Investigator meets with Core Technical Director, Dr. Schug, to discuss experiment design, sample preparation, and planned analysis steps prior to sample preparation.

Investigator isolates the RNA. The FGC can supply our standard protocols for isolating RNA from both small and large samples.

Investigator prepares their library for sequencing.

Investigator submits his/her experiment online and then brings RNA/DNA samples to the FGC. Alan Fox or Olga Smirnova will aid the investigator in putting all information about the samples into our database. Any experiment that does not have a completed submission form will be postponed until it is filled out.

Microarray: The FGC staff will perform all aspects of the microarray experiment, from sample preparation to hybridization to scanning and image analysis to lastly assess image quality and hyb quality controls.

Sequencing: The FGC staff will also perform all aspects of the high-throughput sequencing, from clustering the flowcell to putting the flowcell on the GA II. To ensure the prep worked and the samples are ok, we usually sequence one of the samples first, before doing the whole lot of samples.

Microarray: The data are filtered then normalized prior to calculation of fold-changes. The significance of fold-changes is assessed by comparing them to the variation in each gene across replicates using permutation tests as implemented in SAM. Reanalyses may be performed with fewer replicates as necessary if some of the replicates are found to be poor. Once a list of differentially expressed genes has been prepared that list can be processed with Ingenuity or DAVID (NIH) to identify pathways that are enriched.  Alternatively, the GSEA program can be used with all of the genes to identify pathways, GO function categories, etc. that are differentially expressed as a whole.

Sequencing: Sequences from ChIP-Seq or genome resequencing samples are aligned against the reference genome using ELAND as part of the Illumina pipeline. We use the uniquely-aligning reads and extend them to their (ChIP-seq) to their estimated full length to create a stack-height (or pile-up) profile of the data.  The reads and the stack-height profiles for each lane are loaded in the TessLA browser hosted at the FGC for immediate visualization. For ChIP-Seq experiments we run peak-finders and other analyses to assess the quality of the data. For resequencing experiments we generate a consensus sequence for the target region(s).

We prepare a final report which is made available to the investigator via a password-protected website. The report includes links to Excel sheets containing the differentially expressed genes as well as links to the technical details of the analysis and the raw data files necessary for submitting the data to public repositories as required for most publication in many journals.