The Stemformatics blood atlas integrates data from different transcriptional platforms, providing the means to draw on the deep functional phenotyping that accompany traditional profiling methods, as well as the high cellular resolution of single cell profiling. The resulting atlas provides a multi-scaled approach to visualise and analyse the relationships between sets of genes and blood cell lineages, including the maturation and activation of leukocytes in vivo and in vitro. Projection of new data onto the atlas allows users to benchmark cell isolation or derivation methods, cell line models, and assess new cell activation states.
When integrating different types of transcriptome data, technical variables such as platform or batch can overwhelm biological signal. Here, we demonstrate that it is possible to combine a large number of different profiling experiments, consisting of 850 samples from 38 platforms, summarised from dozens of laboratories and representing hundreds of donors, to create a molecular map of human blood cells. We achieve robust and unbiased cell type clustering using a variance partitioning method, selecting genes with low platform bias relative to biological variation. The method allows for rapid scaling and integration of new data, creating a resource to annotate and benchmark data drawn from different laboratories, protocols, cell models or methods of measurement.