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ISLET: individual-specific reference panel recovery improves cell-type-specific inference

We propose a statistical framework ISLET to infer individual-specific and cell-type-specific transcriptome reference panels. ISLET models the repeatedly measured bulk gene expression data, to optimize the usage of shared information within each subject. ISLET is the first available method to achieve...

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Autores principales: Feng, Hao, Meng, Guanqun, Lin, Tong, Parikh, Hemang, Pan, Yue, Li, Ziyi, Krischer, Jeffrey, Li, Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373385/
https://www.ncbi.nlm.nih.gov/pubmed/37496087
http://dx.doi.org/10.1186/s13059-023-03014-8
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author Feng, Hao
Meng, Guanqun
Lin, Tong
Parikh, Hemang
Pan, Yue
Li, Ziyi
Krischer, Jeffrey
Li, Qian
author_facet Feng, Hao
Meng, Guanqun
Lin, Tong
Parikh, Hemang
Pan, Yue
Li, Ziyi
Krischer, Jeffrey
Li, Qian
author_sort Feng, Hao
collection PubMed
description We propose a statistical framework ISLET to infer individual-specific and cell-type-specific transcriptome reference panels. ISLET models the repeatedly measured bulk gene expression data, to optimize the usage of shared information within each subject. ISLET is the first available method to achieve individual-specific reference estimation in repeated samples. Using simulation studies, we show outstanding performance of ISLET in the reference estimation and downstream cell-type-specific differentially expressed genes testing. We apply ISLET to longitudinal transcriptomes profiled from blood samples in a large observational study of young children and confirm the cell-type-specific gene signatures for pancreatic islet autoantibody. ISLET is available at https://bioconductor.org/packages/ISLET. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03014-8.
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spelling pubmed-103733852023-07-28 ISLET: individual-specific reference panel recovery improves cell-type-specific inference Feng, Hao Meng, Guanqun Lin, Tong Parikh, Hemang Pan, Yue Li, Ziyi Krischer, Jeffrey Li, Qian Genome Biol Method We propose a statistical framework ISLET to infer individual-specific and cell-type-specific transcriptome reference panels. ISLET models the repeatedly measured bulk gene expression data, to optimize the usage of shared information within each subject. ISLET is the first available method to achieve individual-specific reference estimation in repeated samples. Using simulation studies, we show outstanding performance of ISLET in the reference estimation and downstream cell-type-specific differentially expressed genes testing. We apply ISLET to longitudinal transcriptomes profiled from blood samples in a large observational study of young children and confirm the cell-type-specific gene signatures for pancreatic islet autoantibody. ISLET is available at https://bioconductor.org/packages/ISLET. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03014-8. BioMed Central 2023-07-26 /pmc/articles/PMC10373385/ /pubmed/37496087 http://dx.doi.org/10.1186/s13059-023-03014-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Feng, Hao
Meng, Guanqun
Lin, Tong
Parikh, Hemang
Pan, Yue
Li, Ziyi
Krischer, Jeffrey
Li, Qian
ISLET: individual-specific reference panel recovery improves cell-type-specific inference
title ISLET: individual-specific reference panel recovery improves cell-type-specific inference
title_full ISLET: individual-specific reference panel recovery improves cell-type-specific inference
title_fullStr ISLET: individual-specific reference panel recovery improves cell-type-specific inference
title_full_unstemmed ISLET: individual-specific reference panel recovery improves cell-type-specific inference
title_short ISLET: individual-specific reference panel recovery improves cell-type-specific inference
title_sort islet: individual-specific reference panel recovery improves cell-type-specific inference
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373385/
https://www.ncbi.nlm.nih.gov/pubmed/37496087
http://dx.doi.org/10.1186/s13059-023-03014-8
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