1,721,151 research outputs found
Voomsom: Voom-Based Self-Organizing Maps For Clustering RNA-Sequencing Data
No full textBackground: Due to overdispersion in the RNA-Seq data and its discrete structure, clustering samples based on gene expression profiles remains a challenging problem, and several clustering approaches have been developed so far. However, there is no “gold standard” strategy for clustering RNA-Seq data, so alternative approaches are needed. Objective: In this study, we presented a new clustering approach, which incorporates two powerful methods, i.e., voom and self-organizing maps, into the frequently used clustering algorithms such as k-means, k-medoid and hierarchical clustering algorithms for RNA-seq data clustering. Methods: We first filter and normalize the raw RNA-seq count data. Then to transform counts into continuous data, we apply the voom method, which outputs the log-cpm matrix and sample quality weights. After the voom transformation, we apply the SOM algorithm to log-cpm values to get the codebook used in the downstream analysis. Next, we calculate the weighted distance matrices using the sample quality weights obtained from voom transformation and codebooks from the SOM algorithm. Finally, we apply k-means, k-medoid and hierarchical clustering algorithms to cluster samples. Results: The performances of the presented approach and existing methods are compared over simulat-ed and real datasets. The results show that the new clustering approach performs similarly or better than other methods in the Rand index and adjusted Rand index. Since the voom method accurately models the observed mean-variance relationship of RNA-seq data and SOM is an efficient algorithm for modeling high dimensional data, integrating these two powerful methods into clustering algorithms increases the performance of clustering algorithms in overdispersed RNA-seq data. Conclusion: The proposed algorithm, voomSOM, is an efficient and novel clustering approach that can be applied to RNA-Seq data clustering problems
Heat maps of the expression levels in the cervical cancer dataset (a) before and (b) after voom transform.
No full textHeat maps of the expression levels in the cervical cancer dataset (a) before and (b) after voom transform.</p
voom: precision weights unlock linear model analysis tools for RNA-seq read counts
Get PDFNew normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods
Comparison of edger and voom approaches for differential expression analysis based on transcriptome sequencing data
Get PDFIzhodišče: Z razvojem visoko zmogljivih tehnologij sekvenciranja, ki so omogočile pridobitev velike količine podatkov iz bioloških vzorcev, je hitro naraslo tudi število programskih orodij za urejanje teh podatkov, vendar pa trenutno še ni soglasja o najprimernejšem postopku ali metodi za identifikacijo različno izraženih genov s tehnologijo sekvenciranja naslednje generacije (RNA-seq). Namen naloge je bil analizirati dva pristopa za analizo RNA-seq podatkov in njune rezultate validirati z zlatim standardom.
Metode: V nalogi smo uporabili dva pristopa, edgeR (Robinson, et al., 2010) in limma (Ritchie, et al., 2015) -voom (Law, et al., 2014), ter njune rezultate preverili z metodo RT-qPCR. Z RT-qPCR smo preverili štiri gene, ki so imeli izračunane nasprotujoče si log2FC in p-vrednosti. Na koncu smo zbrane rezultate vseh treh metod analizirali s programskim orodjem SPSS.
Rezultati: Rezultati Spearmanovega testa korelacije so pokazali močno korelacijo med izračunanimi log2FC in p-vrednostmi obeh pristopov, vendar je Wilcoxonov test pokazal, da se log2FC in p-vrednosti kljub temu statistično značilno razlikujejo glede na to, katero metodo smo uporabili. Tri gene, ki so se po metodah edgeR in voom najbolj razlikovali, smo analizirali z RT-qPCR in ugotovili, da dobljeni rezultati qRT-PCR bolj sovpadajo s pristopom voom kot z edgeR, kar je potrdil tudi Spearmanov test korelacije in Wilcoxonov test.
Diskusija: Iz rezultatov smo zaključili, da je pristop voom primernejši, saj daje zanesljivejše rezultate kot edgeR kljub temu da smo imeli zelo majhen vzorec (3 posameznike za vsako skupino).Introduction: With the development of high-end sequencing technologies, that produce large amounts of data from biological samples, the number of software tools for analyzing this data has also rapidly increased, but there is no agreement on the most appropriate approach for identifying differentially expressed genes. The purpose of this master\u27s thesis was to analyze two approaches for the RNA-seq data analysis and validated their results with the gold standard.
Methods: Here, we compare two approaches, edgeR (Robinson, et al., 2010) and limma (Ritchie, et al., 2015) -voom (Law, et al., 2014), and we verified their results using the RT-qPCR method. Using RT-qPCR, we verified four genes that had differently computed log2FC and p-values. Finally, the results of all three methods were analyzed with the SPSS software tool.
Results: The results of the Spearman\u27s rank-order correlation showed a strong correlation between calculated log2FC and p-values of both approaches, but the Wilcoxon’s test showed that the values were significantly differ. Among the four selected genes, only three were analyzed with RT-qPCR, since the primers for one gene were not specific enough. Obtained results were more matched with the voom approach than with the edgeR, which was also confirmed by Spearman\u27s correlation and the Wilcoxon signed-rank test.
Discussion: From the results we concluded that the voom approach is better, since it gives more reliable results, even though we had a very small sample size (3 individuals for each group)
Heat maps showing expression levels of the Mont-Pick dataset (a) before and (b) after voom transform.
No full textHeat maps showing expression levels of the Mont-Pick dataset (a) before and (b) after voom transform.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The number of genes considered from each timepoint/treatment replicate and the number of genes considered before and after Voom/Limma filtering of low-expressed genes.
No full textThe number of genes considered from each timepoint/treatment replicate and the number of genes considered before and after Voom/Limma filtering of low-expressed genes.</p
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