Soft windowing application to improve analysis of high-throughput phenotyping data

MOTIVATION: High-throughput phenomic projects generate complex data from small treatment and large control groups that increase the power of the analyses but introduce variation over time. A method is needed to utlize a set of temporally local controls that maximizes analytic power while minimizing...

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Bibliografiset tiedot
Julkaisussa:Bioinformatics
Päätekijät: Haselimashhadi, Hamed, Mason, Jeremy C, Munoz-Fuentes, Violeta, López-Gómez, Federico, Babalola, Kolawole, Acar, Elif F, Kumar, Vivek, White, Jacqui, Flenniken, Ann M, King, Ruairidh, Straiton, Ewan, Seavitt, John Richard, Gaspero, Angelina, Garza, Arturo, Christianson, Audrey E, Hsu, Chih-Wei, Reynolds, Corey L, Lanza, Denise G, Lorenzo, Isabel, Green, Jennie R, Gallegos, Juan J, Bohat, Ritu, Samaco, Rodney C, Veeraragavan, Surabi, Kim, Jong Kyoung, Miller, Gregor, Fuchs, Helmult, Garrett, Lillian, Becker, Lore, Kang, Yeon Kyung, Clary, David, Cho, Soo Young, Tamura, Masaru, Tanaka, Nobuhiko, Soo, Kyung Dong, Bezginov, Alexandr, About, Ghina Bou, Champy, Marie-France, Vasseur, Laurent, Leblanc, Sophie, Meziane, Hamid, Selloum, Mohammed, Reilly, Patrick T, Spielmann, Nadine, Maier, Holger, Gailus-Durner, Valerie, Sorg, Tania, Hiroshi, Masuya, Yuichi, Obata, Heaney, Jason D, Dickinson, Mary E, Wolfgang, Wurst, Tocchini-Valentini, Glauco P, Lloyd, Kevin C Kent, McKerlie, Colin, Seong, Je Kyung, Yann, Herault, de Angelis, Martin Hrabé, Brown, Steve D M, Smedley, Damian, Flicek, Paul, Mallon, Ann-Marie, Parkinson, Helen, Meehan, Terrence F
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Oxford University Press 2020
Aiheet:
Original Papers
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC7115897/
https://ncbi.nlm.nih.gov/pubmed/31591642
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btz744
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