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Thus, a large set of computational tools have been developed to quickly, and with sufficient (but NOT absolute) accuracy align each read to its best location, if any, in a reference. Even though many mapping tools exist, a few individual programs have a dominant "market share" of the NGS world. These programs vary widely in their design, inputs, outputs, and applications. In this section, we will primarily focus on two of the most versatile mappers: BWA and Bowtie2, the latter being part of the Tuxedo suite (e.g. Tophat2).

Sample Datasets and Reference Genomes

You have already worked with one a paired-end yeast ChIP-seq dataset, which we will continue to use here.  In order to demonstrate how to process 

Reference Genomes


BWA - The Most General Mapper



.  We will also use two additional RNA-seq datasets.  The additional data are located in the path:

Code Block

So, the following are the data you will need:

File NameDescriptionSample Illumina, First of pair, FASTQYeast ChIP-seq Illumina, Second of pair, FASTQYeast ChIP-seq
human_rnaseq.fastq.gzSingle-end Illumina, FASTQHuman RNA-seq
human_mirnaseq.fastq.gzSingle-end Illumina, FASTQHuman microRNA-seq

Now we need to set up the raw data for processing. Stage these files on Stampede from Corral in the fewest possible commands.

Code Block
cp /corral-repl/utexas/BioITeam/core_ngs_tools/human_stuff/*rnaseq* .

Do you believe that I gave you files of any reasonable quality?  I wouldn't, so you should check it out.

Code Block

BWA - Yeast ChIP-seq


Bowtie2 and Local Alignment - Human microRNA-seq


BWA-MEM (and Tophat2) - Human mRNA-seq


Future Directions