scHicClusterCompartments¶
scHicClusterCompartments uses kmeans or spectral clustering to associate each cell to a cluster and therefore to its cell cycle. The clustering is applied on dimension reduced data based on the A/B compartments track. This approach reduces the number of dimensions from samples * (number of bins)^2 to samples * (number of bins). Please consider also the other clustering and dimension reduction approaches of the scHicExplorer suite. They can give you better results, can be faster or less memory demanding.
usage: scHicClusterCompartments --matrix scool scHi-C matrix
[--numberOfClusters NUMBEROFCLUSTERS]
--outFileName OUTFILENAME
[--clusterMethod {spectral,kmeans}]
[--chromosomes CHROMOSOMES [CHROMOSOMES ...]]
[--norm] [--binarization]
[--extraTrack EXTRATRACK]
[--histonMarkType HISTONMARKTYPE]
[--threads THREADS] [--help] [--version]
Required arguments¶
- --matrix, -m
The single cell Hi-C interaction matrices to cluster. Needs to be in scool format
- --numberOfClusters, -c
Number of to be computed clusters
Default: 12
- --outFileName, -o
File name to save the resulting clusters
Default: “clusters.txt”
- --clusterMethod, -cm
Possible choices: spectral, kmeans
Algorithm to cluster the Hi-C matrices
Default: “spectral”
Optional arguments¶
- --chromosomes
List of chromosomes to be included in the correlation.
- --norm
Different obs-exp normalization as used by Homer software.
Default: False
- --binarization
Set all positive values of eigenvector to 1 and all negative ones to 0.
Default: False
- --extraTrack
Either a gene track or a histon mark coverage file(preferably a broad mark) is needed to decide if the values of the eigenvector need a sign flip or not.
- --histonMarkType
set it to active or inactive. This is only necessary if a histon mark coverage file is given as an extraTrack.
Default: “active”
- --threads, -t
Number of threads. Using the python multiprocessing module.
Default: 4
- --version
show program’s version number and exit