Returns high-level configuration info on this VISION session. Mostly used to enable/disable features in the visualizer.
- 'name': A title for this session (shown in the top title bar)
- 'meta_sigs': Names of meta-data signatures. Sent here as a convenience as numeric meta-data signatures and gene signatures get combined in the display and often lookups are needed to distinguish.
- 'ncells': Total number of cells
- 'pooled': Whether or not there is micro-pooling
- 'has_sigs': Whether or not there are gene signatures
- 'has_proteins': Whether or not there are CITE-seq proteins
- 'has_lca': Whether or not LC Annotator analysis is available
- 'has_tree': Whether or not Trajectories are available
Response structure:
{
'name': 'Session Name',
'meta_sigs': [list of string],
'ncells': int,
'pooled': bool,
'has_sigs': bool,
'has_proteins': bool,
'has_lca': bool,
'has_tree': bool,
}
Return the per-cell signature scores for signature: <sig_name>
Data comes from obj@SigScores matrix
Response structure:
{
'cells': [list of str, cell ids...],
'values': [list of Number, per cell signature scores],
}
Return the per-cell meta-data values for variable: <sig_name>
Data comes from obj@metaData dataframe
Response structure:
{
'cells': [list of str, cell ids...],
'values': [list of Number or string, per-cell meta-data values],
}
Returns information associated with a signature Data comes from object@sigData
Response structure:
{
'sigDict': { # signature-gene weights
'GeneName1': 1,
'GeneName2': -1,
...
},
'name': 'Signature Name',
'source': 'Signature source', # typically filename where signature was loaded from
'metaData': 'Signature description...', # second column in .gmt file
'geneImportance': { # signature-gene importance values
'GeneName1': .1,
'GeneName2': .01,
...
}
}
Returns expression values for <sig_name> grouped by <cluster_var>.
This is used to generate the gene x cluster heatmap in the bottom left
Values are computed on the fly at the server
Response structure
{
'data': list of list of Number (2d matrix, outer index is row index)
'sample_labels': column labels for the matrix in 'data'
'gene_labels': row labels for the matrix in 'data'
}
Returns the per-cell protein expression values for <protein_name>
Data comes from obj@proteinData matrix
Response structure:
{
'cells': [list of str, cell ids...],
'values': [list of Number, per cell protein expression],
}
For each signature, describes the assignment of signatures to signature-clusters This is used to group signatures in the upper-left section
Response structure:
{
"Signature Name" (str): <cluster_number> (int),
...
}
For each protein, describes the assignment of proteins to protein-clusters Proteins aren't actually clustered in the interface. Every protein is assigned to cluster #1
Response structure:
{
"Protein Name" (str): 1,
...
}
For each meta-data variable, describes the assignment of each variable to meta-data clusters This is used when micropools are created to group factor variables with their expanded percent-value-per-micropool representations
Response structure:
{
"Metadata variable Name" (str): <cluster_number> (int),
...
}
Returns the coordinates for projection <proj_name> in column <proj_col>
Since the scatter plot can show more than just projects, this has been expanded to also
return coordinates from the latent space or other meta-data variables. <proj_name> can
come from names in object@Projections, or can be "Meta Data" to refer to object@metaData or
"Latent Space" to refer to object@LatentSpace. In either case <proj_name> should refer
to an associated column.
Response structure:
List of list of [coordinate, 'cell id']
[
[coordinate (float): 'cell id' (str)],
[coordinate (float): 'cell id' (str)],
[coordinate (float): 'cell id' (str)],
...
[
Returns information on projections and other variables that can be plotted in the main scatter-plot panel. Used to create the dropdown menus.
