Please jump to "ssMSEA" tab page.
Users can download the "Example Profile" and adjust the format of their own files.
The reference miRNA set annotations in sTAM are constituted by 151 miRNA-family sets(Family), 211 miRNA cluster sets(Cluster), 547 miRNA-disease sets(HMDD) and 155 miRNA-function sets(Function), 166 miRNA-TF sets(TF) and 6 tissue specificity sets(TissueSpecific). In addition, users could upload their miRNA sets as well.
(1) 'rank': Rank your expression data, and transform by 10000*rank_dat/miRNA_numbers.
(2) 'log': Do not rank,but transform data by log(data + exp(1)), while data = data[data < 1] = 1.
(3) 'log_rank': Rank your expression data, and transform by log(10000*rank_dat/miRNA_numbers + exp(1)).
Summary of the basic information
The result of sTAM, include two part: enrichment scores and matched miRNAs in corresponding set. Users can click "download" button to package and download the results.
Please jump to "tpMSEA" tab page.
The header must contain two phenotypes in the uploaded profile. Users can download the "Example Profile" and adjust the format of their own files.
(1) 'Signal2Noise': Signal2Noise (default) uses the difference of means scaled by the standard deviation.
(2) 'tTest': tTest uses the difference of means scaled by the standard deviation and number of samples.
(3) 'Fold Change': Fold Change uses the ratio of class means to calculate fold change for natural scale data.
(4) 'Log2 Fold Change': Log2 Fold Change uses the log2 ratio of class means to calculate fold change for natural scale data.
(3) 'Diff_of_Classes': Diff_of_Classes uses the difference of class means to calculate fold change for log scale data.
Note that the higher the number, the longer the running time.
Summary of the basic information
Users can filter the results by clicking the buttons.
Users can click "download" button to package and download the results.
Users can click thumbnail to see detail information about corresponding miRNA set:
Two columns consist of miRNA list and weight. The weight can be FoldChange, log2(FoldChange), signal noise ratio and so on. Users can download the "Example File" and adjust the format of their own files.
sTAM is a computational tool for single sample miRNA set enrichment analysis (MSEA). sTAM integrated the miRNA sets collected in TAM 2.0 (http://lirmed.com/tam2), a tool we previously developed for MSEA of miRNA lists in 2018. sTAM can calculate the enrichment score for one miRNA set in the miRNA expression of one single sample. In addition, sTAM also implemented profile-level MSEA. This is different with TAM 2.0 which runs for a miRNA list, whereas MSEA in sTAM runs for a miRNA profile dataset.
This website has been tested by using Chrome, Microsoft Edge and Firefox browsers. Microsoft IE may not work well.
For users who have miRNA expression profiles and wish to perform single sample miRNA set enrichment analysis, they would jump to ssMSEA tab page.
For users who have miRNA expression profiles for two classes of samples(e.g. tumor and control) and wish to perform miRNA set enrichment analysis, they would jump to tpMSEA tab page.
For users who have a pre-ranked miRNA list consist of miRNA names and weights, they would jump to tpMSEA(pre-ranked) tab page.
For more detail tutorial, please click here
sTAM results from collaboration between groups from Hebei University of Technology and Peking University Health Science Center. We try to understand life science using computing.
sTAM tool is free only for academic usage. For commercial useage, please contact:Dr. Qinghua Cui
Citation: Shi J, Cui Q*. sTAM: An Online Tool for the Discovery of miRNA-Set Level Disease Biomarkers. Mol Ther Nucleic Acids. 2020;21:670-675.