BB	1. Apuntes de la asignatura disponibles en Moodle.
BB	Lawson, J.. Design and Analysis of Experiments with R. CRC press. 2014
BB	Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, Efron MJ, et al. (2015) Big Data: Astronomical or Genomical? PLoS Biol 13(7): e1002195. [Artículo online (CC 4.0 BY)]
BC	2. Akalin, A. (2020) Computational Genomics with R. CRC Press [Ver ed. Online con licencia CC-BY-NC-SA 4.0]
BC	3. Tripathi, R., Sharma, P., Chakraborty, P., & Varadwaj, P. K. (2016). Next-generation sequencing revolution through big data analytics. En: Frontiers in life science, 9(2), 119-149 [Artículo Online Open Access]
BC	Butler, A., Hoffman, P., Smibert, P. et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol 36, 411–420 (2018). [Artículo online por suscripción]
BC	Kitchin, R., & McArdle, G. (2016). What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets. Big Data & Society, 3(1), 2053951716631130 [Artículo online (CC 3.0 BY)]
BC	Law, C.W., Chen, Y., Shi, W. et al. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15, R29 (2014). [Artículo online (CC 4.0 BY)]
BC	Love, M.I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15, 550 (2014). [Artículo online (CC 4.0 BY)]
BC	Zhou, Wm., Yan, Yy., Guo, Qr. et al. Microfluidics applications for high-throughput single cell sequencing. J Nanobiotechnol 19, 312 (2021). [Artículo online (CC 4.0 BY)]