under construction
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 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.
Methods
The following protocol describes processing data from Illumina HiSeq pipeline. These steps may vary depending on your data, its age, 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.
Align your sequence. For RNA-Seq data sets, we mainly have used TopHat, from the University of Maryland.
TopHat is a spliced alignment tool that first runs BowTie (a non-spliced alignment tool) 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. Once you have sorted and indexed these files, IGB will be able to display them. More on this 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. More on this later. 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 TopHat Manual.
Here is an example invocation of TopHat, fine-tuned for Arabidopsis thaliana:
tophat --min-intron-length 40 --max-intron-length 2000 /data/bowtieindex/A_thaliana_Jun_2009 Sample.fastq -o Sample
In this example, we've run bowtie-build using a fasta file A_thaliana_Jun_2009.fa (which you can download from a folder on our QuickLoad site here) to create index files bowtie uses to speed up the alignment process.
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 won't be smart enough to match up 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 sort and 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 this Web site and download the code from this page hosted at sourceforge.net.
The "accepted_hits.bam" file should already be sorted. So all you should need to do next is rename it and make an index for it, like so:
$ mv accepted_hits.bam Sample.bam # samtools index Sample.bam
which will create an index file named Sample.bam.bai.
Make a bedgraph (wiggle) file
Older versions of TopHat used to create a depth (also called coverage) file as part of the TopHat processing step. However, more recent versions of Tophat no longer do this. The program TopHat used to make the coverage graph file was called wiggles; we obtained a copy and made a few modifications to it. You can obtain compiled versions from this wiki page (click "Attachments") or from our subversion repository.
To create bedgraph file from your BAM alignments file on a Linux machine, do this:
$ samtools view Sample.bam | wiggles.linux --wiggle-name="Sample coverage graph" > Sample.bedgraph
to be continued