Response structure:
Dictionary where keys are the name of projections/meta data/latent space and the values are a list of the associated columns
{
'projection_name_1': list of column names in the projection,
'projection_name_2': list of column names in the projection,
'Meta Data': list of numeric meta-data variables,
'Latent Space': list of column names in the latent space
}
Gets information for the LC Annotator - the correlation of each signature with each latent component
Response structure:
{
"zscores": list of list of correlation coefficients (N signatures x N components),
"pvals": list of list of p-values (N signatures x N components),
"proj_labels": list of latent space column names in the same order as columns of 'zscores'/'pvals',
"sig_labels": list of signature names in the same order as columns of 'zscores'/'pvals',
}
Gets information for the LC Annotator - the correlation of each protein with each latent component
Response structure:
{
"zscores": list of list of correlation coefficients (N proteins x N components),
"pvals": list of list of p-values (N proteins x N components),
"proj_labels": list of latent space column names in the same order as columns of 'zscores'/'pvals',
"sig_labels": list of proteins names in the same order as columns of 'zscores'/'pvals',
}
Gets information for the LC Annotator - the correlation of each numeric meta-data variable with each latent component
Response structure:
{
"zscores": list of list of correlation coefficients (N variables x N components),
"pvals": list of list of p-values (N variables x N components),
"proj_labels": list of latent space column names in the same order as columns of 'zscores'/'pvals',
"sig_labels": list of variables names in the same order as columns of 'zscores'/'pvals',
}
Requests a differential expression analysis from the server.
Determines the set of cells used for the numerator (i.e. _num or _n) and for the denominator (i.e. _denom or _d)
Examples:
- To select cells in cluster 5 for the numerator set
'type_n': 'meta','subtype_n': 'cluster','group_num': 'Cluster 5' - To select cells in a saved manual selection for the numerator set
'type_n': 'saved_selection','group_num': 'name_of_selection' - To select a specific set of cell ids for the numerator set
'type_n': 'current','group_num': list of cell ids
Posted data structure:
{
'type_n': either 'current', 'meta', or 'saved_selection'
'type_d': either 'remainder', 'meta', or 'saved_selection'
'subtype_n': which meta-data variable to group cells by if type_n is 'meta'
'subtype_d': which meta-data variable to group cells by if type_d is 'meta'
'group_num': list of cell ids (if type_n is 'current') OR name of saved selection (if type_n is 'saved_selection')
OR value of categorical meta-data variable (if type_n is 'meta')
'group_denom': same behavior as 'group_num'
'min_cells': (int) pre-filter genes expressed in less than this many cells
'subsample_groups': (bool), whether or not to subsample each comparison group first
'subsample_N': (int) size of the groups after subsampling. Ignored if 'subsample_groups' is false
}
Response structure:
DE Results table with {'column name' -> list of values}
{
'Feature': list of feature (gene or protein) names
'Type': list of either 'Gene' or 'Protein'
'logFC': list of log-fold-change values
'stat': list of AUC values
'pval': list of FDR-corrected p-values
}
The display of the top-left area for signatures/proteins/meta-data depends on the selected grouping variable in the dropdown. Commands scoped to a particular grouping variable are nested under "/Clusters".
This call returns a list of grouping variables and the levels/categories associated with them.
Response structure:
{
'name of variable': [list of str - values this variable can take],
'name of variable': [list of str - values this variable can take],
'Cell Type': ['CD4+', 'CD8+', 'NK'], # For example
}
Returns matrices consisting of test statistic and p-value for 1 vs. all differential signature tests and for local autocorrelation.
First column is "Score" and values are for local autocorrelation. Statistic is the 1 - Geary's C.
Other columns are for 1 vs. all differential signature tests for each value in the selected grouping variable in the dropdown. Test statistic are the AUC values from a ranksums test. P-values also from this test.
Response structure:
{
'sig_labels': [list of str] # Rows of matrices in zscores and pvals
'proj_labels': [list of str] # Columns of the matrices in zscores and pvals
'zscores': [list of list of number] # signatures x cell group (+ 'Score') matrix of test statistics
'pvals': [list of list of number] # signatures x cell group (+ 'Score') matrix of p-values
}
Same as /Clusters/<cluster_variable>/SigProjMatrix/Normal, but for meta-data variables
Response structure:
{
'sig_labels': [list of str] # Rows of matrices in zscores and pvals
'proj_labels': [list of str] # Columns of the matrices in zscores and pvals
'zscores': [list of list of number] # variables x cell group (+ 'Score') matrix of test statistics
'pvals': [list of list of number] # variables x cell group (+ 'Score') matrix of p-values
}
Same as /Clusters/<cluster_variable>/SigProjMatrix/Normal, but for CITE proteins
Response structure:
{
'sig_labels': [list of str] # Rows of matrices in zscores and pvals
'proj_labels': [list of str] # Columns of the matrices in zscores and pvals
'zscores': [list of list of number] # proteins x cell group (+ 'Score') matrix of test statistics
'pvals': [list of list of number] # proteins x cell group (+ 'Score') matrix of p-values
}
Not used anymore
Not used anymore
Retrieves a list of genes for which expression values can be plotted. Used to populate the dropdown in the 'Genes' tab.
