L’UMR CBGP – Centre de Biologie pour la Gestion des Populations – a pour vocation de comprendre les mécanismes qui régissent l’évolution de populations d'organismes importants pour l’agronomie, les forêts, la santé humaine ou la conservation de la biodiversité. Les recherches portent sur des modèles biologiques et sont développées selon six axes : origine et caractérisation de la biodiversité ; adaptation des phytophages, de leurs ennemis naturels et de leurs symbiontes ; écologie et évolution des zoonoses ; biologie, écologie et évolution des espèces envahissantes ; génomique statistique et évolutive des populations ; approches moléculaires et bioinformatiques haut débit. Nos tutelles sont l'INRAE, le CIRAD, l'IRD et l'Institut Agro-Montpellier.

UMR CBGP – Centre de Biologie pour la Gestion des Populations – aims to understand the mechanisms that govern populations of organisms that are important to agriculture, forest, human health and biodiversity conservation. Studies concern biological models and follow six lines of research: origin and characterization of biodiversity; adaptation of plant eaters, their natural enemies and symbionts; ecology and evolution of zoonoses; biology, ecology and evolution of invasive species; statistical and evolutionary population genomics; and high-throughput molecular and bioinformatics techniques. Our supervising bodies are INRAE, CIRAD, IRD and Institut Agro-Montpellier.
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71 to 80 of 131 Results
Filter1_sequencing-run.R
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
R Syntax - 8,3 KB - MD5: 14dd967c52750f012e387f2c3c786a35
First R script for data filtering. This script filter data for index contamination following correction 2 from Galan et al. 2016 (Tfa) and works on an abundance text file from Frogs and a metadata file that specifies sample names, biological units, technical replicates and contro...
Filtering_Functions.R
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
R Syntax - 377 B - MD5: 7cc002154f0e34a37b6b53f1ad649fb4
Loading packages and functions required for R scripts for data filtering.
Nextfilters_and_reduction.R
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
R Syntax - 20,2 KB - MD5: 2ea6d5266bd97ee5195e4feff7a93b3a
Second R script for data filtering. This script keeps positive data only if congruent between replicates (duplicates or triplicates) and filters data for extraction & pcr contamination following correction 1 from Galan et al. 2016 (Tcc) and using negative controls. It works on an...
Preprocess_1step_forFrogs_parameters_file_16Sv4.txt
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
Plain Text - 3,5 KB - MD5: 8a32246bf8d40f71976a9131e37a0ac1
This text file contain parameters needed by the shell script "Preprocess_1step_forFrogs.sh"
R-analyses.R
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
R Source Code - 20,9 KB - MD5: 775e2f0bad561c40e36b19d1ec9219e0
R script for all statistical analyses (using R-data.xlsx).
R-data.tab
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
Tabular Data - 4,1 KB - 49 Variables, 17 Observations - UNF:6:3cpS5HiYLk+POaq90NQuug==
Data for statistical analyses for each HTP 96 DNA purification method and cell community standard (DNA yield and abundance tables from amplicon sequencing of the V4 region of bacterial 16SrRNA gene, with metadata)
Repfilter2.R
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
R Syntax - 4,0 KB - MD5: 551c279dc661537756cba1b89ba72472
R function required for the second R script for data filtering.
Tccfilter.R
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
R Syntax - 1,6 KB - MD5: 6c5f4b29437897c7c799dd81f24e31bc
R function required for the second R script for data filtering.
Tfafilter.R
2 mai 2023 - Original data for " Chapuis MP et al. (2023). Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding. Molecular Ecology Resources, 23, 1509–1525"
R Syntax - 1,3 KB - MD5: dbaf780fd41340ca2766594858d24f5f
R function required for the first R script for data filtering.
Readme.txt
2 mai 2023 - Multi-agent model SANDMAN: source code
Plain Text - 79 B - MD5: 20c0b79b96fa22c37c51f8fcb7498f2f
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