Bayesian analysis of plant DNA size distribution via non-additive statistics

Lima, Maxsuel Marcos Fernandes de; S, G. H. Nunes; Silva, R.; Fulco, U. L.; Mello, V.D.; Anselmo, D.H.A.L.

doi:10.1140/epjp/s13360-022-02707-6

Cited by 3 publications

(6 citation statements)

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“…According to [ 36 , 47 ], the coding part of human DNA tends to present short-range correlations. The same behavior for plant DNA can be observed in [ 34 ]. This implies

values close to zero.…”

Section: Resultssupporting

confidence: 77%

“…Initial analyses indicate that, as occurred for the Tsallis’ q -statistics [ 34 ], the

-exponential sum model best fits the DNA length distributions of the species studied here. Therefore, we chose to make a comparison between the sum of

-exponentials ( 9 ) and the

-Maxwellian model ( 11 ) below, proposed in [ 31 ] to explain the length distribution of human DNA.…”

Section: Methodsmentioning

confidence: 64%

“…We use the

-statistics, developed by Kaniadakis [ 26 , 27 , 28 ], to analyze the correlations between the DNA length distributions of some species of the Cucurbitaceae family. There are some works in this direction using the Tsallis q -statistics [ 34 , 35 , 36 ]. The

-entropy and power-law distribution functions naturally arise from the kinetic foundations of

-statistics.…”

Section: Methodsmentioning

confidence: 99%

“…In Ref. [ 34 ], it was proposed a comparison between the q -exponential and a sum of q -exponentials to explain the DNA length distribution of two species of cucurbits, Cucumis melo and Cucumis sativus . Based on this work, we propose an analysis of the same type but using the

.…”

Section: Methodsmentioning

confidence: 99%

“…More recently in [ 34 ], statistical models of the Tsallis type provided the distribution of nucleotide chain lengths, successfully capturing the statistical correlations between the parts of the plant (for both coding and non-coding) DNA strands for two species of the Cucurbitaceae family. We expand the paradigm proposed in [ 31 ] in the context of vegetables in this article.…”

Section: Introductionmentioning

confidence: 99%

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A Bayesian Analysis of Plant DNA Length Distribution via κ-Statistics

Lima

Anselmo

Silva

et al. 2022

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We report an analysis of the distribution of lengths of plant DNA (exons). Three species of Cucurbitaceae were investigated. In our study, we used two distinct κ distribution functions, namely, κ-Maxwellian and double-κ, to fit the length distributions. To determine which distribution has the best fitting, we made a Bayesian analysis of the models. Furthermore, we filtered the data, removing outliers, through a box plot analysis. Our findings show that the sum of κ-exponentials is the most appropriate to adjust the distribution curves and that the values of the κ parameter do not undergo considerable changes after filtering. Furthermore, for the analyzed species, there is a tendency for the κ parameter to lay within the interval (0.27;0.43).

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“…According to [ 36 , 47 ], the coding part of human DNA tends to present short-range correlations. The same behavior for plant DNA can be observed in [ 34 ]. This implies

values close to zero.…”

Section: Resultssupporting

confidence: 77%

“…Initial analyses indicate that, as occurred for the Tsallis’ q -statistics [ 34 ], the

-exponential sum model best fits the DNA length distributions of the species studied here. Therefore, we chose to make a comparison between the sum of

-exponentials ( 9 ) and the

-Maxwellian model ( 11 ) below, proposed in [ 31 ] to explain the length distribution of human DNA.…”

Section: Methodsmentioning

confidence: 64%

“…We use the

-entropy and power-law distribution functions naturally arise from the kinetic foundations of

-statistics.…”

Section: Methodsmentioning

confidence: 99%

.…”

Section: Methodsmentioning

confidence: 99%