Computational Systems Biology Methods and Protocols.7z

TASIC

Temporal Assignment of SIngle

Cells (TASIC) uses on aprobabilistic graphical modelto integrate expression andtime information making itmore robust to noise andstochastic variations. It uses aHidden Markov Model(HMM) based on aprobabilistic Kalman Filterapproach to combine time andexpression information fordetermining the branchingprocess associated with timeseries single-cell studies

Input1. Gene expression mat file

containing normalized geneexpression value. The‘expression_matrix’ matrixdimension is # of genes * # ofcells. 2. Time label mat filecontaining an array denotingthe time assignment of cells,e.g., time_label

¼

[0 0 0 24

24 24], for six cells where firstthree are from time point0 and the last three are fromtime point 24 h

Package

Command

line

Unix/

Linux,Mac OS,Windows

MATLAB [

107

]

Gpfates

Models transcriptional cell fates

as mixtures of the GaussianProcess Latent Variable Modeland Overlapping Mixtures ofGaussian Processes (OMGP)

NA

Package

Command

line

Unix/

Linux

Python

[^108

]

SCOUP

A method to analyze single-cell

expression data fordifferentiation. Unlikeprevious methods, which usedimension reductionapproaches and reconstructdifferentiation trajectories inreduced space, SCOUPdescribes gene expressiondynamics duringdifferentiation directly,including pseudotime and cellfate

The following two libraries are

necessary for pseudotimeestimation based on theshortest path on the PCAspace: LAPACK, BLAS

Package

Command

line

Unix/

Linux

C[

109

]

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Applications of Single-Cell Sequencing for Multiomics 347