Functional Genomics and Bioinformatics Core
The Functional Genomics and Bioinformatics Core provides services to investigators within BNORC and the Boston area looking to expand their research using state-of-the-art genomic applications. It utilizes next generation technologies and sequencing platforms to help identify the complex molecular mechanisms underlying human disease. Core staff can consult with researchers to ensure optimal experimental design on a case-by-case basis. Downstream or stand-alone data analysis pipelines are also offered to help researchers get the most from their datasets.
- Pre- and post-experimental consultation to determine proper experimental approach, design, and interpretation
- Sample quality assessment of DNA and RNA using the BioAnalyzer and Qubit assays
- Library preparation, sequencing, and analysis of transcriptomes (RNA-seq, low-input RNA-seq, Ribo-seq), cistromes (ChIP-seq, CUT&RUN), chromatin accessibility (ATAC-seq).
- Standalone RNA preparation, RNA and DNA Bioanalyzer analyses, chromatin shearing/shear checks
- Standalone sequencing on NextSeq500
- Single Cell/Nucleus nuclear isolation (targeted or untargeted), library RNA-seq Droplet generation, Library Preparation
- Standard RNA-seq analysis: quality assessment and normalization, transcript alignment, PCA, differential expression, functional ontology analysis, GSEA, WGCNA, network analysis.
- Standard ChIP-seq/ATAC-seq/CUT&RUN analyses: QC, alignment, normalization, and peak calling. PCA, differential enrichment analysis, functional ontology analysis, WGCNA, network analysis, sample clustering, and motif discovery/enrichment.
- Standard single cell/nucleus RNA-seq analysis: QC, barcode demultiplexing, transcript alignment, UMI collapsing, ambient RNA estimation/removal, doublet removal, normalization and batch correction, canonical correlation integration, graph-based clustering, and marker determination.
- Bespoke data analysis, including integration of complex ChIP-seq and RNA-seq data sets, GWAS, single-cell sequencing analyses