Response structure:
[list of str - gene names]
Gets the per-cell expression of the gene specified by <gene_name>.
Expression values returned are on a log2 scale.
Response structure: Items in 'values' correspond to the cells in 'cells' in order
{
'cells': [list of str - cell identifiers],
'values': [list of number - gene expression values],
}
Retrieves meta-data information for an individual cell specified by <cell_id>
Response structure:
{
'variable name': value (str or number),
'variable name': value (str or number),
'variable name': value (str or number),
...
}
Retrieves meta-data information for a group of cells
Posted data structure
[list of cell id]
Response structure:
{
'numeric': {
'<variable name>': {
'Min': <min value>,
'Median': <median value>,
'Max': <max value>,
},
'<variable name>': {
'Min': <min value>,
'Median': <median value>,
'Max': <max value>,
},
# Repeat for additional numeric meta-data variables
},
'factor': {
'<variable name>': {
'<factor level 1>': number (proportion of cells assigned to this level,
'<factor level 2>': number (proportion of cells assigned to this level,
'<factor level 3>': number (proportion of cells assigned to this level,
...
}
# Repeat for additional factor meta-data variables
}
}
Used when loading a selection of cells.
Response structure:
[list of str - names of saved selections]
Retrieves the cells associated with the selection, <selection_id>
Response structure:
[list of str - cell ids in the indicated cell selection]
Saves a cell selection with name <selection_id>
[list of str - cell ids to be assigned to this cell selection]
Get the list of different tree layouts that are available Used to populate the 'Projection' dropdown under the 'Trajectories' view
R version: returns the names of object@TrajectoryProjections
Response structure:
[list of str - names of tree projections]
Returns the coordinates for the tree layout <proj_name> in addition
to the position of individual cells
Response structure:
[
[
[<x val>, <y val>, <cell id>], # coordinates for individual cells
[<x val>, <y val>, <cell id>],
[<x val>, <y val>, <cell id>],
...
],
[
[<x val>, <y val>], # coordinates for internal tree nodes
[<x val>, <y val>],
[<x val>, <y val>],
...
],
[list of list of number] # 0/1 adjacency matrix for internal tree nodes
]
Returns matrices consisting of test statistic and p-value trajectory autocorrelation
Format is similar to /Clusters/<cluster_variable>/SigProjMatrix/Normal, but without
the 1 vs all test results.
'zscores' and 'pvals' matrices have just a single column
Response structure:
{
'sig_labels': [list of str] # Rows of matrices in zscores and pvals
'proj_labels': ["Score"],
'zscores': [list of list of number] # signatures x 1 matrix of test statistics
'pvals': [list of list of number] # signatures x 1 matrix of p-values
}
Same as /Tree/SigProjMatrix/Normal but for meta-data variables
'zscores' and 'pvals' matrices have just a single column
Response structure:
{
'sig_labels': [list of str] # Rows of matrices in zscores and pvals
'proj_labels': ["Score"],
'zscores': [list of list of number] # variables x 1 matrix of test statistics
'pvals': [list of list of number] # variables x 1 matrix of p-values
}
Same as /Tree/SigProjMatrix/Normal but for CITE protein expression values
'zscores' and 'pvals' matrices have just a single column
Response structure:
{
'sig_labels': [list of str] # Rows of matrices in zscores and pvals
'proj_labels': ["Score"],
'zscores': [list of list of number] # proteins x 1 matrix of test statistics
'pvals': [list of list of number] # proteins x 1 matrix of p-values
}