{"doi":"10.1186/s13059-021-02434-8","title":"Specific splice junction detection in single cells with SICILIAN","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>Precise splice junction calls are currently unavailable in scRNA-seq pipelines such as the 10x Chromium platform but are critical for understanding single-cell biology. Here, we introduce SICILIAN, a new method that assigns statistical confidence to splice junctions from a spliced aligner to improve precision. SICILIAN is a general method that can be applied to bulk or single-cell data, but has particular utility for single-cell analysis due to that data’s unique challenges and opportunities for discovery. SICILIAN’s precise splice detection achieves high accuracy on simulated data, improves concordance between matched single-cell and bulk datasets, and increases agreement between biological replicates. SICILIAN detects unannotated splicing in single cells, enabling the discovery of novel splicing regulation through single-cell analysis workflows.</jats:p>","journal":"Genome Biology","year":2021,"id":635577,"datarank":0.47670807455219194,"base_score":3.1780538303479458,"endowment":3.1780538303479458,"self_citation_contribution":0.47670807455219194,"citation_network_contribution":0.0,"self_endowment_contribution":0.47670807455219194,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":23,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":74096,"name":"Julia Eve Olivieri","orcid":null,"position":1,"is_corresponding":false},{"id":1649052,"name":"Ana Damljanovic","orcid":null,"position":2,"is_corresponding":false},{"id":558818,"name":"Julia Salzman","orcid":"0000-0001-7630-3436","position":3,"is_corresponding":false},{"id":74091,"name":"Roozbeh Dehghannasiri","orcid":"0000-0001-7413-3437","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Specific splice junction detection in single cells with SICILIAN","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>Precise splice junction calls are currently unavailable in scRNA-seq pipelines such as the 10x Chromium platform but are critical for understanding single-cell biology. Here, we introduce SICILIAN, a new method that assigns statistical confidence to splice junctions from a spliced aligner to improve precision. SICILIAN is a general method that can be applied to bulk or single-cell data, but has particular utility for single-cell analysis due to that data’s unique challenges and opportunities for discovery. SICILIAN’s precise splice detection achieves high accuracy on simulated data, improves concordance between matched single-cell and bulk datasets, and increases agreement between biological replicates. SICILIAN detects unannotated splicing in single cells, enabling the discovery of novel splicing regulation through single-cell analysis workflows.</jats:p>","is_dataset_classified":null,"base_score":3.1780538303479458,"endowment":3.1780538303479458,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"34353340","pmcid":"PMC8339681","openalex_id":"https://openalex.org/W3189355494","authors":[],"funders":[{"funder_name":"National Cancer Institute","grant_id":"R25 CA180993","title":null},{"funder_name":"National Science Foundation","grant_id":"DGE-1656518","title":null},{"funder_name":"National Science Foundation","grant_id":"MCB1552196","title":null},{"funder_name":"National Institute of General Medical Sciences","grant_id":"R01 GM116847","title":null},{"funder_name":"U.S. National Library of Medicine","grant_id":"T15 LM7033-36","title":null},{"funder_name":"NIGMS NIH HHS","grant_id":"R35 GM139517","title":null},{"funder_name":"NLM NIH HHS","grant_id":"T15 LM007033","title":null},{"funder_name":"National Science Foundation","grant_id":"1552196","title":"CAREER: Dissecting the Biogenesis and Function of Circular RNA in Simple Eukaryotes"},{"funder_name":"National Institutes of Health","grant_id":"5R01GM116847-05","title":"Unbiased discovery of mechanisms regulating circRNA"},{"funder_name":"National Institutes of Health","grant_id":"5R25CA180993-02","title":"Cancer Systems Biology Scholars Program"},{"funder_name":"National Institutes of Health","grant_id":"5T15LM007033-36","title":"Biomedical Informatics Training at Stanford"},{"funder_name":"Alfred P. Sloan Foundation","grant_id":"","title":null},{"funder_name":"McCormick Foundation","grant_id":"","title":null},{"funder_name":"Baxter International Foundation","grant_id":"","title":null}],"total_grants":14,"fwci":1.4809,"citation_percentile":0.82387467,"influential_citations":0,"citation_trend":[{"year":2021,"count":4},{"year":2022,"count":5},{"year":2023,"count":3},{"year":2024,"count":8},{"year":2025,"count":1},{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://genomebiology.biomedcentral.com/track/pdf/10.1186/s13059-021-02434-8","host_type":"journal"},{"url":"https://genomebiology.biomedcentral.com/track/pdf/10.1186/s13059-021-02434-8","host_type":"publisher"},{"url":"https://link.springer.com/content/pdf/10.1186/s13059-021-02434-8.pdf","host_type":"publisher"},{"url":"https://link.springer.com/article/10.1186/s13059-021-02434-8/fulltext.html","host_type":"publisher"},{"url":"https://doi.org/10.1186/s13059-021-02434-8","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/34353340","host_type":"repository"},{"url":"https://scholarlycommons.pacific.edu/soecs-facarticles/309","host_type":"repository"},{"url":"https://doaj.org/article/4dee55d25b49435aad4876e037e96258","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8339681","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC8339681","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC8339681?pdf=render","host_type":"Europe_PMC"},{"url":"http://dx.doi.org/10.1186/s13059-021-02434-8","host_type":""},{"url":"https://dx.doi.org/10.1186/s13059-021-02434-8","host_type":""}],"fields_of_study":["Single-cell and spatial transcriptomics","RNA Research and Splicing","Molecular Biology Techniques and Applications","0301 basic medicine","0303 health sciences","03 medical and health sciences"],"mesh_terms":["Algorithms","Animals","Humans","RNA Splicing","Alternative Splicing","Sequence Analysis, RNA","Entropy","Computational Biology","Mice","Single-Cell Analysis"],"keywords":["splice","Computational biology","Biology","Sicilian","Alternative splicing","RNA splicing","Genetics","Computer science","Gene","Exon","QH301-705.5","Sequence Analysis, RNA","Entropy","Short Report","QH426-470","Mice","Animals","Humans","Biology (General)","Single-Cell Analysis","Algorithms"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"geo"},{"name":"arrayexpress"},{"name":"ega"},{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T15:19:15.132382Z","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":[]}