Expression Atlas update: insights from sequencing data at both bulk and single cell level
Nancy George, Silvie Fexová, Alfonso Munoz Fuentes, Pedro Madrigal, Yalan Bi, Haider Iqbal, Upendra Kumbham, Nadja Nolte, Lingyun Zhao, Anil S. Thanki, Iris Yu, Jose C Marugan Calles, Karoly Erdos, Liora Vilmovsky, Sandeep R Kurri, Anna Vathrakokoili Pournara, David Osumi-Sutherland, Ananth Prakash, Shengbo Wang, Marcela K Tello-Ruiz, Sunita Kumari, Doreen Ware, Damien Goutte-Gattat, Yanhui Hu, Nick Brown, Norbert Perrimon, Juan Antonio Vizcaíno, Tony Burdett, Sarah A. Teichmann, Alvis Brāzma, Irene Papatheodorou
Abstract
Expression Atlas (www.ebi.ac.uk/gxa) and its newest counterpart the Single Cell Expression Atlas (www.ebi.ac.uk/gxa/sc) are EMBL-EBI's knowledgebases for gene and protein expression and localisation in bulk and at single cell level. These resources aim to allow users to investigate their expression in normal tissue (baseline) or in response to perturbations such as disease or changes to genotype (differential) across multiple species. Users are invited to search for genes or metadata terms across species or biological conditions in a standardised consistent interface. Alongside these data, new features in Single Cell Expression Atlas allow users to query metadata through our new cell type wheel search. At the experiment level data can be explored through two types of dimensionality reduction plots, t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP), overlaid with either clustering or metadata information to assist users' understanding. Data are also visualised as marker gene heatmaps identifying genes that help confer cluster identity. For some data, additional visualisations are available as interactive cell level anatomograms and cell type gene expression heatmaps.