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Amezquita, R.A., Lun, A.T.L., Becht, E. et al. Orchestrating single-cell analysis with Bioconductor. Nature Methods (2019) doi:10.1038/s41592-019-0654-x
Pasolli, E, et al. (2017) Accessible, curated metagenomic data through ExperimentHub Nature Methods 14, 1023–1024. doi:10.1038/nmeth.4468
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Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, et al. (2013) Software for Computing and Annotating Genomic Ranges. PLoS Comput Biol 9(8): e1003118. doi: 10.1371/journal.pcbi.1003118
Irizarry R, et al. (2015) Biomedical Data Science. Course Notes, EdX PH525.1x.


20 most recent PubMed and PubMed Central citations mentioning "Bioconductor". For a complete list, go to PubMed and PubMed Central. Last updated 2019-12-12T15:00:09-05:00.

Ahmed M, Kim DR. Modelling the gene expression and the DNA-binding in the 3T3-L1 differentiating adipocytes. Adipocyte, 8(1), pp. 401-411. doi:10.1080/21623945.2019.1697563 (7 December 2019)
Freytag S, Lister R. schex avoids overplotting for large single cell RNA-sequencing datasets. Bioinformatics. doi:10.1093/bioinformatics/btz907 (3 December 2019)
Chao KH, Hsiao YW, Lee YF, Lee CY, Lai LC, Tsai MH, Lu TP, Chuang EY. RNASeqR: an R package for automated two-group RNA-Seq analysis workflow. IEEE/ACM Trans Comput Biol Bioinform. doi:10.1109/TCBB.2019.2956708 (2 December 2019)
Amezquita RA, Lun ATL, Becht E, Carey VJ, Carpp LN, Geistlinger L, Martini F, Rue-Albrecht K, Risso D, Soneson C, Waldron L, Pagès H, Smith ML, Huber W, Morgan M, Gottardo R, Hicks SC. Orchestrating single-cell analysis with Bioconductor. Nat Methods. doi:10.1038/s41592-019-0654-x (2 December 2019)
Díaz-Riaño J, Posada L, Acosta IC, Ruíz-Pérez C, García-Castillo C, Reyes A, Zambrano MM. Computational search for UV radiation resistance strategies in Deinococcus swuensis isolated from Paramo ecosystems. PLoS One, 14(12), pp. e0221540. doi:10.1371/journal.pone.0221540 (2 December 2019)
Su S, Tian L, Dong X, Hickey PF, Freytag S, Ritchie ME. CellBench: R/Bioconductor software for comparing single-cell RNA-seq analysis methods. Bioinformatics. doi:10.1093/bioinformatics/btz889 (28 November 2019)
Huan X, Jinhe Y, Rongzong Z. Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset. Med Sci Monit, 25, pp. 8891-8904. doi:10.12659/MSM.920636 (23 November 2019)
Bhuva DD, Cursons J, Smyth GK, Davis MJ. Differential co-expression-based detection of conditional relationships in transcriptional data: comparative analysis and application to breast cancer. Genome Biol, 20(1), pp. 236. doi:10.1186/s13059-019-1851-8 (14 November 2019)
Zhang C, Hu X, Qi F, Luo J, Li X. Identification of CD2, CCL5 and CCR5 as potential therapeutic target genes for renal interstitial fibrosis. Ann Transl Med, 7(18), pp. 454. doi:10.21037/atm.2019.08.62 (9 November 2019)
Jiang Y, Zhang H, Andrews SV, Arshad H, Ewart S, Holloway JW, Fallin MD, Bakulski KM, Karmaus W. Estimation of Eosinophil Cells in Cord Blood with References Based on Blood in Adults via Bayesian Measurement Error Modeling. Bioinformatics. doi:10.1093/bioinformatics/btz839 (9 November 2019)
Zheng SC, Breeze CE, Beck S, Dong D, Zhu T, Ma L, Ye W, Zhang G, Teschendorff AE. EpiDISH web server: Epigenetic Dissection of Intra-Sample-Heterogeneity with online GUI. Bioinformatics. doi:10.1093/bioinformatics/btz833 (9 November 2019)
Carlucci M, Kriščiūnas A, Li H, Gibas P, Koncevičius K, Petronis A, Oh G. DiscoRhythm: an easy-to-use web application and R package for discovering rhythmicity. Bioinformatics. doi:10.1093/bioinformatics/btz834 (8 November 2019)
Fornes O, Castro-Mondragon JA, Khan A, van der Lee R, Zhang X, Richmond PA, Modi BP, Correard S, Gheorghe M, Baranašić D, Santana-Garcia W, Tan G, Chèneby J, Ballester B, Parcy F, Sandelin A, Lenhard B, Wasserman WW, Mathelier A. JASPAR 2020: update of the open-access database of transcription factor binding profiles. Nucleic Acids Res. doi:10.1093/nar/gkz1001 (8 November 2019)
Pal K, Tagliaferri I, Livi CM, Ferrari F. HiCBricks: building blocks for efficient handling of large Hi-C datasets. Bioinformatics. doi:10.1093/bioinformatics/btz808 (7 November 2019)
Di Filippo L, Righelli D, Gagliardi M, Matarazzo MR, Angelini C. HiCeekR: A Novel Shiny App for Hi-C Data Analysis. Front Genet, 10, pp. 1079. doi:10.3389/fgene.2019.01079 (4 November 2019)
Fraser L, Brym P, Pareek CS, Mogielnicka-Brzozowska M, Paukszto Ł, Jastrzębski JP, Wasilewska-Sakowska K, Mańkowska A, Sobiech P, Żukowski K. Transcriptome analysis of boar spermatozoa with different freezability using RNA-Seq. Theriogenology, 142, pp. 400-413. doi:10.1016/j.theriogenology.2019.11.001 (2 November 2019)
Kuijjer ML, Hsieh PH, Quackenbush J, Glass K. lionessR: single sample network inference in R. BMC Cancer, 19(1), pp. 1003. doi:10.1186/s12885-019-6235-7 (25 October 2019)
Gonçalves ANA, Lever M, Russo PST, Gomes-Correia B, Urbanski AH, Pollara G, Noursadeghi M, Maracaja-Coutinho V, Nakaya HI. Assessing the Impact of Sample Heterogeneity on Transcriptome Analysis of Human Diseases Using MDP Webtool. Front Genet, 10, pp. 971. doi:10.3389/fgene.2019.00971 (24 October 2019)
Gustavsen JA, Pai S, Isserlin R, Demchak B, Pico AR. RCy3: Network biology using Cytoscape from within R. F1000Res, 8, pp. 1774. doi:10.12688/f1000research.20887.1 (18 October 2019)


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