Analysis tasks¶
compileoutput¶
BypassAnalyzedData¶
Description:
Creates a copy of a user-selected .csv file. This enables easy integration
with any of the downstream analysis tasks
Parameters:
* source_file – Path to file that should be copied
* overwrite – Boolean to indicate whether to overwrite any files present in this analysis task
AggregateMERlinData¶
Description:
Loads the output of a selected analysis task from MERlin for each dataset included
in the metaDataSet and combines them into a single, vertically concatenated file.
Parameters:
* task_to_aggregate – Name of the MERlin task for which the analysis result should be concatentated
* overwrite – Boolean to indicate whether to overwrite any files present in this analysis task
cluster¶
Clustering¶
Description:
performs graph-based clustering of cells based on the provided data, most
typically expression measurements. This method assumes that you want to use
every entry in your input dataset for clustering
Parameters:
* file_creation_task – Name of the compileoutput task that contains the expression data
* prior_clustering – Name of the Clustering task, if any, that preceded this round of clustering
(this is typically used when reclustering a subset of cells that were partitioned out in a prior clustering round.
* cell_type – The name of the type of cells that are to be clustered (used in conjunction with prior_clustering, see examples/cellTypeAnnotations.csv).
* k_values – A list of the k values to use when constructing the k-nearest neighbor graph
* resolutions – A list of the resolutions to use for clustering
* use_PCs – Boolean indicating whether to reduce dimensionality with PCA. Only PCs explaining more variance than the 1st PC of a randomized version of the dataset are kept
* cluster_min_size – Minimum number of cells that must be in a cluster
* clustering_algorithm – Modularity optimization algorithm to use, either leiden or louvain
BootstrapClustering¶
Description:
Performs clustering on randomly downsampled (in terms of rows) instance of the input data matrix.
Parameters:
* bootstrap_frac – Fraction of rows to retain
* bootstraps – Number of different downsamplings to analyze for a given k value and resolution pairing
* cluster_task – Name of the Clustering task that this bootstrap analysis is associated with (this
ensures that the same set of clustering parameters are used between that clustering and the bootstrap clusterings).
ClusterStabilityAnalysis¶
Description:
Calculates the stability of clusters based on jaccard similarity of the most
pair of clusters from a full clustering result and a bootstrap clustering result when
analyzed with the same k value and resolution, for all k value and resolution pairs analyzed.
The clustering parameters that yielded the clustering result that contains at least 90% of
the cells (or whatever is set as min_fraction_cells) in stable clusters and also yielded
the greatest number of clusters is selected, and the full stability metrics are output to a table.
If a cellTypeAnnotations.csv file is placed in the base directory of this analysis task it can be used
to retrieve a subset of cells based on the labels on that annotation and the selected clustering result.
Parameters:
* min_fraction_cells: Minimum number of cells that must be in stable clusters for a result to be considered
* cluster_task: Name of the Clustering task to get results from
* bootstrap_cluster_task: name of the BootstrapClustering task to get results from
* kValues_to_consider: list of k values to use in stability analysis if restricting to a subset of those analysed in the clustering
* resolutions_to_consider: list of resolutions to use in stability analysis if restricting to a subset of those analysed in the clustering