Hobotnica: exploring molecular signature quality
| Autor: | Alexey Sizykh, Yulia A. Medvedeva, Sarah J. Wheelan, Bahman Afsari, Alexey Stupnikov, Alexander V. Favorov, Luigi Marchionni |
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| Rok vydání: | 2021 |
| Předmět: |
Measure (data warehouse)
Modalities General Immunology and Microbiology Computer science media_common.quotation_subject Gene Expression Profiling Experimental data Computational Biology Gold standard (test) General Medicine computer.software_genre Signature (logic) General Biochemistry Genetics and Molecular Biology Phenotype Distance matrix Quality (business) Data mining General Pharmacology Toxicology and Pharmaceutics Set (psychology) computer media_common |
| Zdroj: | F1000Research. 10 |
| ISSN: | 2046-1402 |
| Popis: | A Molecular Features Set (MFS), is a result of vast diversity of bioinformatics pipelines. In case when MFS is used for further analysis to distinguish between phenotypes, it is often referred to as a signature. Lack of the “gold standard” for most experimental data modalities makes it hard to provide valid estimation for a particular MFS’s quality. Yet, this goal can partially be achieved by analyzing inner-sample Distance Matrix (DM) and their power to distinguish between phenotypes.The quality of a DM can be assessed by summarizing its power to quantify the differences of inner-phenotype and outer-phenotype distances. This estimation of the DM quality can be construed as a measure of the MFS’s quality.Here we propose Hobotnica, an approach to estimate MFS’s quality by their ability to stratify data, and assign them significance scores, that allows for collating various signatures and comparing their quality for contrasting groups. |
| Databáze: | OpenAIRE |
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