Single-cell sequencing is a powerful technology that offers a focused approach to biomarker and target discovery. If you're working in oncology research, you most likely use it to develop new diagnostic biomarkers or anti-tumor treatments. If you study the immune system, you may use it to detect individual immune cells or to distinguish among different immune cell groups to propose new targets for disease treatment.
Yet, if you work with single-cell sequencing data, you know that beyond the many possibilities lie many challenges. You probably obtain single-cell RNA-seq (scRNA-seq) data from multiple programs and disease indications, and from both publicly and internally generated data. These data are difficult to integrate and align. What's more, the sheer volume of data and noise within each dataset make it extremely challenging to draw meaningful conclusions.
QIAGEN Discovery Bioinformatics Services eases the challenges of working with single-cell sequencing data to quickly and efficiently help answer questions relevant to your research goals. Our team supplements your workforce with our bioinformatics experts and performs analyses tailored to your interests. We offer a range of support, such as building custom pipelines and server solutions, as well as provide hypercare support and training. We take on everything from secondary analysis services to in-depth analysis of biological data.
Need support with content curation? Leave it up to us, whether it's literature, datasets, pathways or a customized integrated 'omics data collection based on your internal data ('internal Land'). We'll perform deep meta-analysis on data collections and take on the bulk data processing. By working with us, you'll save time organizing and visualizing internal pipelines and results so you can focus on validating your hypothesis to more quickly make your next big discovery.
In addition to our basic services, our custom-built single-cell analysis pipelines incorporate cutting-edge public and/or proprietary bioinformatics tools to identify rare cell types, track cell lineage, infer developmental trajectories and determine inter-cellular interactions of single cells. We do this using data from many single-cell sequencing methods, such as cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), assay for transposase-accessible chromatin by sequencing (ATAC-seq), single-cell T cell receptor sequencing (scTCR-seq) and single nucleus RNA sequencing (snRNA-seq), among others. Our experts query the OmicSoft Single Cell Land database to answer your specific biological questions, such as:
Figure 1. Example output showing the abundance of different cell types across datasets.
General challenges of analyzing scRNA-seq data
We design our pipelines to handle your most common scRNA-seq analysis challenges. These challenges include the relatively small number of sequencing reads, the sparsity of data, limited processing power and cell population heterogeneity. Gene expression profiling by scRNA-seq is also inherently noisier than bulk RNA-seq, making effective data analysis more complicated. To address these caveats of working with scRNA-seq data, we:
Figure 2. CellMap employing dimension reduction to explore cell types across samples.
Metadata curation challenges
Another challenge of scRNA-seq data is metadata curation. Due to a lack of standards for the deposition of cell-level metadata, you could end up spending the majority of your time processing data and curating metadata. Why not let our team of curators handle the metadata? Our team of experts can manually curate single-cell projects and precisely curate cell clusters to help you more quickly and easily answer your biological questions. To do this, we:
Differential expression analysis challenges
After identifying the cell type identities of the scRNA-seq clusters, you'd typically perform differential expression analysis between conditions within particular cell types. While commercial algorithms perform differential expression analysis, the p-values from these analyses are often inflated because a cell is treated as a sample. Since single cells within a sample have variation, we can compare gene expression across individual cells. This is known as pseudo-bulk RNA-seq data. Our team implements this approach to create a custom pseudo-bulk integrated 'omics data collection ('Land') so you can easily explore single-cell data to make accurate comparisons.
Figure 3. Explore pre-computed differential expression of marker genes in different cell types, to understand how a target gene differentially expressed in different cell clusters. In this example output, you can see the differential expression of CD34 across different cell types in normal vs. hematologic cancer samples.
On all our projects, we work with you to determine the output and deliverables that best fit your needs. Here are some examples of our deliverables that'll support your work using single-cell technologies:
Figure 4. Single-cell project workflow.
