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

• Main Authors: Ng, Hong-Kiat, Wong, Wing-Cheong, Tantoso, Erwin, Soong, Richie, Eisenhaber, Frank
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2018
• Subjects: Finite-size Effects; Nyquist Sampling Criterion
• Online Access: https://hdl.handle.net/10356/86009; http://hdl.handle.net/10220/45276
• Institution: Nanyang Technological University

Background: Though earlier works on modelling transcript abundance from vertebrates to lower eukaroytes have specifically singled out the Zip’s law, the observed distributions often deviate from a single power-law slope. In hindsight, while power-laws of critical phenomena are derived asymptotically...