This folder consists of scripts for the following paper studying the cell cycle analysis of M.Tuberculosis at TAMU-Bioinformatics Ioerger Lab.
- Bandekar, Aditya C., Sishir Subedi, Thomas R. Ioerger, and Christopher M. Sassetti. "Cell-cycle-associated expression patterns predict gene function in mycobacteria." Current Biology 30, no. 20 (2020): 3961-3971.
Major sections are:
- normalization and identifying significant genes (anova analysis)
- operon modeling and comparison with published literature
- periodicity analysis of gene expression using fft,metacycle, curve-fitting
- smoothing of gene expression and transposon data using bayesian gaussian regression
- peak assignment for gene expression
- principle component analysis of expression data
- sparse regression optimization and modeling (heuristic – graph algorithms)
- weighted correlation model hard/soft thresholding
- sigma factor motif discovery using finite state machine algorithms
- non linear modeling using radial basis function
- phase analysis using bi clustering algorithms