Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Charity W. Law"'
Autor:
Yue You, Xueyi Dong, Yong Kiat Wee, Mhairi J. Maxwell, Monther Alhamdoosh, Gordon K. Smyth, Peter F. Hickey, Matthew E. Ritchie, Charity W. Law
Publikováno v:
Genome Biology, Vol 24, Iss 1, Pp 1-21 (2023)
Abstract Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and its presence can hamper the detection of differentially expressed genes. Since most bulk RNA-seq methods assume equal group variances, we introduce
Externí odkaz:
https://doaj.org/article/d10773884bdb4c46881828200216a0c4
Autor:
Luyi Tian, Jafar S. Jabbari, Rachel Thijssen, Quentin Gouil, Shanika L. Amarasinghe, Oliver Voogd, Hasaru Kariyawasam, Mei R. M. Du, Jakob Schuster, Changqing Wang, Shian Su, Xueyi Dong, Charity W. Law, Alexis Lucattini, Yair David Joseph Prawer, Coralina Collar-Fernández, Jin D. Chung, Timur Naim, Audrey Chan, Chi Hai Ly, Gordon S. Lynch, James G. Ryall, Casey J. A. Anttila, Hongke Peng, Mary Ann Anderson, Christoffer Flensburg, Ian Majewski, Andrew W. Roberts, David C. S. Huang, Michael B. Clark, Matthew E. Ritchie
Publikováno v:
Genome Biology, Vol 22, Iss 1, Pp 1-24 (2021)
Abstract A modified Chromium 10x droplet-based protocol that subsamples cells for both short-read and long-read (nanopore) sequencing together with a new computational pipeline (FLAMES) is developed to enable isoform discovery, splicing analysis, and
Externí odkaz:
https://doaj.org/article/b1aa5d4188e746cca4e60723f7229ae1
Autor:
Yue You, Xueyi Dong, Yong Kiat Wee, Mhairi J. Maxwell, Monther Alhamdoosh, Gordon K. Smyth, Peter F. Hickey, Matthew E. Ritchie, Charity W. Law
Publikováno v:
Genome Biology, Vol 24, Iss 1, Pp 1-1 (2023)
Externí odkaz:
https://doaj.org/article/069db538e8c34bdfb20f76f929315fd0
Autor:
Charity W. Law, Kathleen Zeglinski, Xueyi Dong, Monther Alhamdoosh, Gordon K. Smyth, Matthew E. Ritchie
Publikováno v:
F1000Research, Vol 9 (2020)
Differential expression analysis of genomic data types, such as RNA-sequencing experiments, use linear models to determine the size and direction of the changes in gene expression. For RNA-sequencing, there are several established software packages f
Externí odkaz:
https://doaj.org/article/2b0afa4be8984122bf111f03451fedae
Autor:
Charity W. Law, Monther Alhamdoosh, Shian Su, Xueyi Dong, Luyi Tian, Gordon K. Smyth, Matthew E. Ritchie
Publikováno v:
F1000Research, Vol 5 (2018)
The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential ex
Externí odkaz:
https://doaj.org/article/3f1c5ac2a9a54dca83f76f26c352fd04
Autor:
Monther Alhamdoosh, Charity W. Law, Luyi Tian, Julie M. Sheridan, Milica Ng, Matthew E. Ritchie
Publikováno v:
F1000Research, Vol 6 (2017)
Gene set enrichment analysis is a popular approach for prioritising the biological processes perturbed in genomic datasets. The Bioconductor project hosts over 80 software packages capable of gene set analysis. Most of these packages search for enric
Externí odkaz:
https://doaj.org/article/65b4d62fd2f04791be482de3db4b116a
Publikováno v:
F1000Research, Vol 5 (2016)
The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential ex
Externí odkaz:
https://doaj.org/article/99978fb5eb7a448a811084730cc521b9
Publikováno v:
F1000Research, Vol 5 (2016)
The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential ex
Externí odkaz:
https://doaj.org/article/5425c6a738b14d1f9c6134e1a823ab6b
Autor:
Yue You, Xueyi Dong, Yong Kiat Wee, Mhairi J Maxwell, Monther Alhamdoosh, Gordon K Smyth, Peter F Hickey, Matthew E Ritchie, Charity W Law
Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and when not modelled appro-priately, its presence can hamper the detection of differentially expressed genes. Most bulk RNA-seq methods assume equal group vari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5509008b16cb382dad91d45a4990521b
https://doi.org/10.1101/2022.09.12.507511
https://doi.org/10.1101/2022.09.12.507511
Autor:
Xueyi Dong, Mei R. M. Du, Quentin Gouil, Luyi Tian, Jafar S. Jabbari, Rory Bowden, Pedro L. Baldoni, Yunshun Chen, Gordon K. Smyth, Shanika L. Amarasinghe, Charity W. Law, Matthew E. Ritchie
The current lack of benchmark datasets with inbuilt ground-truth makes it challenging to compare the performance of existing long-read isoform detection and differential expression analysis workflows. Here, we present a benchmark experiment using two
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69cd6c4a297726898cd9091ae2c35315
https://doi.org/10.1101/2022.07.22.501076
https://doi.org/10.1101/2022.07.22.501076