What We Offer

At AccuraScience, we provide expert, customized bioinformatics services aligned with your research questions, data types, and downstream goals. Our clients span academia, biotech, and pharma - from exploratory studies to regulated clinical programs.

Founded in 2013, AccuraScience was the first U.S.-based bioinformatics service company offering broad-spectrum customized solutions to academic and industry researchers.

Our team of senior bioinformaticians brings over 200 years of combined experience, with deep biological insight and computational rigor.

We’ve successfully completed projects for 180+ research institutions, contributed to NIH-funded grants, and supported numerous peer-reviewed publications and clinical applications.

🔬 Short-Read Sequencing & Core Omics Analysis

• - Whole-genome and exome data - genome assembly, precise variant calling, copy number detection
• - Targeted panels & amplicons - high-confidence variant calls, depth/coverage QC, low-frequency detection
• - RNA-seq - expression quantification, differential testing, splicing analysis, de novo assembly, variant-aware quantification
• - Epigenomics - ATAC-seq, ChIP-seq, CUT&Tag, CUT&RUN, Hi-C (our expert’s guide on ATAC-seq & CUT&Tag)
• - DNA methylation - WGBS, RRBS, EPIC array, scBS-seq (common pitfalls blog)

🧬 Single-Cell & Spatial Transcriptomics

• - Single-cell RNA-seq – scRNA-seq analysis, clustering, DE, trajectory (scRNA-seq analysis blog)
• - 10X Single-Cell Multiome – joint scRNA + scATAC, gene activity inference (10X Multiome blog)
• - Spatial Transcriptomics – Visium, Xenium, CosMx, spatial domain and DE (spatial analysis guide)
• - Multi-Omics Integration – RNA, ATAC, methylation, proteomics, metabolomics (multi-omics integration blog)

🧬 Long-Read Sequencing & Hybrid Genome Analysis

• - Genome assembly & structural variant detection - tuned Flye/Canu pipelines, multi-round polishing (long-read genome assembly blog)
• - Full-length RNA isoform analysis - Iso-Seq, direct RNA, chimera removal, clustering, comparison to RefSeq
• - Base modification detection - long-read methylation, cross-platform validation
• - Hybrid assemblies - optimized integration of short- and long-read data (hybrid integration blog)

🧪 GWAS, EWAS, TWAS, and Population-Level Analysis

• - Full pipeline support - from raw data through final association tables and figures
• - Confounder correction - population structure, rare variants, LD inflation, summary stat interpretation (GWAS essentials blog; GWAS pitfalls blog; Beyond GWAS blog)

🤖 AI & Machine Learning

• - Cancer subtyping, biomarker discovery, image-based diagnostics (CNNs, etc)
• - Drug response modeling, multi-omics predictors, LLMs in biology
• - SVM, random forest, neural networks, transformer models (AI modeling tips; 10 real-world AI use cases)

🔬 AlphaFold & Structural Modeling

• - AlphaFold 2 and 4 structure prediction, domain annotation, and binding interface modeling
• - Post-prediction refinement with FoldX, Rosetta, or AutoDock (AlphaFold 2 blog; AlphaFold 4 blog; Challenges in AlphaFold Modeling and Beyond)

🦠 Microbiome & Metagenomics

• - 16S and shotgun metagenomics - taxonomic profiling, functional annotation, alpha/beta diversity, host-microbe associations (microbiome analysis guide)

🧫 Proteomics & Mass Spectrometry

• - Quantitative proteomics - DIA, TMT pipelines, differential abundance
• - Robust pre-processing - imputation, normalization, batch effect removal (solving proteomics analysis challenges)

🧪 Metabolomics

• - LC-MS, GC-MS, and NMR-based metabolite profiling and quantification
• - Peak deconvolution, normalization, multivariate modeling, and pathway analysis (metabolomics blog)

🛠️ Custom Pipelines & Troubleshooting

• - Resolving alignment, quantification, and QC issues across diverse assays and custom designs
• - Tailoring pipelines for non-standard data, legacy formats, or reviewer-raised concerns

🤖 NIH NAM Grant Support & Modeling

• - NAM-based study design for NIH grants - modeling strategy, human data sourcing, policy alignment
• - Mechanistic and ML model selection, data integration, reviewer-ready justification text (9 NAM examples blog)

📌 Resources & Next Steps

• ➡️ - Meet Our Team - 200+ years of expertise across academia, biotech, and clinical domains
• ➡️ - 10 Reasons to Work With Us - including cost-effectiveness, rigor, and grant/publication support
• ➡️ - Testimonials - direct feedback from clients who’ve published or secured funding
• ➡️ - How It Works - simple, transparent project process
• ➡️ - Pricing - clear deliverables and fair costs
• ➡️ - FAQs - turnaround, file types, what’s included
• ➡️ - Our Blogs - expert insights, technical guides, and analysis pitfalls to avoid
• ➡️ - Send an Inquiry or Chat With Us - let’s discuss your needs today