EMPeror protocols

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EMPeror specifications

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Unique identifier OMICS_07236
Name EMPeror
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Requirements
Numpy, SciKit-bio, qcli
Maintained Yes

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Publication for EMPeror

EMPeror in pipelines

 (3)
2017
PMCID: 5517580
PMID: 28725026
DOI: 10.1038/s41598-017-06055-9

[…] weighted pairwise distances, and the effect of the investigated factors was statistically assessed by the adonis test. beta-diversity plots (principal component analysis, pcoa) were visualized by emperor. the list of specific commands used for each qiime step is available upon request., in order to identify the most closely related species, the 16s rrna gene consensus sequences of the ten […]

2016
PMCID: 4957366
PMID: 26769272
DOI: 10.3382/ps/pev381

[…] biom table filtering. a jackknifed beta diversity analysis (lozupone et al., ) was conducted to assess statistical variation of sample location in principle coordinate analysis (pcoa) plots. we used emperor (vázquez-baeza et al., ) to visualize pcoa plots. following initial evaluation of the data, the biom table was variously filtered to focus on particular sample comparisons, specifically […]

2015
PMCID: 4621408
PMID: 26503553
DOI: 10.1038/srep15488

[…] unifrac metric and otu membership-based dissimilarity jaccard metric were employed to measure the pairwise community similarity between samples that were re-sampled to equal sequencing depth. emperor was used to visualize the distance matrix of all the 81 samples based on pcoa (principle coordinate analysis). the hierarchical clustering method upgma was applied to group samples according […]

EMPeror in publications

 (77)
PMCID: 5902705
PMID: 29692773
DOI: 10.3389/fmicb.2018.00718

[…] within biofilms from all four barley varieties and corn was evaluated using the unweighted and weighted unifrac distances () and visualized as principal coordinate analysis (pcoa) plots using emperor (). anosim (analysis of similarities) with 999 permutations was used to compare the unweighted unifrac distances., linear discriminant analysis effect size (lefse) was used to determine […]

PMCID: 5868818
PMID: 29579080
DOI: 10.1371/journal.pone.0194881

[…] influential principal coordinates were drawn from the resulting distance matrices either using either the make_2d_plots.py qiime script, or within the beta_diversity_through_plots.py script using emperor 9.51 software [], respectively. distance and dissimilarity metrics were used to compare the microbial communities between the two groups by utilising the permutational anova (permanova) [] […]

PMCID: 5862444
PMID: 29561873
DOI: 10.1371/journal.pone.0193671

[…] were computed from the calculated unifrac distance matrix to compress dimensionality into three-dimensional principal coordinate analysis (pcoa) plots created by qiime 2 and visualized by emperor []. differences between microbial communities (beta diversity) based on phylogenetic information visualized on the pcoa plots were calculated by permutational multivariate analysis […]

PMCID: 5860773
PMID: 29558527
DOI: 10.1371/journal.pone.0194489

[…] repeating the pcoa analysis for each resampled table (with one otu omitted) and plotting the results (i.e. the variance) as confidence ellipsoids around the samples []. the pcoa was visualized with emperor []., the sequence data are available at the ncbi short read repository under the accession number srr6080480., the morphological analyses of fungal spores resulted in the identification of 22 […]

PMCID: 5864415
PMID: 29577086
DOI: 10.1128/mSystems.00218-17

[…] the microbiomes, a tree was constructed from the sotus with sepp (saté-enabled phylogenetic placement; https://github.com/smirarab/sepp/blob/master/sepp/tree.py), and then results were visualized in emperor (). sample communities were then annotated with greengenes. the per-sample read counts generated after demultiplexing were used to compare false-negativity rates for using a gel to qualify […]

EMPeror institution(s)
BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, USA

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