{"doi":"10.1007/978-1-4939-9240-9_5","title":"Single-Cell RNA-Seq by Multiple Annealing and Tailing-Based Quantitative Single-Cell RNA-Seq (MATQ-Seq)","abstract":null,"journal":"Methods in Molecular Biology","year":2019,"id":593299,"datarank":0.6811680785566903,"base_score":2.772588722239781,"endowment":2.772588722239781,"self_citation_contribution":0.41588830833596724,"citation_network_contribution":0.265279770220723,"self_endowment_contribution":0.41588830833596724,"citer_contribution":0.265279770220723,"corpus_percentile":null,"corpus_rank":null,"citation_count":15,"citer_count":14,"citers_with_citation_signal":11,"citers_with_endowment":11,"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":68992,"name":"Chenghang Zong","orcid":"0000-0002-8337-8038","position":1,"is_corresponding":false},{"id":552685,"name":"Kuanwei Sheng","orcid":"0000-0002-7155-9915","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Single-Cell RNA-Seq by Multiple Annealing and Tailing-Based Quantitative Single-Cell RNA-Seq (MATQ-Seq)","abstract":"Single-cell technologies have emerged as advanced tools to study various biological processes that demand the single cell resolution. To detect subtle heterogeneity in the transcriptome, high accuracy and sensitivity are still desired for single-cell RNA-seq. We describe here multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq) with ~90% capture efficiency. In addition, MATQ-seq is a total RNA assay allowing for detection of nonpolyadenylated transcripts.","is_dataset_classified":null,"base_score":2.772588722239781,"endowment":2.772588722239781,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"31028632","pmcid":null,"openalex_id":"https://openalex.org/W2942193912","authors":[],"funders":[{"funder_name":"NIBIB NIH HHS","grant_id":"DP2 EB020399","title":null}],"total_grants":1,"fwci":1.9095,"citation_percentile":0.87428826,"influential_citations":0,"citation_trend":[{"year":2019,"count":1},{"year":2020,"count":1},{"year":2021,"count":2},{"year":2022,"count":2},{"year":2023,"count":3},{"year":2024,"count":3},{"year":2025,"count":1},{"year":2026,"count":2}],"oa_status":"closed","license":"http://www.springer.com/tdm","oa_locations":[{"url":"http://link.springer.com/content/pdf/10.1007/978-1-4939-9240-9_5","host_type":"publisher"},{"url":"https://doi.org/10.1007/978-1-4939-9240-9_5","host_type":"book series"},{"url":"https://pubmed.ncbi.nlm.nih.gov/31028632","host_type":"repository"}],"fields_of_study":["Single-cell and spatial transcriptomics","Molecular Biology Techniques and Applications","RNA Research and Splicing"],"mesh_terms":["Animals","Humans","RNA","Gene Library","Sequence Analysis, RNA","DNA, Complementary","Gene Expression Profiling","Reverse Transcription","Single-Cell Analysis","Transcriptome"],"keywords":["RNA-Seq","Single-cell analysis","RNA","Transcriptome","Cell","Computational biology","Biology","Gene","Gene expression","Genetics","Biotechnology","Single cell","Total RNA","Transcriptomics","Library Preparation"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-26T19:49:44.937854Z","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":[]}