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Aaron Lun
Aaron Lun
Verified email at gene.com
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Cited by
Cited by
Year
Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
L Haghverdi, ATL Lun, MD Morgan, JC Marioni
Nature Biotechnology, 2018
20152018
A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor.
ATL Lun, DJ McCarthy, JC Marioni
F1000 Research Ltd, 2016
15962016
Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R
DJ McCarthy, KR Campbell, ATL Lun, QF Wills
Bioinformatics 33 (8), 1179-1186, 2017
15722017
From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline
Y Chen, ATL Lun, GK Smyth
F1000Research 5, 2016
12052016
Pooling across cells to normalize single-cell RNA sequencing data with many zero counts
ATL Lun, K Bach, JC Marioni
Genome biology 17 (1), 75, 2016
11472016
Orchestrating single-cell analysis with Bioconductor
RA Amezquita, ATL Lun, E Becht, VJ Carey, LN Carpp, L Geistlinger, ...
Nature Methods, 1-9, 2019
7512019
EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data
ATL Lun, S Riesenfeld, T Andrews, T Gomes, JC Marioni
Genome Biology 20 (1), 63, 2019
7282019
Doublet identification in single-cell sequencing data using scDblFinder
PL Germain, A Lun, CG Meixide, W Macnair, MD Robinson
F1000Research 10, 2021
4842021
csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windows
ATL Lun, GK Smyth
Nucleic acids research 44 (5), e45, 2015
4252015
It’s DE-licious: a recipe for differential expression analyses of RNA-seq experiments using quasi-likelihood methods in edgeR
ATL Lun, Y Chen, GK Smyth
Methods in Molecular Biology 1418, 391-416, 2016
4232016
Three-dimensional disorganization of the cancer genome occurs coincident with long-range genetic and epigenetic alterations
PC Taberlay, J Achinger-Kawecka, ATL Lun, FA Buske, K Sabir, ...
Genome research 26 (6), 719-731, 2016
3602016
Detection and removal of barcode swapping in single-cell RNA-Seq data
JA Griffiths, AC Richard, K Bach, ATL Lun, JC Marioni
Nature Communications 9 (1), 2667, 2018
2602018
diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data
ATL Lun, GK Smyth
BMC Bioinformatics 16 (1), 258, 2015
2092015
Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR
Y Chen, ATL Lun, GK Smyth
Statistical Analysis of Next Generation Sequencing Data, 51-74, 2014
2092014
COMRADES determines in vivo RNA structures and interactions
O Ziv, MM Gabryelska, ATL Lun, LFR Gebert, J Sheu-Gruttadauria, ...
Nature methods 15 (10), 785-788, 2018
1732018
Transcriptional Heterogeneity in Naive and Primed Human Pluripotent Stem Cells at Single-Cell Resolution
T Messmer, F von Meyenn, A Savino, F Santos, H Mohammed, ATL Lun, ...
Cell reports 26 (4), 815-824. e4, 2019
1542019
Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data
ATL Lun, JC Marioni
Biostatistics 18 (3), 451-464, 2017
1482017
Testing for differential abundance in mass cytometry data
ATL Lun, AC Richard, JC Marioni
Nature methods 14 (7), 707-709, 2017
1452017
De novo detection of differentially bound regions for ChIP-seq data using peaks and windows: controlling error rates correctly
ATL Lun, GK Smyth
Nucleic acids research 42 (11), e95-e95, 2014
1312014
Specificity of RNAi, LNA and CRISPRi as loss-of-function methods in transcriptional analysis
L Stojic, ATL Lun, J Mangei, P Mascalchi, V Quarantotti, AR Barr, C Bakal, ...
Nucleic acids research, 2018
1202018
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