The tidyomics ecosystem: enhancing omic data analyses

• Published in: Nature methods Vol. 21; no. 7; pp. 1166 - 1170
• Main Authors: Hutchison, William J., Keyes, Timothy J., Crowell, Helena L., Serizay, Jacques, Soneson, Charlotte, Davis, Eric S., Sato, Noriaki, Moses, Lambda, Tarlinton, Boyd, Nahid, Abdullah A., Kosmac, Miha, Clayssen, Quentin, Yuan, Victor, Mu, Wancen, Park, Ji-Eun, Mamede, Izabela, Ryu, Min Hyung, Axisa, Pierre-Paul, Paiz, Paulina, Poon, Chi-Lam, Tang, Ming, Gottardo, Raphael, Morgan, Martin, Lee, Stuart, Lawrence, Michael, Hicks, Stephanie C., Nolan, Garry P., Davis, Kara L., Papenfuss, Anthony T., Love, Michael I., Mangiola, Stefano
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.07.2024; Nature Publishing Group
• Subjects: 631/114; 706/648/160; Bioinformatics; Biological Microscopy; Biological Techniques; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Brief Communication; Communication; Computational Biology - methods; Data Analysis; Data science; Ecosystems; Ethnicity; Generalized linear models; Genomics; Genomics - methods; Grammar; Humans; Leukocytes (mononuclear); Leukocytes, Mononuclear - cytology; Leukocytes, Mononuclear - metabolism; Life Sciences; Lymphocytes; Peripheral blood mononuclear cells; Proteomics; Science education; Software; Syntax

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipula...