Local High-Performance Compute Workstation
At ANGENOVO, we believe that high-throughput bioinformatics doesn’t always need to depend on remote cloud services. That’s why we maintain a dedicated local workstation powered by NVIDIA GPU and high-performance CPUs, enabling in-house processing of large-scale sequencing and omics datasets.
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The NVIDIA RTX delivers outstanding accelerated performance for GPU-enabled pipelines (for example deep-learning models, single-cell data embedding, run‐time-critical processing) and tight integration with our local cluster.
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Because the data never leaves our secure servers, you benefit from lower latency, faster turn-around, and full control over compute resources.
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We optimise our local pipeline for memory-intensive workflows (e.g., single-cell RNA-seq, large metagenomes, proteomic/metabolomic integration) enabling analyses that are not always feasible on generic cloud machines.
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Our infrastructure ensures high reliability and reproducibility: we version all software containers, maintain logs, and provide you full transparency on compute environment, hardware specification, and performance metrics.
Local Computation Pipeline
We have assembled a robust, modular bioinformatics pipeline tailored for life-science research, and fine-tuned for our local infrastructure. Key features include:
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Modular design: Using containerised workflows (e.g., Docker/Singularity), we can plug in custom modules for DNA-seq, RNA-seq, single‐cell, epigenomics, proteomics and metabolomics – as described on our main page.
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Optimised for GPU acceleration: For workflows where GPU acceleration provides major benefit (e.g., embedding high‐dimensional single‐cell transcriptomes, training custom neural networks for variant calling or clustering), our NVIDIA workstation provides a performance edge.
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Scalable local cluster: While the workstation is a key node, we integrate it as part of a local compute cluster with shared storage, fast networking and scheduled job queues — delivering both custom one‐off jobs and batch analyses with efficiency.
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Transparent reporting and reproducibility: Each job produces a detailed report (software versions, hardware utilisation, run-time, QC metrics) and full pipeline logs. You receive not only processed data but also the “provenance” of how it was derived.
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Custom software / scripts: Our team of bioinformaticians not only run standard workflows but can also develop bespoke modules or extend pipelines to your specific research question (e.g., novel variant calling, custom clustering, custom multi‐omics integration).
Data Privacy & Customer Security
We recognise the sensitivity of omics data in life‐science research (human genomics, patient samples, proprietary biotech data). Here’s how we protect your data:
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On-premises data handling: All raw data and intermediate files are stored and processed on our secure internal servers — no third-party cloud provider is required unless explicitly requested by you.
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Access control & encryption: Data at rest is encrypted, and access to servers is limited to authorised bioinformatics personnel. Access logs are maintained and you may request audit trails.
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Confidentiality agreements: We operate under strict confidentiality and are happy to sign NDAs or other data‐use agreements as required by your institution or funding body.
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Data deletion & archiving: After project completion we offer flexible data‐retention policies: you may request we delete or archive raw/intermediate data within a defined timeframe. You retain full ownership of your data and we only act as processor.
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Compliance with relevant regulations: We adhere to relevant Norwegian and EU data‐protection guidelines (including GDPR when applicable) and maintain secure backup systems with controlled access.
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Custom privacy workflows: If you need additional protections (e.g., anonymisation/pseudonymisation of human sample metadata, secure file transfer, isolated processing environment), we can accommodate these workflows tailored to your project.
Accelerate your discoveries with our expert bioinformatics services.
DNA sequencing data analysis
DNA sequencing encompasses a variety of techniques, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and targeted sequencing. These methods allow the investigation of heritable and somatic DNA variants. Beyond next-generation sequencing (NGS) data, SNP and CGH arrays are employed to detect genetic polymorphisms and copy-number variants, respectively. Metagenomic whole-genome sequencing of microbial communities provides insights into their compositions and functions.
We routinely analyze DNA sequence data to address research questions in both basic biology and biomedical settings. Below are some of the typical DNA sequencing data analyses we perform. If you are interested in learning how we can help you maximize the potential of your DNA-seq data, leave us a message, and we will schedule a short call with one of our experts.
RNA sequencing data analysis
Transcriptome-wide analyses of gene expression are highly popular among researchers investigating gene regulation in various biological systems, from single cells to tissues and complex microbiomes. RNA-seq data enables a multitude of analyses, addressing numerous research questions in biology and biomedicine.
Here, we present some of the most common analyses we perform on RNA-seq data. Exploratory, differential expression, and pathway analyses also apply to other high-throughput expression data, such as expression microarray or proteomic data.
We hope the examples below illustrate the vast potential of RNA sequencing. If you are planning an RNA-seq experiment and want to learn how we can help you maximize your data, leave us a message, and we will schedule a short call with one of our experts.
Proteomic and metabolomic data analysis
Computational analysis of proteins and metabolites addresses fundamental questions of biochemistry: Which reactions occur? What is being synthesized? How is energy produced and utilized?
While transcriptomics is often used to infer activities of signaling and metabolic pathways, proteomics and metabolomics provide a more direct view into the key molecules of these pathways and individual reactions.
Proteins and metabolites are typically identified and quantified using mass spectrometry (MS). Alternative methods, such as antibody-based techniques for proteins and nuclear magnetic resonance (NMR) for metabolites, offer lower throughput or less quantitative data at a lower cost compared to MS.
Beyond pathway analyses, proteomic and metabolomic data from patient samples are especially useful for biomarker discovery.
If you are interested in leveraging proteomic and metabolomic data to advance your research, contact us to learn more about our services.
Single-cell RNA sequencing data analysis
Single-cell RNA sequencing (scRNA-seq) is a rapidly advancing and diversifying technology in molecular biology. Studying gene expression at the single-cell level has been as transformative as the advent of bulk RNA sequencing.
Beyond scRNA-seq, several other next-generation sequencing (NGS)-based assays have been adapted for single-cell protocols. These include genomic, proteomic, and epigenetic assays, with single-cell ATAC-sequencing frequently performed alongside scRNA-seq.
Platforms and protocols for scRNA-seq vary in throughput (number of cells) and transcript coverage (3’/5’ tag-based vs. whole-transcript). Our team has extensive experience with a range of technologies, including 10X Genomics, Drop-Seq, the BD Rhapsody system, and protocols from the CEL-Seq and Smart-Seq families.
If you are planning a single-cell sequencing experiment and would like to learn how we can help you maximize your data, please contact us to schedule a short call with one of our experts.
Epigenomic data analysis
Epigenomics characterizes the chromatin state down to the finest chemical modifications. These epigenetic changes to DNA and associated proteins affect gene expression and can lead to altered cellular states, including diseases.
Our team analyzes a wide range of epigenomic sequencing data to gain a deeper understanding of intracellular molecular mechanisms and identify biomarkers for diseases.
If you seek comprehensive insights into epigenetic modifications and their implications, our expertise can help you achieve your research goals. Contact us to learn more about our epigenomics services.