BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty
Abstract Alternative splicing is a biological process during gene expression that allows a single gene to code for multiple proteins. However, splicing patterns can be altered in some conditions or diseases. Here, we present BANDITS, a R/Bioconductor package to perform differential splicing, at both...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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BMC
2020-03-01
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| Series: | Genome Biology |
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| Online Access: | http://link.springer.com/article/10.1186/s13059-020-01967-8 |
| _version_ | 1818042808389337088 |
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| author | Simone Tiberi Mark D. Robinson |
| author_facet | Simone Tiberi Mark D. Robinson |
| author_sort | Simone Tiberi |
| collection | DOAJ |
| description | Abstract Alternative splicing is a biological process during gene expression that allows a single gene to code for multiple proteins. However, splicing patterns can be altered in some conditions or diseases. Here, we present BANDITS, a R/Bioconductor package to perform differential splicing, at both gene and transcript level, based on RNA-seq data. BANDITS uses a Bayesian hierarchical structure to explicitly model the variability between samples and treats the transcript allocation of reads as latent variables. We perform an extensive benchmark across both simulated and experimental RNA-seq datasets, where BANDITS has extremely favourable performance with respect to the competitors considered. |
| first_indexed | 2024-12-10T08:52:12Z |
| format | Article |
| id | doaj.art-c71f3c299d574906a10e046c9b7bb9b2 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-10T08:52:12Z |
| publishDate | 2020-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-c71f3c299d574906a10e046c9b7bb9b22022-12-22T01:55:33ZengBMCGenome Biology1474-760X2020-03-0121111310.1186/s13059-020-01967-8BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertaintySimone Tiberi0Mark D. Robinson1Institute of Molecular Life Sciences and SIB Swiss Institute of Bioinformatics, University of ZurichInstitute of Molecular Life Sciences and SIB Swiss Institute of Bioinformatics, University of ZurichAbstract Alternative splicing is a biological process during gene expression that allows a single gene to code for multiple proteins. However, splicing patterns can be altered in some conditions or diseases. Here, we present BANDITS, a R/Bioconductor package to perform differential splicing, at both gene and transcript level, based on RNA-seq data. BANDITS uses a Bayesian hierarchical structure to explicitly model the variability between samples and treats the transcript allocation of reads as latent variables. We perform an extensive benchmark across both simulated and experimental RNA-seq datasets, where BANDITS has extremely favourable performance with respect to the competitors considered.http://link.springer.com/article/10.1186/s13059-020-01967-8Alternative splicingDifferential splicingDifferential transcript usageRNA-seqTranscriptomicsBayesian hierarchical modelling |
| spellingShingle | Simone Tiberi Mark D. Robinson BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty Genome Biology Alternative splicing Differential splicing Differential transcript usage RNA-seq Transcriptomics Bayesian hierarchical modelling |
| title | BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty |
| title_full | BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty |
| title_fullStr | BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty |
| title_full_unstemmed | BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty |
| title_short | BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty |
| title_sort | bandits bayesian differential splicing accounting for sample to sample variability and mapping uncertainty |
| topic | Alternative splicing Differential splicing Differential transcript usage RNA-seq Transcriptomics Bayesian hierarchical modelling |
| url | http://link.springer.com/article/10.1186/s13059-020-01967-8 |
| work_keys_str_mv | AT simonetiberi banditsbayesiandifferentialsplicingaccountingforsampletosamplevariabilityandmappinguncertainty AT markdrobinson banditsbayesiandifferentialsplicingaccountingforsampletosamplevariabilityandmappinguncertainty |