{"doi":"10.1145/3765612.3767790","title":"AtlasCollect: A Single Cell Data Atlas platform and Unified Platform for Datasets Collection and Integration","abstract":"Single-cell datasets typically represent heterogeneous populations and require meticulous computational approaches for in-depth analysis, but more importantly, given the explosion in single cell data generation, a crucial need arises for integration of data and analysis on atlas levels. Several tools exist to collect experimental single-cell data in the form of raw sequencing data files and experiment-level metadata, such as GEO Archive and Sequence Read Archive (SRA)[3]. Other tools or packages are available for performing cell-level analysis of individual datasets, such as Loupe Browser (10x Genomics), Seurat[5], and SC1[4]. Finally, there are \"atlases,\" which typically display datasets as one integrated dataset with extensive cell-level metadata and 'pseudo-bulk' level insights. However, there are currently no atlas development tools that allow for interactive and dynamic aggregation of single cell datasets that comprehensively collect and curate single cell sequencing datasets while simultaneously allowing for interactive datasets integration and assessment of integration effects. In this work we present 'AtlasCollect', an innovative web-based interactive platform designed to streamline the collection, mapping, and live integration of single-cell RNA sequencing (scRNA-seq) data developed using the Next.js framework as well as R custom code and packages. Our tool provides a user-friendly interface that simplifies complex data management using SQLite and file systems, automates exploratory analysis workflows for data validation and visualization, and offers a centralized hub for various integration algorithms. A key strength of this platform lies in its interfacing with multiple established dataset integration methods, including CCA [6], Harmony[2], Joint PCA [6], and RPCA [1]. Furthermore, our platform facilitates seamless integration with downstream comprehensive analysis platforms and frameworks such as Seurat[5] and SC1[4] and addresses challenges related to batch effects. To conclude, the AtlasCollect platform aims to empower researchers with varying levels of computational expertise to gain immediate insights into cellular heterogeneity and gene expression dynamics of dataset collectives.","journal":null,"year":2025,"id":584821,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":0.0,"corpus_rank":10062,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9085,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":38392,"name":"Marmar R. Moussa","orcid":"0000-0003-0574-6656","position":1,"is_corresponding":false},{"id":1470655,"name":"Olajumoke B. Oladapo","orcid":"0009-0009-3562-7587","position":2,"is_corresponding":false},{"id":1497933,"name":"Youla Ali","orcid":"0009-0001-0276-6486","position":3,"is_corresponding":false},{"id":1497934,"name":"Nicholas Louque","orcid":"0009-0001-6674-3160","position":4,"is_corresponding":false},{"id":1497935,"name":"Suryaveer Kapoor","orcid":"0009-0004-7995-6896","position":5,"is_corresponding":false},{"id":1497932,"name":"Sriram Boddeda","orcid":"0009-0005-3262-9561","position":0,"is_corresponding":true}],"reference_count":2,"raw_metadata":null,"created_at":"2026-07-19T02:59:16.166424Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}