Resources

BIT 815 Course Page

The Analysis of Deep Sequencing Data course is designed to introduce biologists to the Linux command-line computing environment, to cloud computing, and to open-source software for analysis of next-generation sequencing data. The Read the Docs webpage contains computing exercises utilize the software discussed, and provide participants with the opportunity to carry out analysis of sample datasets using a virtual machine image through the NC State University Virtual Computing Lab (Biostar_DNASeq image). This Linux system is customized to provide the bioinformatics software described during the course, and is available for class participants to use at any time. However, there is documentation for installation of the required programs on local machines that do not have access to the VCL or would like to install on a local machine. The objective of the course (and webpage) is not to make course participants experts in every aspect of sequence analysis, but instead to empower participants to learn the specific skills they need by teaching basic skills in command-line Linux computing, and providing an introduction to the literature and on-line resources.

Software documentation

If we have existing documentation for a software package, there will be a link to that documenation. If not, please contribute by adding a pull request. Add instructions for doing the pull request here.

It is preferred that you create a new page for your documentation and submit a pull request, but you may also contibute by submitting a BUG report if you are more comfortable doing so.

Conda BLAST BEAST 2
QIIME2 Bowtie 2 bwa
SPAdes Cufflinks Velvet
Canu Trimmomatic FastQC

Here is the Software Spreadsheet that contains the original plans for shared documenation.

External Resources

A “living” textbook that is contiually updated as new software and sequencing platforms are made. Another great introductory resource to those new to sequence analysis, with the purchase of the book subscription you also gain access to a few online workshops and courses like “Python in 100 hours”.