2018
DOI: 10.1186/s12575-018-0067-8
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Silhouette Scores for Arbitrary Defined Groups in Gene Expression Data and Insights into Differential Expression Results

Abstract: BackgroundHierarchical Sample clustering (HSC) is widely performed to examine associations within expression data obtained from microarrays and RNA sequencing (RNA-seq). Researchers have investigated the HSC results with several possible criteria for grouping (e.g., sex, age, and disease types). However, the evaluation of arbitrary defined groups still counts in subjective visual inspection.ResultsTo objectively evaluate the degree of separation between groups of interest in the HSC dendrogram, we propose to u… Show more

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Cited by 29 publications
(33 citation statements)
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References 60 publications
(82 reference statements)
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“…In a comparison of the performance of each method using different numbers of replicates ( Fig. 1 and Additional le 1), we observed that AUC values tend to increase as the number of replicates increases and this trend is consistent with a previous report [20].…”
Section: Analysis Of Simulated Data For a Two-group Comparisonsupporting
confidence: 91%
See 1 more Smart Citation
“…In a comparison of the performance of each method using different numbers of replicates ( Fig. 1 and Additional le 1), we observed that AUC values tend to increase as the number of replicates increases and this trend is consistent with a previous report [20].…”
Section: Analysis Of Simulated Data For a Two-group Comparisonsupporting
confidence: 91%
“…To date, several methods to enable the analysis of RNA-seq data have been developed, including normalization [5][6][7][8][9][10], various R packages [11][12][13][14][15][16], and graphical user interfaces (GUI) [17][18][19]. Research on more e cient and accurate methods to identify DEGs continues, and new ndings continue to be reported by researchers [20][21][22][23][24][25].…”
Section: Introductionmentioning
confidence: 99%
“…The AgglomerativeClustering function from Scikit-Learn with euclidean affinity and Ward linkage was used to perform hierarchical grouping (Pedregosa et al, 2011 ). We calculated the number of groups (synaptic subtypes) that best describe our data based on maximization of the silhouette score, a measure of similarity within a group and dissimilarity between different groups (Rousseeuw, 1987 ; Zhao et al, 2018 ).…”
Section: Methodsmentioning
confidence: 99%
“…However, even the tendency to obtain a large number of DE genes between cell types cannot distinguish these. For example, a bulk RNA-seq dataset exists (Schurch et al, 2016 ) that can produce nearly 70% DE genes (Zhao et al, 2018 ). A common feature of these data sets is a high number of replicates (>40 replicates per group).…”
mentioning
confidence: 99%