Matthew Ritchie-Publications

Matthew Ritchie-Publications

Selected publications

  1. Tian L, Jabbari JS, Thijssen R, Gouil Q, Amarasinghe SL, Voogd O, Kariyawasam H, Du MRM, Schuster J, Wang C, Su S, Dong X, Law CW, Lucattini A, Prawar YDJ, Collar Fernandez C, Chung JD, Naim T, Chan A, Ly CH,  Lynch GS, Ryall JG, Anttila CJA, Peng H, Anderson MA, Flensburg C, Majewski I, Roberts AW, Huang DCS, Clark MB, Ritchie ME. Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing. Genome Biol. 2021, 22:310. PMID: 34763716
  2. Su S, Gouil Q, Blewitt ME, Cook D, Hickey PF, Ritchie ME. NanoMethViz: an R/Bioconductor package for visualizing long-read methylation data. PLoS Comp Biol. 2021, 17(10):e1009524. PMID: 34695109
  3. Tian L, Dong X, Freytag S, Lê Cao KA, Su S, JalalAbadi A, Amann-Zalcenstein D, Weber TS, Seidi A, Jabbari JS, Naik SH, Ritchie ME. Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments. Nat Methods. 2019, 16(6):479-487. PMID: 31133762
  4. Gigante S, Gouil Q, Lucattini A, Keniry A, Beck T, Tinning M, Gordon L, Woodruff C, Speed TP, Blewitt ME, Ritchie ME. Using long-read sequencing to detect imprinted DNA methylation. Nucleic Acids Res. 2019, 47(8):e46. PMID: 30793194
  5. Tian L, Su S, Dong X, Amann-Zalcenstein D, Biben C, Seidi A, Hilton DJ, Naik SH, Ritchie ME. scPipe: A flexible R/Bioconductor preprocessing pipeline for single-cell RNA-sequencing data. PLoS Comput Biol. 2018,14(8):e1006361. PMID: 30096152
  6. Su S, Law CW, Ah-Cann C, Asselin-Labat ML, Blewitt ME, Ritchie ME. Glimma: interactive graphics for gene expression analysis. Bioinformatics. 2017, 33(13):2050-52. PMID: 28203714
  7. Alhamdoosh M, Ng M, Wilson NJ, Sheridan JM, Huynh H, Wilson MJ, Ritchie ME. Combining multiple tools outperforms individual methods in gene set enrichment analyses. Bioinformatics. 2017, 33(3):414-24. PMID: 27694195
  8. Law CW, Alhamdoosh M, Su S, Smyth GK, Ritchie ME. RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR, F1000Research, 2016, 5:1408. PMID: 27441086
  9. Liu R, Holik AZ, Su S, Jansz N, Chen K, Leong HS, Blewitt ME, Asselin-Labat ML, Smyth GK, Ritchie ME. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. Nucleic Acids Res. 2015;43(15):e97. PMID: 25925576
  10. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47. PMID: 25605792

Further publications