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BxGenomics Bulk RNA-Seq View Now Covers 56,000+ Projects — Here's What's New

Published by Susan @ June 15, 2026, 6:28 pm

We are excited to announce a significant expansion of the BxGenomics Bulk RNA-Seq View database. This update brings a dramatically larger collection of public RNA-Seq datasets to researchers, making BxGenomics one of the most comprehensive online platforms for transcriptomics data mining. In this update, over 31,000 new projects covering over 890,000 samples have been added to the platform (Table 1).

The database now contains nearly 1.82 million samples across more than 56,400 projects — roughly doubling the scope of what was available before. The most substantial additions come from recent years of RNA-Seq research. The update brings full coverage through 2025, with the largest waves of new data coming from 2021–2024. The previous database had limited coverage beyond 2021, with only 5 projects from 2022 and none beyond. This update closes that gap entirely, ensuring researchers have access to the latest publicly available transcriptomics data. The growth is balanced across both supported species. Of the newly added projects, approximately 15,000+ are human and 15,000+ are mouse — reflecting BxGenomics' commitment to serving the full breadth of biomedical and basic science research communities. 

  Previous Database Updated Database Change
Total Projects 25,247 56,452 +124%
Total Samples ~929,000 ~1,820,000 +96%
Human Projects 12,083 27,573 +128%
Mouse Projects 13,164 28,879 +119%
Journals Represented 770 1,285 +67%
 

Table 1. Updates of Bulk RNA-Seq View

The datasets in BxGenomics Bulk RNA-Seq View now come from publications spanning 1,285 peer-reviewed journals — up from 770 in the previous version — reflecting the full breadth of the biomedical research community. This breadth ensures that whatever your research focus — development, immunology, oncology, neuroscience, metabolism, or beyond — BxGenomics is likely to contain relevant published datasets ready to explore. The collection draws from high-impact journals across genomics, cell biology, immunology, cancer research, and beyond, including:

Nature Communications, Cell Reports, Nature, Scientific Reports, eLife, PNAS, Frontiers in Immunology, Cell, Science Advances, Nucleic Acids Research, iScience, JCI Insight, Journal of Clinical Investigation, Molecular Cell, Cell Stem Cell, Journal of Experimental Medicine, Cancer Research, Stem Cell Reports, Nature Immunology, Immunity, International Journal of Molecular Sciences, PLoS ONE, Cell Death & Disease, Communications Biology, Science, Blood, Nature Cell Biology, Genes & Development, Cancer Cell, Oncogene, and hundreds more.

The updated database includes projects across the full spectrum of experimental scale, from small focused studies to large consortium-scale datasets. The majority of the 56,400+ projects reflect individual laboratory publications, while nearly 1,900 projects contain over 100 samples each — including consortium-scale studies exceeding 200 samples. This diversity means BxGenomics serves both researchers seeking targeted datasets for specific biological questions and those interested in large population-level or disease cohort analysis.

What This Means For You

With this update, BxGenomics Bulk RNA-Seq View now provides over 56,000 human and mouse RNA-Seq projects — all accessible without writing a single line of code (Fig.1). Whether you are:

  • Exploring gene expression across published datasets before designing your own experiment
  • Mining public data to validate findings or generate new hypotheses
  • Running DEG analysis on a dataset of interest using limma or DESeq2
  • Visualizing results through QuickOmics with publication-ready PCA plots, volcano plots, heatmaps, and pathway overlays

Figure 1. Dashboard of BxGenomics Bulk RNA-Seq View.

Getting Started

Ready to explore? Head to the BxGenomics Bulk RNA-Seq View to browse the full updated catalog. Use the search and filter tools to find datasets by keyword, species, or sample size — then jump straight into viewing the data or doing a DEG Analysis with one click. No bioinformatics background required. Just curiosity.