Improve circRNA-miRNA interaction analysis #166
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Co-authored-by: Nico Trummer <[email protected]>
Co-authored-by: Nico Trummer <[email protected]>
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nictru
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Aug 8, 2024
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Extending
MIRNA_PREDICTIONsubworkflow:MIRNA_NORMALIZATION(process): performs DESeq2 normalization.Adding
MIRNA_FILTERING(process): filters output ofMIRNA_NORMALISATIONbased onparams.mirna_min_sampleandparams.mirna_min_percentage.Based on this, all samples that did not survive the filtering get removed from
mature.MIRNA_BINDINGSITES: This subworkflow performs binding site predictions with the specified tools inparams.mirna_tools.The output of each tool gets converted into a unified format, which serves as an input for
MAJORITY_VOTE.This process filters out binding sites, which were predicted by less than
params.mirna_votetools.MIRNA_BINDINGSITEScan be extended with tools likeTarpMIR(see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5018371/) andPITA(https://mybiosoftware.com/pita-6-microrna-prediction-tool.html) in the future.COMPUTE_CORRELATIONS(process): computes correlations between miRNA and transcript expression levels,and writes the results to individual TSV files for each miRNA-target interaction specified in the input binding sites file.
This will be the entry point for the SPONGING analysis module mentioned in Issue 137.
LINT RESULTS SUMMARY
[✔] 569 Tests Passed
[?] 0 Tests Ignored
[!] 23 Test Warnings
[✗] 0 Tests Failed