Imaging-based platforms like Xenium® and MERFISH® visualize transcripts directly in cells using in situ hybridization for single-cell resolution, while sequencing-based platforms like Visium® capture RNA from barcoded spots and computationally map it back to tissue, trading some resolution for [...]
iSCanGuide™ eliminates the bottleneck in single-cell analysis, rapidly converting raw sequencing output into cell identity. Key Takeaways Single-cell RNA-seq analysis lets researchers resolve individual cell types, states, and transitions, but the analytical workflow required to get there [...]
While single-cell RNA sequencing tells you what cell types are present in a tissue, spatial transcriptomics tells you where cells are relative to one another in a tissue. This distinction can change the interpretation of biological data. Key [...]
GPU-Accelerated Platform Unifies Fragmented Workflows, Turning Weeks of Analysis into Minutes ANN ARBOR, MI, May 7, 2026 /PRNewswire/-- Advaita Bio today announced the launch of iSCanGuide™, a cloud-based platform engineered to transform large-scale single-cell and spatial transcriptomics datasets into [...]
A comprehensive review and assessment of pathway analysis methods Genome Biology recently published a peer-reviewed paper containing a comprehensive benchmarking and comparison of 13 widely-used pathway analysis methods across more than 1,000 analyses. We highlight the most important [...]
Pathway Analysis vs Gene Set Analysis What is the Difference and When Should I Use Each? To some, pathway analysis and gene set analysis are synonyms. However, there are important distinctions between these [...]
How do you validate a pathway analysis method? How do you compare such methods? My previous post, Pathway Analysis vs Gene Set Analysis, ended with an interesting question: has anybody really compared side-by-side gene [...]
Not getting much from your pathway analysis? Use Impact Analysis instead of Enrichment alone. How are you currently analyzing your RNASeq and proteomics data? Are you currently using one of the [...]
In bioinformatics, careful attention to detail is critical when analyzing gene expression and protein expression data. One of the most frequent questions we hear is: What background should be used when performing pathway or other gene set enrichment analysis? [...]
Discover how researchers are tackling one of spatial transcriptomics’ biggest computational challenges: multi-slice data alignment and integration. Spatial transcriptomics (ST) enables researchers to map gene expression within the native architecture of tissues, providing unprecedented insight into cellular context, tissue organization, [...]
If you are using or contemplating using single-cell technologies, you may be interested in this review and benchmarking article on cellular deconvolution. Deconvolution is a technique that allows you to get information at the cell type level from bulk RNA [...]
This award will be used to develop advanced methods for the analysis of single cell and spatial genomics and transcriptomics data, while providing life scientists a platform that can provide a one- stop solution that implements the best practices. Ann [...]
We often hear the following question: "Is there any way to know if the whole pathway or the whole GO is upregulated or downregulated? The results table shows p-values and DE numbers, but I want to know if that [...]
You are a life scientist undertaking cutting edge research that involves experiments in which you collect omics data: transcriptomics, genomics, proteomics, methylation, RNASeq, ATACSeq, single cell, etc. You are working on an exciting and very important problem. You have great [...]
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