biostudies-literatureMa WFAmerican Heart AssociationNCATS NIH HHSFondation LeducqNHLBI NIH HHSNational Institutes of Health12-22https://www.ebi.ac.uk/biostudies/studies/S-EPMC8919504biostudies-literatureUnknown340<h4>Background and aims</h4>The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets.<h4>Methods</h4>Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploratiAtherosclerosisEnhanced single-cell RNA-seq workflow reveals coronary artery disease cellular cross-talk and candidate drug targets.PMC8919504R01 HL155165UL1 TR001873R01 HL156849R01 HL132904R01 HL136314R01 HL150359K12HL143959T32HL007284R01 HL148239R00 HL125912R01HL148239POST35120545R00HL125912T32 HL007284K12 HL143959Miller CLGancayco CReilly MPMosquera JVLigay AVHodonsky CJSlenders LLi MTurner AWWong DPan HMa WFBarrientos NBMai Dvan der Laan SWPasterkamp GOwsiany KAlencar GFOwens GKMokry MKhomtchouk BBSong YfalseEnhanced single-cell RNA-seq workflow reveals coronary artery disease cellular cross-talk and candidate drug targets.<h4>Background and aims</h4>The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets.<h4>Methods</h4>Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further explorati2022-01-01T00:00:00Z2022 Jan2026-05-28T12:54:44.142Z2025-02-18T22:34:38.274ZS-EPMC89195043487181610.1016/j.atherosclerosis.2021.11.025