For details in Linux part, please go to HPC_biolinux webpage.
Bring your specific problems to discuss with the Instructor & TAs.
NGS workflow, general data analysis pipeline, data formats, short read alignment software, general workflow for DNA-seq, RNA-seq and ChIP-seq and corresponding software resources. Data visualization tools such as IGV.
RNA-seq data analysis: experimental design, spliced mapping, data normalization, transcriptome assembly and abundance quantification. The tuxedo suite protocol (Tophat/cufflinks/cuffdiff parameter) for RNA-seq. Popular pipelines such as Tophat-HTSeq-DESeq pipeline for RNA-seq. R based statistical analysis of gene expression. Downstream pathway analysis software. Open source RNA-seq software with graphical user interface. ChIP-seq work flow and software. Galaxy.
Getting reference genome sequences to HPC, getting reference annotation. FASTA and FASTQ format of data. Prepareing reference sequence for alignment. Using tophat/bowtie to align short reads. Use the alignment obtained and run cuffmerge, cufflinks and cuffdiff. Examine cuffdiff output. Depending on the time and level of students, cummeRbund can also be covered. ChIP-seq with Galaxy if needed.
If you have specific questions about the Bioinformatics-related parts of the course, please contact Jenny Wu <firstname.lastname@example.org> for more information.
The class will consist of a morning lecture followed by an extended tutorial that will last thru the afternoon. Both sessions are available to the entire UCI community. The sessions are free. Both sessions include coffee, mid-session snacks and lunch.
For registration, go to http://datascience.uci.edu/
Contact Janet Ko <Jko@uci.edu> if you have any questions.
Bioinformatics Courses at UCI
EPIDEM 275 Special Epi Topics: Bioinformatics
(Course Code # 91667) Spring 2019
Dr. Norden-Krichmar – email@example.com
CS284A: Representations & Algorithms for Molecular Biology
(Course code #35370)
Dr. Xiaohui Xie – firstname.lastname@example.org
ECO EVO 253. Functional and Structural Evolutionary Genomics.