Cell-Single cell data analysis tool
The Cell-Single cell data analysis tool provides six key interactive and customizable functions
including clustering, differential abundance analysis (DAA), global differential abundance analysis
(GDAA), box plotting, Cluster Activity and cell-cell interaction network based on 13 single cell
datasets of cancer immunotherapy including 307485 cells from 7 cancer types.
The Cell-Single cell data analysis tool enables users to flexibly explore the association between
cell clusters and cancer immunotherapy, analyze tumor microenvironment and the function and mechanism
of immunotherapy-related cell clusters base on single cell datasets of cancer immunotherapy.
View our Help page for further detailed information.
Clustering
This feature allows the user to perform cluster analysis on single-cell data of cancer immunotherapy.
Differential Abundance Analysis (DAA)
This function allows user to obtain differential abundance analysis and heatmap for cell clusters in a specific immunotherapy related single cell dataset. The DAA includes comparing the abundance of cell cluster between immunotherapy treatment vs no treatment samples, and immunotherapy response vs no response samples. This feature allows user to apply custom thresholds on a given dataset.
Box Plotting
This function generates box plots for comparing abundance of a specific cell cluster between immunotherapy treatment vs no treatment samples or immunotherapy response vs no response samples.
Cluster Activity
Users can explore the activity of marker genes of different cell types in clusters to characterize different clusters.
Global Differential Abundance Analysis (GDAA)
This function allows user to obtain differential abundance analysis and heatmap for cell types from CellMarker database by globally considering multiple different cancer immunotherapy datasets. This feature allows user to compare the degree and direction of differential abundance of cells in different cancer immunotherapy datasets.
Cell Interaction Network
This function generates two cell cluster-cell cluster interaction networks under different immunotherapy conditions including immunotherapy treatment vs no treatment or immunotherapy response vs no response.
This function allows user to obtain differential abundance analysis and heatmap for cell
clusters in a specific immunotherapy related single cell dataset of cancer. The DAA includes comparing
the abundance of cell cluster between immunotherapy treatment vs no treatment samples,
and immunotherapy response vs no response samples. This feature allows user to apply custom
thresholds on a given dataset.
Immunotherapy conditions: select an interested immunotherapy condition (T/NT or R/NR).
T/NT: immunotherapy treatment vs no treatment; R/NR: immunotherapy response vs no response.
Dataset Select: select a specific single-cell dataset under the corresponding immunotherapy condition for differential analysis.
Immunotherapy conditions
Dataset Select
This function allows user to obtain differential abundance analysis and heatmap for cell
types from CellMarker database by globally considering multiple different immunotherapy
datasets of cancer. Single-sample GSEA algorithm was used to evaluate the activity of marker
genes of different cell types from the CellMarker database in each cell. This feature allows
user to compare the degree and direction of differential abundance of cell types from the
CellMarker database in different immunotherapy single-cell datasets.
Immunotherapy conditions: select an interested immunotherapy condition (T/NT or R/NR).
T/NT: immunotherapy treatment vs no treatment; R/NR: immunotherapy response vs no response.
Total differ number: the minimum number of immunotherapy datasets that the abundance of cells is differential (pvalue <= 0.05 & (FC >=2 | FC <= 0.5)).
Differ number up: the minimum number of datasets that the abundance of cells is significantly high
(T/NT or R/NR) in immunotherapy treatment (response) individuals. The significance thresholds were set as pvalue <= 0.05 & (FC >=2 | FC <= 0.5).
Differ number down: the minimum number of datasets that the abundance of cells is significantly low (T/NT or R/NR) in
immunotherapy no treatment (no response) individuals. The significance thresholds were set as pvalue <= 0.05 & (FC >=2 | FC <= 0.5).
Immunotherapy conditions
Total differ number
Differ number up
Differ number down
This function generates box plots for comparing abundance of a specific cell cluster between cancer
immunotherapy treatment (drug) vs no treatment (nodrug) samples or immunotherapy response vs no response samples.
Immunotherapy conditions: select an interested immunotherapy condition (T/NT or R/NR) for drawing the boxplot.
T/NT: immunotherapy treatment (drug) vs no treatment (nodrug); R/NR: immunotherapy response vs no response.
Dataset Select: select a specific single-cell dataset under the corresponding immunotherapy condition for drawing the boxplot.
Cluster: select a cell cluster for drawing the boxplot.
Immunotherapy conditions
Dataset Select
Cluster
This feature allows the user to perform cluster analysis on single-cell data of cancer immunotherapy.
The clustering function is performed based on R package Seurat with default parameters.
Immunotherapy conditions: select an interested immunotherapy condition (T/NT or R/NR) for cell clustering.
T/NT: immunotherapy treatment (drug) vs no treatment (nodrug); R/NR: immunotherapy response vs no response.
Dataset select: select a specific single-cell dataset under the corresponding immunotherapy condition for cell clustering.
Immunotherapy conditions
Dataset select
Users can explore the activity of marker genes of different cell types in clusters to characterize different clusters.
For cell type:
Immunotherapy conditions: select an interested immunotherapy condition (T/NT or R/NR). T/NT: immunotherapy treatment vs no treatment; R/NR: immunotherapy response vs no response.
Dataset select: select a specific single-cell dataset under the corresponding immunotherapy condition.
Cell type: select a cell type to explore the activity of its maker genes in different clusters of the corresponding immunotherapy dataset.
Top N: select the number of clusters to shown according to the activity of the selected cell type (from high to low).
Immunotherapy conditions
Dataset Select
Cell type
This function generates two cell cluster-cell cluster interaction networks under
immunotherapy treatment (drug) vs no treatment (nodrug) or immunotherapy response vs no response respectively.
Immunotherapy conditions: select an interested immunotherapy condition (T/NT or R/NR).
T/NT: immunotherapy treatment (drug) vs no treatment (nodrug); R/NR: immunotherapy response vs no response.
Dataset Select: select a specific single-cell dataset under the corresponding immunotherapy condition.
Top N: select the number of cell cluster-cell cluster interactions
to shown according to the significance of interaction (from high to low).