dc.contributor.author | Magness, A | |
dc.contributor.author | Colliver, E | |
dc.contributor.author | Enfield, KSS | |
dc.contributor.author | Lee, C | |
dc.contributor.author | Shimato, M | |
dc.contributor.author | Daly, E | |
dc.contributor.author | Moore, DA | |
dc.contributor.author | Sivakumar, M | |
dc.contributor.author | Valand, K | |
dc.contributor.author | Levi, D | |
dc.contributor.author | Hiley, CT | |
dc.contributor.author | Hobson, PS | |
dc.contributor.author | van Maldegem, F | |
dc.contributor.author | Reading, JL | |
dc.contributor.author | Quezada, SA | |
dc.contributor.author | Downward, J | |
dc.contributor.author | Sahai, E | |
dc.contributor.author | Swanton, C | |
dc.contributor.author | Angelova, M | |
dc.coverage.spatial | England | |
dc.date.accessioned | 2024-09-13T14:52:33Z | |
dc.date.available | 2024-09-13T14:52:33Z | |
dc.date.issued | 2024-06-15 | |
dc.identifier | ARTN 5135 | |
dc.identifier | 10.1038/s41467-024-48870-5 | |
dc.identifier.citation | Nature Communications, 2024, 15 (1), pp. 5135 - | en_US |
dc.identifier.issn | 2041-1723 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/6391 | |
dc.identifier.eissn | 2041-1723 | |
dc.identifier.eissn | 2041-1723 | |
dc.identifier.doi | 10.1038/s41467-024-48870-5 | |
dc.identifier.doi | 10.1038/s41467-024-48870-5 | |
dc.description.abstract | The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights. | |
dc.format | Electronic | |
dc.format.extent | 5135 - | |
dc.language | eng | |
dc.language.iso | eng | en_US |
dc.publisher | NATURE PORTFOLIO | en_US |
dc.relation.ispartof | Nature Communications | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_US |
dc.subject | Humans | |
dc.subject | Deep Learning | |
dc.subject | Image Processing, Computer-Assisted | |
dc.subject | Animals | |
dc.subject | Software | |
dc.subject | Spatial Analysis | |
dc.subject | Single-Cell Analysis | |
dc.subject | Phenotype | |
dc.subject | Mice | |
dc.subject | Image Cytometry | |
dc.title | Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX. | en_US |
dc.type | Journal Article | |
dcterms.dateAccepted | 2024-05-16 | |
dc.date.updated | 2024-09-13T14:51:01Z | |
rioxxterms.version | VoR | en_US |
rioxxterms.versionofrecord | 10.1038/s41467-024-48870-5 | en_US |
rioxxterms.licenseref.startdate | 2024-06-15 | |
rioxxterms.type | Journal Article/Review | en_US |
pubs.author-url | https://www.ncbi.nlm.nih.gov/pubmed/38879602 | |
pubs.issue | 1 | |
pubs.organisational-group | ICR | |
pubs.organisational-group | ICR/Primary Group | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions/Cancer Biology | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions/Cancer Biology/Lung Cancer Group | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions/Closed research teams | |
pubs.organisational-group | ICR/Primary Group/ICR Divisions/Closed research teams/Lung Cancer Group | |
pubs.publication-status | Published online | |
pubs.publisher-url | http://dx.doi.org/10.1038/s41467-024-48870-5 | |
pubs.volume | 15 | |
icr.researchteam | Lung Cancer Group | en_US |
dc.contributor.icrauthor | Downward, Julian David Harry | |
icr.provenance | Deposited by Mr Arek Surman on 2024-09-13. Deposit type is initial. No. of files: 1. Files: Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX.pdf | |