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[Visualization of transcriptome data].
Pei, X T; Jiao, X W; Ping, Z G.
Afiliación
  • Pei XT; People's Hospital of Zhengzhou University/Henan Provincial People's Hospital/Henan Eye Hospital/ Henan Eye Institute/Henan Key Laboratory of Ophthalmology and Visual Science, Zhengzhou 450003, China.
  • Jiao XW; People's Hospital of Zhengzhou University/Henan Provincial People's Hospital/Henan Eye Hospital/ Henan Eye Institute/Henan Key Laboratory of Ophthalmology and Visual Science, Zhengzhou 450003, China.
  • Ping ZG; College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Zhonghua Yu Fang Yi Xue Za Zhi ; 54(5): 586-592, 2020 May 06.
Article en Zh | MEDLINE | ID: mdl-32388965
As an important method to study the phenotype and function of organisms, transcriptome has become one of hot topics in current research. The transcriptomics research usually accompanies with massive data. With the increase of the amount of data, the rules and features hidden in it are not easy to be found. Transforming big data into visual graphics is the most undoubtedly intuitive way to display the hidden information of big data. Several graphs commonly used in transcriptome study were introduced in this paper, such as Venn diagram, heat map, principal component analysis scatter plot, enrichment analysis plot, and time series analysis plot, in order to help readers to choose suitable graphics in future studies.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Gráficos por Computador / Biología Computacional / Transcriptoma Idioma: Zh Revista: Zhonghua Yu Fang Yi Xue Za Zhi Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Gráficos por Computador / Biología Computacional / Transcriptoma Idioma: Zh Revista: Zhonghua Yu Fang Yi Xue Za Zhi Año: 2020 Tipo del documento: Article País de afiliación: China