Genomics and Multi-Omics Data Analysis
Send us the data and the biological question. We handle the analysis, the interpretation, and the figures.
Transcriptomics. Bulk and single-cell RNA-seq, spatial, and ribosomal profiling.
Epigenomics. Bulk and single-cell ATAC-seq, methylation by array or bisulfite sequencing, and HiC.
Genomics. Genomic structure and variant calling, GWAS, rare variants, de novo association in family trios, and oncoplots.
Proteomics and metabolomics. SomaScan and Olink protein expression, single-cell proteomics by CyTOF and CITE-seq, and metabolomic data.
Long-range sequencing. PacBio single-molecule footprinting and base modification calling.
Integrative analysis across phenotype, genotype, and multiple omics layers is where most of the biological insight actually shows up, so we treat it as the point rather than an add-on. Where current methods fall short we build the tool, which is how most of our open-source software started.
Large-scale datasets are routine here.
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