2017
DOI: 10.1101/181610
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

BITE: an R package for biodiversity analyses

Abstract: Nowadays, molecular data analyses for biodiversity studies often require advanced bioinformatics skills, preventing many life scientists from analyzing their own data autonomously. BITE R package provides complete and user-friendly functions to handle SNP data and third-party software results (i.e. Admixture, TreeMix), facilitating their visualization, interpretation and use. Furthermore, BITE implements additional useful procedures, such as representative sampling and bootstrap for TreeMix, filling the gap in… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
85
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 105 publications
(85 citation statements)
references
References 14 publications
0
85
0
Order By: Relevance
“…In order to avoid issues related to missing values, all marker positions displaying missing data were removed. Furthermore, to assess the robustness of the graph underlying the modeled migrations, we adopted the following bootstrap-based procedure implemented in BITE package (Milanesi et al, 2017 ): first a varying number of migrations was modeled up to a maximum of 15 ( m 15 ) and with a number of SNPs per block equal to 50. The most meaningful number of migrations, m best , was identified based on the variance explained, the log likelihood and p values associated with each m , and the biological meaning of the migrations themselves.…”
Section: Methodsmentioning
confidence: 99%
“…In order to avoid issues related to missing values, all marker positions displaying missing data were removed. Furthermore, to assess the robustness of the graph underlying the modeled migrations, we adopted the following bootstrap-based procedure implemented in BITE package (Milanesi et al, 2017 ): first a varying number of migrations was modeled up to a maximum of 15 ( m 15 ) and with a number of SNPs per block equal to 50. The most meaningful number of migrations, m best , was identified based on the variance explained, the log likelihood and p values associated with each m , and the biological meaning of the migrations themselves.…”
Section: Methodsmentioning
confidence: 99%
“…Hence, the lowest 15-fold crossvalidation error was used to identify the most likely number of ancestral populations. The admixture graphs were visualized in R using the R package 'BITE' (Milanesi et al 2017).…”
Section: Admixture Analysismentioning
confidence: 99%
“…Migration events (m) ranging from 0 to 14 were modeled with AMU defined as the outgroup. To investigate the tree topology and migration edge consistencies, 200 bootstrap replicates were generated for each model separately using the R package 'BITE' (Milanesi et al 2017). To evaluate migration events and identify the most likely number of migrations, we estimated the f-index, the fraction of the variance in the sample covariance matrix (Ŵ) accounted for by the model covariance matrix (W).…”
Section: Population Split and Migration Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…We then ran TreeMix 100 times for 0 (as null model) and 1 migration event and obtained a consensus tree and bootstrap values using the BITE R package (84). The residual covariance matrix was estimated for each m value and the consensus tree using TreeMix.…”
Section: Admixture Analysesmentioning
confidence: 99%