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- Analysis of next generation sequencing data including Exome-sequencing, RNA-sequencing, ChIP-sequencing and whole genome re-sequencing;
- Analysis of microarray datasets including mRNA (Affymetrix), SNP, and micro-RNA;
- Analysis of nCounter NanoString data;
- Analysis of publicly available datasets using search parameters defined by the OSUCCC client, for example from the Gene Expression Omnibus (GEO) database of microarray results, The Cancer Genome Atlas (TCGA), and International Cancer Genome Consortium (ICGC) data portals that allows access to results of thousands of deep sequencing projects;
- Pathway and network analysis from microarray and NGS data;
- Image analysis, including the processing of images in order to reconstruct a three-dimensional tissue, or improvement of image quality using specialized computer programs
- Additional bioinformatics analysis as needed (including protein structure prediction, Genbank search, BLAST, PDB search and motif analysis)
Massively Parallel Sequence Analysis
The sequence output from the Illumina HiSeq 2500 consists of about 200 million sequence tags of 50-100 bp in length per sample.
The sequencer output is useful to biologists when the BISR provides several standard data transformations. The BISR provides three classes of service for the sequence analysis: 1) running an automated pipeline from the sequencing machine to compile sequence reads and their quality assignments; 2) running best practice workflows for the analysis of RNA-sequencing, ChIP-sequencing, Exome-sequencing, and whole genome re-sequencing. Final output besides alignment results are gene expression quantification for RNA-sequencing, variant analysis for exome-sequencing and whole genome re-sequencing, and peak detection for ChIP-sequencing datasets; 3) performing downstream analysis including sample comparisons, pathway analysis and integration with private and publicly available datasets.
Analysis of Microarray Methods
The Analysis of Microarray Methods includes mRNA (Affymetrix), SNP and micro-RNA. Microarray methods results are first analyzed by the Biostatistics Shared Resource to identify genes/probes that have significantly changed expression level in the assay. The BISR not only provides downstream analysis of identifying pathways enriched in the results, but it also helps with data presentation and results submission in public databases.
Publicly Available Datasets Analysis
The Gene Expression Omnibus (GEO) is one of the world’s largest databases in which primary data from nearly all published microarray experiments are stored. The BISR staff analyzes this publicly available data with the biologist.
The Cancer Genome Atlas (TCGA), and International Cancer Genome Consortium (ICGC) are data portals that allows access to results of thousands of deep sequencing projects. BISR staff implements and runs custom workflows and integrates these publicly available datasets to generate new hypotheses or draw new conclusions.
Pathway & Network Analysis of Results from Sequencing and Microarray
Typical analysis of sequencing and Microarray data results in set of genes that have altered gene expression, or have functional mutations. The BISR staff are expert users of Ingenuity Pathway Analysis program, which enables the identification of biological pathways and networks that are enriched in results. The pathway analysis assists the biologist with navigating the large numbers of gene hits, and it can generate new hypotheses for the biologist to test in the laboratory.
Additionally, the BISR can provide advanced network analysis, such as co-expression network analysis, gene regulatory and interaction network analysis, and dense network motif discovery.
Image analysis, including 3D reconstruction, deconvolution and de-noising, offers a variety of image analysis tools to facilitate microscopic image presentation or to make interpretations that otherwise would not be apparent on the original image because of technical limitations.
Sign in to eRamp (https://eramp.osumc.edu) to place orders with BISR.