TAM 2.0: tool for MicroRNA set analysis

Li, Jianwei; Han, Xiaofen; Wan, Yanping; Zhang, Shan; Zhao, Yingshu; Fan, Rui; Cui, Qinghua; Zhou, Yuan

doi:10.1093/nar/gky509

Cited by 143 publications

(117 citation statements)

References 31 publications

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“…Datasets incorporated in miEAA were compiled either automatically or manually. TAM, another miRNA enrichment tool with functionality similar to miEAA, uses a fewer number of high-quality annotations, which come exclusively from manual curation [13]. A detailed comparison with respect to 22 criteria between our tool and TAM is shown in Supplementary Table 5.…”

Section: Discussionmentioning

confidence: 99%

“…While this may speak for a molecular and biological similarity, a certain publication bias, e.g. for cancer, is a confounding factor that skews the statistics [13].…”

Section: Discussionmentioning

confidence: 99%

“…Novel datasets were obtained to build our enrichment categories, consisting of Gene Ontology [25], miRTarBase 8.0 [15], KEGG [26], miRandola 2017 [22], miRPathDB 2.0 [16], TissueAtlas [17], MNDR v2.0 [19], NPInter 4.0 [27], RNALocate v2.0 [21], TAM 2.0 [13], and TransmiR v2.0 [20]. Other pre-existing datasets have been updated, including HMDD v3.0 [18] and miRBase v22.1 [28].…”

Section: Data Collectionmentioning

confidence: 99%

“…Given the growing interest in miRNAs, other tools with similar functionality to miEAA exist. Among the most functional tools, the recent successor version of TAM [13] introduced 1, 238 human miRNA set categories obtained from manual literature review of approximately 9, 000 scientific manuscripts, along with new query and visualisation features. In addition to the over-and under-representation analysis, users can compare the correlation of two miRNA lists under different disease conditions.…”

Section: Introductionmentioning

confidence: 99%

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miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Kern

Fehlmann

Solomon

et al. 2020

Preprint

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AbstractGene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs.Here, we present miEAA 2.0, supporting miRNA input from Homo sapiens, Mus musculus, and Rattus norvegicus. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miR-Base miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualisations such as heatmaps and running sum curves with background distributions. Lastly, additional methods to correct for multiple hypothesis testing were implemented. We demonstrate the new features using case studies for human kidney cancer and mouse samples. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

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Section: Discussionmentioning

confidence: 99%

“…While this may speak for a molecular and biological similarity, a certain publication bias, e.g. for cancer, is a confounding factor that skews the statistics [13].…”

Section: Discussionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Kern

Fehlmann

Solomon

et al. 2020

Preprint

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“…11 We then developed TAM for MSEA for a list of miRNAs, for example deregulated miRNA in some cancers. 12,13 In addition, two other tools for MSEA, miSEA 14 and miEAA, 15 have also been developed with different statistical methods. These tools provide helps in discovering valuable clues and predicting novel disease-related 6 miRNAs based on miRNA expression data.…”

Section: Discussionmentioning

confidence: 99%

sTAM: An Online Tool for the Discovery of miRNA-set Level Disease Biomarkers

Shi

Cui

2020

Preprint

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microRNAs (miRNAs) are one class of important small noncoding RNA molecules, which have shown their excellent ability as biomarkers of various diseases. However, current miRNA biomarkers including those comprised of multiple miRNAs work at a single-miRNA level but not at a miRNA set level. Given the rapidly accumulated miRNA omics data, it is believed that miRNA set level analysis could be an important supplement to the single miRNA level analysis. For doing so, here we presented a computational method for single-sample miRNA set enrichment analysis and developed the sTAM tool (http://mir.rnanut.net/stam). Moreover, we demonstrated the usefulness of sTAM scores in discovering miRNA-set level biomarkers through two case studies. We conducted pan-cancer analysis of the sTAM scores of "tumor suppressor miRNA set" on 15 types of cancers from TCGA and 14 types of cancers from GEO, finding that the scores show a good performance in distinguishing the cancers from the controls. Moreover, we revealed that the sTAM score of "brain development" miRNA set can effectively predict cerebrovascular disorder (CVD).Finally, we believe sTAM can be used in discovering disease-related biomarkers at a miRNA-set level.

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Profiling and bioinformatic analysis reveal differential microRNA expression in the left and right kidneys in normal mice

et al. 2019

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Physiological and pathophysiological differences exist between the left and right kidneys; however, the molecular bases for these differences remain unknown. Since miRNAs are involved in kidney function and the development of kidney diseases, we examined their differential expression through miRNA profiling of the left and right kidneys of normal mice. We find that 36 miRNAs exhibit higher expression, whereas 22 miRNAs show lower expression in the left than the right kidneys in mice under physiological condition. Ten miRNAs were further examined by quantitative PCR assays, and four of them with high expression level were confirmed by Northern blot. Through bioinformatic analysis, we dissected the function and network of the differentially expressed miRNAs, providing insights into the physiological and pathophysiological differences between the left and the right kidneys.

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TAM 2.0: tool for MicroRNA set analysis

Cited by 143 publications

References 31 publications

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

sTAM: An Online Tool for the Discovery of miRNA-set Level Disease Biomarkers

Profiling and bioinformatic analysis reveal differential microRNA expression in the left and right kidneys in normal mice

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