Computational Biology and Bioinformatics Services and Consultations

Analysis of next generation sequencing data including whole exome-sequencing, RNA-sequencing, smRNA-sequencing, ChIP-sequencing, ATAC-sequencing and whole genome re-sequencing.
Analysis of long read sequencing (such as PacBio and Oxford Nanopore Sequencing) including QC and error correction of long reads, gene/gene isoform expression, novel gene discovery and full length isoform identification, de novo fusion gene detection and corresponding fusion isoform expression profiles, allele-specific expression and haplotyping, de novo genome assembly, de novo transcriptome assembly, methylation calling, nucleosome positioning and chromatin accessibility.
Single-cell RNA-seq data analysis services:
- Basic scRNA-seq data analyses, including quality control, alignment, trimming, assembly, differentiation expression, and clustering, using developed pipelines
- Advanced scRNA-seq data analyses, including but not limited to cell trajectory discovery, cell type prediction, co-regulated gene module identification
- Selective scRNA-seq analyses in aim to solving specific issues such as drop-out issue, immense expression data (i.e., 10X scRNA-seq data)
- Result interpretation and interpretation
- An all-in-one user-friendly web server for scRNA-seq analysis
- Integrative analysis of single-cell multi-omics data to enhance the effectiveness and efficiency
Metagenomic data analysis services:
- Metagenomic data analysis including species/strain composition profiling, taxonomic analysis, abundance analysis, phylogenetic analysis, whole-genome shotgun analysis
- Metatranscriptomic data analysis including functional profiling, expression activity analysis,16S ribosomal RNA analysis, whole-transcriptome shotgun analysis
- Advanced joint metagenomic and metatranscriptomics data analysis for more accurate gene-level, species-level, and strain-level analysis
- Network studies in microbiome and host–microbiota interactions based on high-throughput multi-omics data
- Causality study between human microbiota and diseases
- Existing tools/pipelines recommendation, analysist training and guidance
Analysis of microarray datasets, including mRNA (Affymetrix), SNP, and micro-RNA.
Analysis of nCounter NanoString data.
Proteomics data analysis:
- Protein/peptide identification and quantification from label-free and label-based tandem mass spectrometry data
- Post-translational modification analysis (PTM), such as phosphorylation
- Downstream bioinformatics analysis, such as: differential expression analysis, pathway analysis and functional enrichment, analysis, network analysis, involving finding pivotal proteins in the networks
Metabolomics data analysis:
- LC-MS data preprocessing (including quality control assessment of raw chromatograms, peak calling, retention time alignment, and preliminary identification using MS2 data if available)
- Interpretation of liquid-chromatography untargeted metabolomics datasets, which include relative abundances of a broad spectrum of polar and non-polar small molecules (< 1500 Daltons)
- Statistical analysis to identify biologically-relevant metabolites
- Pathway enrichment analysis of relevant metabolites
Integrative analysis of publicly available datasets (dbGaP, GEO, TCGA) using search parameters defined by the OSUCCC researchers.
Pathway analysis of results from sequencing and microarray data.
Custom bio-molecular data management, application development, deployment and support.
CRISPR Screening:
- Experimental Design
- Cancer-specific essential genes
- Synthetic lethal partners
- Drug resistance mechanism
Precision cancer medicine services:
- Integrating gene expression profiles, mutations and phenotype features to predict target, drug and biomarker in precision cancer medicine
- Identification of potential druggable targets
- Assessment of efficacy drugs and associated biomarkers

Training and Workshops: BISR faculty and staff offer short 1-2 day workshops and seminars addressing bioinformatics questions and needs of OSU researches. The workshops contain hands-on activities, to help OSU researchers to understand the process of data analysis and the interpretation of the results.

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Massively Parallel Sequence Analysis

The sequence output from the Illumina HiSeq 4500. 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 microRNA. 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 implement and run custom workflows and integrate these publicly available datasets to generate new hypotheses or draw new conclusions.

Pathway and 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. BISR staff are expert users of the 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.

Computational Biology and Bioinformatics Services and Consultations

Computational Biology and Bioinformatics Services and Consultations

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