If you are using this pipeline, please cite: Ware, A.P., Kabekkodu, S.P., Chawla, A., Paul, B., Satyamoorthy K. Diagnostic and prognostic potential clustered miRNAs in bladder cancer. 3 Biotech 12, 173 (2022). https://doi.org/10.1007/s13205-022-03225-z

Overview

Big data analytics through command line computation may be a daunting task to life science researchers. Hence, to overcome the computational challenges and reduce the complexity of multistep Commandline computing, we developed an automated pipeline called CmiRClustFinder v2.0. This is an improved version of the previous standalone pipeline CmiRClustFinder v1.0. For more information please visit documentation section.


Upload a CNV File (.txt):



Upload Genetic elements (.bed):



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How to use?

CmiRClustFinder is designed for Linux operating system. If you wish to use this pipeline, please visit GitHub


How it works?


CmiRClustFinder v1.0 computes the integrated data in five steps. The installation script will download all the necessary resources and prepare the pipeline for use in the first step. In the second step, the GAIA package finds frequent aberrations in chromosomal regions among cancer patients’ datasets. In the third step, the LiftOver tool matches the genomic build for RCNVs and user-defined genetic elements. We have integrated BEDTools to find co-localization of significant RCNV and genomic elements in the fourth step. Lastly, the Circlize package generates a circos representation of the data.



Select cancer type:


Upload BED File:



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