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I started my journey into bioinformatics by asking “What is genomics?” and then “What is a gene?” My biology collaborators were still heatedly responding to one another an hour later and I learned a great deal through this process. Just about everything I thought was “obvious” turned out to be incorrect or controversial.  I cannot stress enough the importance of asking your questions and respectfully responding to the questions of others.   Because of the diversity of your backgrounds, we can all learn from one another more effectively than you can learn everything from the teacher.

The primary focus of the statistical analyses will be differential gene expression using microarrays and sequencing. These analyses use most of the statistical tools that are also useful for other array and sequencing based studies such as chromatin immunoprecipitation (ChIP), methylation and marker studies such as genome-wide association studies (GWAS) using single nucleotide polymorphisms (SNPs), two other types of studies that we will discuss (more briefly). These statistical tools are also useful for proteomics and other “omics” data although we will not discuss these. A number of important topics will only be touched upon briefly.  Some of these are covered in Applied Bioinformatics, BMMB 597D, Bioinformatics I: Foundations in Data Driven Life Sciences BMMB597B and Elements of Network Science and its Applications, PHYS 580.