Input and runtime details for job 5382027 (precomputed example)
Input
Job ID 5382027 (server version 4.3.0)
Job Submitted & Queued | @ Mon Aug 08 10:19:27 CEST 2016 | ||
metaMIR Started | @ Mon Aug 08 10:19:39 CEST 2016 | ||
metaMIR Finished & Post-Processing | @ Mon Aug 08 10:20:31 CEST 2016 | ||
Job Completed | @ Mon Aug 08 10:20:32 CEST 2016 |
Description of the job
example3
An example of metaMIR in differential analysis mode. The transforming
growth factor beta (TGFb) signalling pathway, important during neural
development (including neural crest) is often dysregulated in the
development or progression of cancers. In many contexts, up-regulation of
the activating components of the pathway can be involved in the progression
of disease. A potential therapeutic application of miRNAs in this context
would be to search a miRNA that targets (down-regulates) these components.
At the same time, given the multitudinous targets of miRNAs, one would not
want to target tumour suppressor genes.
In this gene list, the TGFb componens are plain, indicating the search
should be "positive" to find miRNAs that will target (down-regulate) these
genes as in the standard analysis. Genes prefixed with a minus sign (-) are
those tumour suppressors one does *not* want to be simultaneously targeted
by any miRNA returned for a cluster in the positive search.
Output download complete results [zip]
Result table
miRNA | Final Score | Positive Combo | Positive Score | Positive Group | Positive List |
---|---|---|---|---|---|
hsa-miR-302a-5p | 2.932 | BMP2,BMPR2,MYC,SMAD1,SMAD2,SMAD4,TGFB1,TGFB2 | 2.507 | 8 | 2.39 |
hsa-miR-1285-5p | 2.14 | BMPR1A,BMPR2,TGFB2,TGFB3,TGFBR1,TGFBR2,TGFBR3 | 2.084 | 7 | 2.14 |
hsa-miR-4308 | 2.611 | BMP4,BMPR2,SMAD1,SMAD3,TGFB2,TGFB3,TGFBR1,TGFBR3 | 1.981 | 8 | 2.17 |
hsa-miR-548az-5p | 1.142 | BMP4,BMPR2,MYC,SMAD1,SMAD4,TGFBR3 | 1.117 | 6 | 1.14 |
Result table - repPos
Gene name | Rep |
---|---|
BMP2 | 100 |
BMP7 | 100 |
BMPR1A | 100 |
BMPR2 | 100 |
MYC | 100 |
SMAD2 | 100 |
SMAD3 | 100 |
SMAD4 | 100 |
TGFB2 | 100 |
TGFB3 | 100 |
Result table - clusterPos
Gene 1 | Inter | Gene 2 | Norm |
---|---|---|---|
BMP2 | pp | BMP7 | 7.5 |
BMPR1A | pp | BMPR2 | 8.5 |
MYC | pp | NOG | 6 |
SMAD1 | pp | SMAD2 | 7.5 |
SMAD3 | pp | SMAD4 | 8.5 |
TGFB2 | pp | TGFB3 | 8.5 |
TGFBR1 | pp | TGFBR2 | 8.5 |
TGFBR3 | pp | BMP2 | 8.5 |
BMP7 | pp | BMPR1A | 8.5 |
BMPR2 | pp | MYC | 8.5 |
Job resubmission
usability assessment
When using metaMIR please cite :
- Jason A. Davis, Sita J. Saunders, Martin Mann, Rolf Backofen
Combinatorial ensemble miRNA target prediction of co-regulation networks with non-prediction data
Nucleic Acids Research, 2017, 45 (15), 8745–8757. - Martin Raden, Syed M Ali, Omer S Alkhnbashi, Anke Busch, Fabrizio Costa, Jason A Davis, Florian Eggenhofer, Rick Gelhausen, Jens Georg, Steffen Heyne, Michael Hiller, Kousik Kundu, Robert Kleinkauf, Steffen C Lott, Mostafa M Mohamed, Alexander Mattheis, Milad Miladi, Andreas S Richter, Sebastian Will, Joachim Wolff, Patrick R Wright, and Rolf Backofen
Freiburg RNA tools: a central online resource for RNA-focused research and teaching
Nucleic Acids Research, 46(W1), W25-W29, 2018.