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Analysis and Design of Single-cell RNA Sequencing Data Normalization Algorithms

Mohseni, Sepideh | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55247 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Hossein Khalaj, Babak
  7. Abstract:
  8. Single Cell RNA sequencing (scRNA-seq) data provides more information about gene expression at cellular level. However, because of noise and sparsity that exist in scRNA-seq data, analysis of this data has faced to obstacles. Global normalization approach can not resolve correctly missing data that come from technical variability. So this approach cause emerging incorrect bias and dishonest conclusion about cell type. In this study we review some models for scRNA-seq data imputation,explain a new method for filtering genes and clustering data and use matrix completion algorithm for imputation data
  9. Keywords:
  10. Error Correction ; RNA Sequencing ; Single Cell Sequencing ; Dropout Imputation ; Single Cell RNA Sequencing (scRNA-seq) ; Data Normalizing ; Gene Expression Data

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