By working with QIAGEN Discovery Bioinformatics Services on projects for scRNA-seq processing, you'll save time and increase accuracy to more quickly gain a robust and insightful understanding of complex disease. We'll take on the aspects of your bioinformatics that are most challenging and limiting for you. Our customized support empowers you to more readily gain a robust and insightful understanding of the biological mechanisms in your data, to accelerate and drive your next big discovery.
Would you like to reduce the burden of working with scRNA-seq data to more quickly reach your next biomarker or target discovery? Learn more and request a consultation about our range of bioinformatics services that'll extend and scale your in-house resources. Contact us today at QDIservices@qiagen.com to get your custom single-cell project started. Together, let's unravel the biological discoveries hidden in single cells.
Are you a scientist or public health lab professional studying viral host response? Do you find it challenging to find high-quality curated information on gene expression studies from viral host response to advance and deepen your insights and accelerate your research? Or maybe you need a way to combine all the potentially valuable data you find in the public domain but don't know where to start? QIAGEN Discovery Bioinformatics Services is launching a new offering that makes such data readily available with only a few clicks of your mouse. QIAGEN Viral Land represents a highly curated and re-processed collection of high-value human viral host and viral vaccine RNA-seq and microarray expression data, harmonized into a single platform. This dataset represents 201 projects, spanning over 15,000 samples examining viral-host and vaccine research, with the ultimate goal of helping researchers and academic and public health labs generate hypotheses using the wealth of data available in the public domain. This new gene expression database on viral studies leverages a simple-to-use web portal, known as QIAGEN OmicSoft Land Explorer, to:
The new Viral Land delivers web-based access to public gene expression studies. The samples are easily visualized and can be grouped or filtered by sample annotations, such as study type (used for host response or vaccine response), virus classifications, tissue, cell type and more.
The Land Explorer web design allows you to interrogate the expression of one or more genes in a single public study as well as multiple studies that have been processed in the same way. For example, IL6 is highly expressed in tissues from hosts infected with coronavirus and influenza (Blanco-Melo D. et al.; Figure 1 left). Further examination of a collection of eight viral host studies checking for IL6 expression reveals that IL6 is also highly expressed in blood derived from individuals infected with Zika and dengue relative to uninfected.
Accelerate your antiviral host response research. Request a consultation on Viral Land from our experts today, and visit us here for more information about QIAGEN Discovery Bioinformatics Services.
Reference:
Blanco-Melo D., et al. (2020) Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19. Cell 181(5):1036-1045.
Need to expand your bioinformatics and curation expertise to harness the power of ‘omics data? Let QIAGEN Discovery Bioinformatics Services help.
Not all research teams have the time and in-house expertise to leverage the power of complex and high-volume ‘omics data, and many organizations lack workforce resources or server and infrastructure support. These limitations create bottlenecks, leaving research goals that don’t advance.
QIAGEN Discovery Bioinformatics Services can reduce the burden of broadening your in-house bioinformatics capabilities. We offer complete Sample to Insight workflows and tools which work together to reveal deep insights into your biological questions. Our team uses best-in-class bioinformatics tools and solutions from QIAGEN Digital Insights to support your projects and goals, whatever your needs may be.
Discover the benefits of partnering with a leading provider of bioinformatics tools and services for discovery research scientists:
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Dr. Philip James, Ph.D., Senior Researcher at a small research institute called Nofima, was confronted with several challenges associated with access to analytics tools when studying the effect of diet on gene regulation in sea urchins, including processing and pathway analysis of RNA-seq data. He also needed to put the results into a biological context.
Dr. James found partnering with QIAGEN Discovery Bioinformatics Services a reliable and convenient way to extend in-house resources, with our expertise and tailored bioinformatic services ensuring time savings and high-quality results.
Inspirational and groundbreaking science is often unorthodox and tricky, even concerning bioinformatics research. Follow the journey of partnering with QIAGEN Discovery Bioinformatics Services, from initial contact and delivery of data analysis to submission for publication.
