User’s Guide¶
Creat MICTI Object¶
$MICTI(data,geneNames,cellNames,k=None,cluster_label=None,cluster_assignment=None, th=0,seed=None, ensembel=False, organisum=”hsapiens”)
Input¶
data¶
Input data as sparce or dense matrix where the rows are cells and the columns are genes
geneNames¶
List of gene names
cellNames¶
List of cell names
k¶
The number of clusters or cell types
cluster_label¶
List of cluster lablees /cell types names
cluster_assignment¶
An aaray of cluster assignment for each of cells
th¶
The treshold gene expression value to consider a certain gene is expressed or not
ensembel¶
A boolian value indicating the given gene name is ENSEBEL gene Id or not
organisum¶
The organisum where dataset belong eg. hsapiens or mmusculus
Output¶
The output is the MICTI object
Data visualisation¶
$MICTI.get_Visualization(dim=2,method="tsne")
Input¶
dim¶
The number of dimension for visualisation dim=2 or dim=3
method¶
The method used for low dimensional visualisation, method=”PCA” or method=”tsne”
Output¶
Returns none. Desplays the lower dimensional representation of the dataset
Clustering cells¶
$MICTI.cluster_cells(numberOfCluster, method="kmeans", maxiter=500)
Input¶
numberOfCluster¶
The number of clusters
method¶
The method used for clustering. There are two options, ie. method=”kmeans” for kmeans clustering or method=”GM” gaussian mixture model for clustering
maxiter¶
The maximum iteration that the k-means or Gaussian mixture algorithm takes in the clustering process.
Output¶
Returns None, assigning each cells into k clusters
Cell-type marker genes¶
$MICTI.marker_gene_FDR_p_value(clusterNo)
Input¶
clusterNo¶
The cluster number. Each clusters are identified by number. For example, if there are six clusters/cell-types, the cluster numbers are from 0-5.
Output¶
Returns a table with Z-score, p-value and FDR p-value for each of the genes.
significant cluster markers¶
$MICTI.get_markers_by_Pvalues_and_Zscore(clusterNo,threshold_pvalue=.01, threshold_z_score=0)
Input¶
clusterNo¶
The cluster number. Each clusters are identified by number. For example, if there are six clusters/cell-types, the cluster numbers are from 0-5.
threshold_pvalue¶
The threshold FDR p-value. Genes/Markers with less than the threshold FDR p-value are selected.
threshold_z_score¶
The threshold Z-scores. Genes/markers with greater than the threshold z-score are selected.
Output¶
Returns a table with Z-score, p-value and FDR p-value of significantlly cell-type/cluster marker genes filtered by FDR Pvalue and Z-score.