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DESCRIPTION

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Package: bambu
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Type: Package
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Title: Context-Aware Transcript Quantification from Long Read RNA-Seq data
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Version: 3.2.3
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Version: 3.2.4
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Authors@R: c(person("Ying", "Chen", role = c("cre","aut"),
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email = "[email protected]"),
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person("Andre", "Sim", role = "aut",

README.md

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### Release History
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**bambu v3.2.6**
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Release date: 2023-Apr-26
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Minor changes:
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* Fixes crash during Low Memory Mode when there are scaffolds with no reads
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* Fixes crash on windows machines caused by DNAStringSet
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* Adds NDR metadata when running discovery mode with recommended NDR, so users do not need to look at console for the recommended NDR.
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* Re-enabled GitHub actions for new devel branch name and the windows check
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* Fixed a crash that occurs with large datasets resulting in large overflow tables during novel gene id assignment
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* Remove nested bplapply in EM
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* Remove unused eqClassById list column in the readClassDist object to reduce memory usage
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* Fixed a bug that caused identical unspliced reads to not be tracked when trackReads = TRUE
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- Fixes crash during Low Memory Mode when there are scaffolds with no reads
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- Fixes crash on windows machines caused by DNAStringSet
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- Adds NDR metadata when running discovery mode with recommended NDR, so users do not need to look at console for the recommended NDR.
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- Re-enabled GitHub actions for new devel branch name and the windows check
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- Fixed a crash that occurs with large datasets resulting in large overflow tables during novel gene id assignment
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- Remove nested bplapply in EM
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- Remove unused eqClassById list column in the readClassDist object to reduce memory usage
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- Fixed a bug that caused identical unspliced reads to not be tracked when trackReads = TRUE
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**bambu version 3.0.0**
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Release date: 2022-10-25
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Major changes:
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* Updated the input parameters of Bambu to simplify the user experience
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* Introduced NDR threshold recommendation
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* Implemented trainBambu(), allowing users to train and use models on their own data
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* Reads that cannot be assigned to any transcript are grouped as incompatible counts
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* Partial estimates are removed from output as it can be directly obtained based on total count estimates and full-length count estimates
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* The fusion mode is now available, which assigns read classes that align to multiple genes to a new combined fusion gene
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- Updated the input parameters of Bambu to simplify the user experience
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- Introduced NDR threshold recommendation
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- Implemented trainBambu(), allowing users to train and use models on their own data
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- Reads that cannot be assigned to any transcript are grouped as incompatible counts
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- Partial estimates are removed from output as it can be directly obtained based on total count estimates and full-length count estimates
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- The fusion mode is now available, which assigns read classes that align to multiple genes to a new combined fusion gene
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Minor changes:
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* Novel transcripts and genes are now by default output with a Bambu prefix
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* Updated the documentation, messages and errors output by Bambu
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* Annotated transcripts (with unique exon-junctions) with at least 1 full-length read are assigned a NDR rank
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- Novel transcripts and genes are now by default output with a Bambu prefix
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- Updated the documentation, messages and errors output by Bambu
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- Annotated transcripts (with unique exon-junctions) with at least 1 full-length read are assigned a NDR rank
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**bambu version 1.99.0**
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Release date: 2020-05-29
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### Citation
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Chen, Ying, et al. "Context-Aware Transcript Quantification from Long Read RNA-Seq data with Bambu" bioRxiv (2022). doi: https://doi.org/10.1101/2022.11.14.516358
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Chen, Y., Sim, A., Wan, Y.K. et al. Context-aware transcript quantification from long-read RNA-seq data with Bambu. Nat Methods (2023). https://doi.org/10.1038/s41592-023-01908-w
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### Contributors
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inst/CITATION

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citEntry(entry="article",
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title = "Context-Aware Transcript Quantification from Long Read RNA-Seq data with Bambu",
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title = "Context-aware transcript quantification from long-read RNA-seq data with Bambu",
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author = personList( as.person("Ying Chen"),
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as.person("Andre Sim"),
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as.person("Yuk Kei Wan"),
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as.person("Min Hao Ling"),
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as.person("Michael I. Love"),
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as.person("Jonathan Göke")),
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year = 2022,
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journal = "bioRxiv",
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doi = "https://doi.org/10.1101/2022.11.14.516358",
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year = 2023,
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journal = "Nature Methods",
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doi = "https://doi.org/10.1038/s41592-023-01908-w",
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textVersion =
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paste("Chen, Y., Sim, A. D., Wan, Y. K., Yeo, K., Lee, J. J. X., Ling, M. H., ... & Göke, J.",
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"Context-Aware Transcript Quantification from Long Read RNA-Seq data with Bambu",
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"bioRxiv (2022)" ) )
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paste("Chen, Y., Sim, A., Wan, Y. K., Yeo, K., Lee, J. J. X., Ling, M. H., Love, M. I. & Göke, J.",
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"Context-aware transcript quantification from long-read RNA-seq data with Bambu",
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"Nat Methods (2023)" ) )

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