NDRindex: a method for the quality assessment of single-cell RNA-Seq preprocessing data
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SOFTWARE
NDRindex: a method for the quality assessment of single‑cell RNA‑Seq preprocessing data Ruiyu Xiao1, Guoshan Lu1, Wanqian Guo2 and Shuilin Jin2,3*
From Biological Ontologies and Knowledge bases workshop 2019 San Diego, CA, USA. 18-21 November 2019 *Correspondence: [email protected] 3 School of Mathematics, Harbin Institute of Technology, Harbin, China Full list of author information is available at the end of the article
Abstract Background: Single-cell RNA sequencing can be used to fairly determine cell types, which is beneficial to the medical field, especially the many recent studies on COVID19. Generally, single-cell RNA data analysis pipelines include data normalization, size reduction, and unsupervised clustering. However, different normalization and size reduction methods will significantly affect the results of clustering and cell type enrichment analysis. Choices of preprocessing paths is crucial in scRNA-Seq data mining, because a proper preprocessing path can extract more important information from complex raw data and lead to more accurate clustering results. Results: We proposed a method called NDRindex (Normalization and Dimensionality Reduction index) to evaluate data quality of outcomes of normalization and dimensionality reduction methods. The method includes a function to calculate the degree of data aggregation, which is the key to measuring data quality before clustering. For the five single-cell RNA sequence datasets we tested, the results proved the efficacy and accuracy of our index. Conclusions: This method we introduce focuses on filling the blanks in the selection of preprocessing paths, and the result proves its effectiveness and accuracy. Our research provides useful indicators for the evaluation of RNA-Seq data. Keywords: Single-cell, RNA-seq, Normalization, Dimension reduction, Preprocess path
Background Nowadays, single-cell RNA sequencing is being generally used in biology and iatrology related areas. The efficient methods used in COVID-19 researches these days would be a good example. Many researchers used single cell RNA sequencing data to determine the sensitivity of organs other than the lungs, and found that the heart, esophagus, kidney, and ileum are also munitive organs [1–4]. One of the main advantages of single-cell RNA sequencing (scRNA-Seq) is that it can be clustered unsupervised to determine cell © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not per
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