Finite-size effects in transcript sequencing count distribution: Its power-law correction necessarily precedes downstream normalization and comparative analysis

Finite-size effects in transcript sequencing count distribution: Its power-law correction necessarily precedes downstream normalization and comparative analysis

10.1186/s13062-018-0204-y

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Bibliographic Details
Main Authors: Wong, W.-C, Ng, H.-K, Tantoso, E, Soong, R, Eisenhaber, F
Other Authors: PATHOLOGY
Format: Article
Published: 2020
Subjects:
microRNA
animal
genetics
human
theoretical model
tumor cell line
Animals
Cell Line, Tumor
Humans
MicroRNAs
Models, Theoretical
Online Access:https://scholarbank.nus.edu.sg/handle/10635/173740
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Institution: National University of Singapore
Description
Summary:10.1186/s13062-018-0204-y

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