Alleviating batch effects in cell type deconvolution with SCCAF-D.

Cell type deconvolution methods can impute cell proportions from bulk transcriptomics data, revealing changes in disease progression or organ development. But benchmarking studies often use simulated bulk data from the same source as the reference, which limits its application scenarios. This study examines batch effects in deconvolution and introduces SCCAF-D, a computational workflow that ensures a Pearson Correlation Coefficient above 0.

bia-binder: A web-native cloud compute service for the bioimage analysis community.

We introduce bia-binder (BioImage Archive Binder), an open-source, cloud-architectured, and web-based coding environment tailored to bioimage analysis that is freely accessible to all researchers. The service generates easy-to-use Jupyter Notebook coding environments hosted on EMBL-EBI's Embassy Cloud, which provides significant computational resources. The bia-binder architecture is free, open-source and publicly available for deployment.

The evolution of computational research in a data-centric world.

Computational data-centric research techniques play a prevalent and multi-disciplinary role in life science research. In the past, scientists in wet labs generated the data, and computational researchers focused on creating tools for the analysis of those data. Computational researchers are now becoming more independent and taking leadership roles within biomedical projects, leveraging the increased availability of public data.

CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues.

Motivation: Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods.

Canonical Wnt and TGF-β/BMP signaling enhance melanocyte regeneration but suppress invasiveness, migration, and proliferation of melanoma cells.

Melanoma is the deadliest form of skin cancer and develops from the melanocytes that are responsible for the pigmentation of the skin. The skin is also a highly regenerative organ, harboring a pool of undifferentiated melanocyte stem cells that proliferate and differentiate into mature melanocytes during regenerative processes in the adult. Melanoma and melanocyte regeneration share remarkable cellular features, including activation of cell proliferation and migration.

Expression Atlas update: insights from sequencing data at both bulk and single cell level.

Expression Atlas (www.ebi.ac.

Benchmarking strategies for cross-species integration of single-cell RNA sequencing data.

The growing number of available single-cell gene expression datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Cross-species integration of single-cell RNA-sequencing data has been particularly informative in this context. However, in order to do so robustly it is essential to have rigorous benchmarking and appropriate guidelines to ensure that integration results truly reflect biology.

Simulating structurally variable nuclear pore complexes for microscopy.

Motivation: The nuclear pore complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and an important reference standard in microscopy: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudoatomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single-molecule localization microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability.

Brain Regeneration Resembles Brain Cancer at Its Early Wound Healing Stage and Diverges From Cancer Later at Its Proliferation and Differentiation Stages.

Gliomas are the most frequent type of brain cancers and characterized by continuous proliferation, inflammation, angiogenesis, invasion and dedifferentiation, which are also among the initiator and sustaining factors of brain regeneration during restoration of tissue integrity and function. Thus, brain regeneration and brain cancer should share more molecular mechanisms at early stages of regeneration where cell proliferation dominates. However, the mechanisms could diverge later when the regenerative response terminates, while cancer cells sustain proliferation.

The BioImage Archive - Building a Home for Life-Sciences Microscopy Data.

Despite the huge impact of data resources in genomics and structural biology, until now there has been no central archive for biological data for all imaging modalities. The BioImage Archive is a new data resource at the European Bioinformatics Institute (EMBL-EBI) designed to fill this gap. In its initial development BioImage Archive accepts bioimaging data associated with publications, in any format, from any imaging modality from the molecular to the organism scale, excluding medical imaging.

Single-Cell Analysis Reveals the Immune Characteristics of Myeloid Cells and Memory T Cells in Recovered COVID-19 Patients With Different Severities.

Despite many studies on the immune characteristics of Coronavirus disease 2019 (COVID-19) patients in the progression stage, a detailed understanding of pertinent immune cells in recovered patients is lacking. We performed single-cell RNA sequencing on samples from recovered COVID-19 patients and healthy controls. We created a comprehensive immune landscape with more than 260,000 peripheral blood mononuclear cells (PBMCs) from 41 samples by integrating our dataset with previously reported datasets, which included samples collected between 27 and 47 days after symptom onset.

Expression Atlas update: gene and protein expression in multiple species.

The EMBL-EBI Expression Atlas is an added value knowledge base that enables researchers to answer the question of where (tissue, organism part, developmental stage, cell type) and under which conditions (disease, treatment, gender, etc) a gene or protein of interest is expressed. Expression Atlas brings together data from >4500 expression studies from >65 different species, across different conditions and tissues. It makes these data freely available in an easy to visualise form, after expert curation to accurately represent the intended experimental design, re-analysed via standardised pipelines that rely on open-source community developed tools.

The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences.

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.

Meta-analysis of COVID-19 single-cell studies confirms eight key immune responses.

Several single-cell RNA sequencing (scRNA-seq) studies analyzing immune response to COVID-19 infection have been recently published. Most of these studies have small sample sizes, which limits the conclusions that can be made with high confidence. By re-analyzing these data in a standardized manner, we validated 8 of the 20 published results across multiple datasets.

A proteomics sample metadata representation for multiomics integration and big data analysis.

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets.

REMBI: Recommended Metadata for Biological Images-enabling reuse of microscopy data in biology.

Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.

An integrated landscape of protein expression in human cancer.

Using 11 proteomics datasets, mostly available through the PRIDE database, we assembled a reference expression map for 191 cancer cell lines and 246 clinical tumour samples, across 13 lineages. We found unique peptides identified only in tumour samples despite a much higher coverage in cell lines. These were mainly mapped to proteins related to regulation of signalling receptor activity.

Tumour gene expression signature in primary melanoma predicts long-term outcomes.

Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.

Urinary metabolic phenotyping for Alzheimer's disease.

Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer's Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer's Disease and Mild Cognitive Impairment.

From ArrayExpress to BioStudies.

ArrayExpress (https://www.ebi.ac.