Data for LSA analysis

  1. Abad, Naiara 1
  2. Uranga, Ainhoa 1
  3. Ayo, Begoña 1
  4. Arrieta, Jesús María 2
  5. Baña, Zuriñe 1
  6. Artolozaga, Itxaso 1
  7. Azúa, Iñigo 1
  8. Iriberri, Juan 1
  9. González-Rojí, Santos J. 3
  10. Unanue, Maria Antonia 1
  1. 1 Department of Immunology, Microbiology and Parasitology. Faculty of Science and Technology. University of Basque Country (UPV/EHU). Sarriena S/N. 48940. Leioa, Spain
  2. 2 Oceanographic Center of Canary Island, Spanish Institute of Oceanography IEO, Vía Espaldón, Parcela 8, Santa Cruz De Tenerife, 38180, Spain
  3. 3 Oeschger Centre for Climate Change Research (OCCR), University of Bern, Hochschulstrasse 4, 3012 Bern, Switzerland
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Editor: Zenodo

Año de publicación: 2022

Tipo: Dataset

CC BY 4.0

DOI: 10.5281/ZENODO.6868359 lock_openAcceso abierto editor

Resumen

This code is supplementary to the paper "Kinetic modulation of bacterial hydrolases by microbial community structure in coastal waters" by Abad et al. <br> It contains the following files: 0) README.txt: This README file. 1) Complex saturation kinetics modelling.R: It contains the code developed for the determination of the kinetic parameters of the extracellular enzymatic activities by fitting the hydrolysis rates to four different kinetic models of increasing complexity using a non-linear least squares regression. 2) LSA functions.R: It contains the functions implemented in R to perform the Local Similarity analysis. Our specific modifications related to the function LocalSimilarity3 are indicated by the comment "#New: modified function". 3) LSA script.R: It is an updated version of the code developed by Ruan et al (2006) that has been used to perform the Local Similarity analysis in our study. The comment "#New: modified function” indicates our specific modifications within the original code. The following modifications were added to the original code: The calculation of the linear interpolation of missing values (NA’s) using the R package zoo (Zeleis et al 2021). The calculation of the q-values by using the R package qvalue (Storey et al 2022). <strong>NOTE:</strong> it is important to set the working directory in the same folder where all the provided files are stored.