{"doi":"10.1101/2025.09.01.673517","title":"User-friendly scheduler Using a hybrid architecture and supercomputing for big data processing","abstract":"The exponential growth of omics data requires novel strategies for storage, transfer, and processing of said data. We present a scheduler based on the Temporal.io workflow framework which enables two key optimizations of bioinformatics workflows. Firstly, we enable users to transparently map workflow steps to diverse execution environments, including high-performance computing (HPC) resources managed by the SLURM resource manager through an easy-to-use graphical user interface. Secondly, we enable asynchronous execution of workflows, a feature which guarantees that workflows will achieve reasonable resource utilization even when the scheduler cannot make use of a system's full RAM and CPU resources. Thirdly, we propose a universal, platform agnostic JSON representation of workflows that allows platform-specific execution details to be abstracted away from the core scientific logic. Our work includes a custom executor plugin that supports translation of workflows from an external language, such as Nextflow, to our universal JSON format. Finally, we develop a graphical user interface to make our scheduler easy-to-use for non-technical users. When benchmarked on a bulk RNA sequencing workflow, these features reduced the cost and time requirements. We illustrated the merits of our cross-platform method using credit allocations from federally funded supercomputers.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":574080,"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":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9552,"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":1481573,"name":"Varun Mittal","orcid":"0009-0000-8531-8912","position":1,"is_corresponding":false},{"id":1481574,"name":"Bryce Fukuda","orcid":"0009-0003-7203-5261","position":2,"is_corresponding":false},{"id":568618,"name":"Ka Yee Yeung","orcid":"0000-0002-1754-7577","position":3,"is_corresponding":false},{"id":568617,"name":"Ling‐Hong Hung","orcid":"0000-0002-5209-2248","position":4,"is_corresponding":false},{"id":1481881,"name":"P.S. McKeever","orcid":null,"position":0,"is_corresponding":true}],"reference_count":13,"raw_metadata":null,"created_at":"2026-07-19T02:57:40.686992Z","pmid":"40950027","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":[]}