Description Usage Arguments Value References See Also
View source: R/computePersistence.R
Takes a data.frame
of numeric gene expression over time (genes X ZT times) and computes the persistence score using getPersistence
.
For a given gene, each lag (min to max) is used to transform the expression into a 3-D embedded space via time-delay embedding.
A non-linear dimension reduction technique (laplacian eigenmaps) is used to transfrom the 3-D embedding to a 2-D embedding.
Finally, the persistence score of the 2-D embedding is calculated via persistence homology.
The median persistence score across all lags (min to max) for each gene is returned as a numeric vector.
For more details see TimeCycle's vignette:
vignette("TimeCycle")
.
1 2 3 4 5 6 7 | computePersistence(
data,
minLag = 2,
maxLag = 5,
cores = parallel::detectCores() - 2,
laplacian = T
)
|
data |
a |
minLag |
a |
maxLag |
a |
cores |
a |
laplacian |
a |
a vector
of the median persistence score across lags (minLag to maxLag) for each gene in data
Wadhwa RR, Williamson DFK, Dhawan A, Scott JG. (2018). "TDAstats: R pipeline for computing persistent homology in topological data analysis." Journal of Open Source Software. 2018; 3(28): 860. doi:[10.21105/joss.00860]
Bauer U. (2019). "Ripser: Efficient computation of Vietoris-Rips persistence barcodes." arXiv: 1908.02518.
calculate_homology
for Persistence Homology calculation.
buildTakens_ndim
for for generating time-delay embedding.
computeLaplacianEmbedding
for 3-D to 2-D laplacian eigenmaps dimension reduction.
getPersistence
for use on a single gene expression time-series.
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