keep the index files (.bai from samtools and .tbi from tabix) in the same folder with their corresponding alignments or bedgraph files.
Once you open them in IGB, scroll and zoom to a smallist region of your genome -- a region where you can see maybe five or six different genes. (Use the "search" tab to zoom in on a particular gene of interest.)
Then, click "Load Data" to load data from the files you selected. (All selected files should appear in the Data Management Table on the right side of the Data Access tab.)
If all goes well, the bedgraph file data should appear in a graph track. To change its appearance, e.g., add a y-axis, change the color, etc. select the track label and click the Graph Adjuster tab, which contains various controls for working with graphs.
The reads (from the BAM) file appear in tracks above and below the axis. To change how reads look, choose File->Preferences->Tracks and use the options you see there to merge all the reads into a single +/- track, use color to indicate strand, change the number of reads that are shown in stacks, and so on.
For more information on working with tracks and graphs, please see the IGB User's Guide.
And remember, if you have questions, get in touch with us or use Google. All IGB tutorials and user guide materials are publicly available on our wiki and have (mostly) been indexed in Google.