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sNMF specifications

Information


Unique identifier OMICS_22407
Name sNMF
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Computer skills Advanced
Version 1.2
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Olivier Francois

Publication for sNMF

sNMF citations

 (18)
library_books

Convergent genomic signatures of domestication in sheep and goats

2018
Nat Commun
PMCID: 5840369
PMID: 29511174
DOI: 10.1038/s41467-018-03206-y

[…] th for goats only. During the last two millennia, wild populations declined while domestic groups increased (see Supplementary Note  and Supplementary Fig. ).Genetic structure analysis performed with sNMF within Ovis and Capra groups showed two isolated gene pools representing wild and domestic animals for both sheep and goat (Fig. ). Using Treemix and f3 statistics, we could not detect evidence f […]

call_split

Revealing the selection history of adaptive loci using genome wide scans for selection: an example from domestic sheep

2018
BMC Genomics
PMCID: 5778797
PMID: 29357834
DOI: 10.1186/s12864-018-4447-x
call_split See protocol

[…] lysis to visualize patterns in relationships between individuals using PLINK based on the genotype matrix [, ]; a model based approach to estimate individual ancestry coefficients, using the software sNMF []; a model based approach to infer populations splits and mixtures using the software treemix []. We included two outgroup populations in our analyses: Asian Mouflon (Ovis orientalis orientalis) […]

library_books

The Evolutionary History of Nebraska Deer Mice: Local Adaptation in the Face of Strong Gene Flow

2018
Mol Biol Evol
PMCID: 5905656
PMID: 29346646
DOI: 10.1093/molbev/msy004

[…] erformed in R using the method implemented in the Bioconductor (release 3.4) package SNPrelate v1.8.0 (). We inferred the ancestry proportions of all individuals based on K potential components using sNMF () implemented in the R/Bioconductor release 3.4 package LEA v1.6.0 () with default settings. We examined K values from 1 to 12, and selected the K that minimized the cross entropy as suggested b […]

library_books

At the Origin of a Worldwide Invasion: Unraveling the Genetic Makeup of the Caribbean Bridgehead Populations of the Dengue Vector Aedes aegypti

2017
Genome Biol Evol
PMCID: 5758905
PMID: 29267872
DOI: 10.1093/gbe/evx267

[…] rformed a Discriminant Analysis of Principal Components () using the R package adegenet v1.4.2 () with the number of populations as the number of clusters. Then we used the “structure-like” algorithm sNMF for inferring admixture coefficients for all individuals as implemented in the R package LEA (; ). The number of genetic clusters, K, was varied from 1 to 10. We performed 100 runs for each value […]

library_books

Genome‐wide single‐nucleotide polymorphism data reveal cryptic species within cryptic freshwater snail species—The case of the Ancylus fluviatilis species complex

2017
Ecol Evol
PMCID: 5773296
PMID: 29375779
DOI: 10.1002/ece3.3706

[…] nd the second axis 5.6% to 9.3%, respectively. This resulted in a clear clustering of specimens for all datasets, in which a major proportion of the variance was explained by these axes (Figure ). An sNMF analysis was conducted to analyze the population structure in more detail. According to the cross‐entropy criterion, K = 3 was the best number of clusters in all datasets, because cross‐entropy d […]

call_split

Genetic and physical mapping of anther extrusion in elite European winter wheat

2017
PLoS One
PMCID: 5679578
PMID: 29121111
DOI: 10.1371/journal.pone.0187744
call_split See protocol

[…] (GAPIT) []. Furthermore, to see the hidden population sub-structuring, we used R-based STRUCTURE-like inference algorithm LEA by assuming 10 ancestral populations (K = 1 − 10) and using the function snmf which provides least squares estimates of ancestry proportions and estimates an entropy criterion that evaluates the quality of fit of the statistical model to the data by using a cross-validatio […]

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sNMF institution(s)
Université Joseph Fourier Grenoble 1, Centre National de la Recherche Scientifique, Techniques de l’Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble Unité Mixte de Recherche 5525, Grenoble, France; Xerox Research Center Europe, Meylan, France
sNMF funding source(s)
Supported by a grant from la Région Rhône-Alpes and by Grenoble Institute of Technology.

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