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Update step5_par.txt
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fiorini9 authored Nov 10, 2023
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Showing 1 changed file with 20 additions and 17 deletions.
37 changes: 20 additions & 17 deletions scrnabox.slurm/hto/pars/step5_par.txt
Original file line number Diff line number Diff line change
Expand Up @@ -22,49 +22,52 @@ par_one_seurat= "no"
############################################################################
# If you have multiple Seurat objects, choose whether you want to integrate or merge the objects
############################################################################
## integrate Seurat objects
par_integrate_seurat= "yes"
par_merge_seurat= "no"


############################################################################
# Parameters for integration
############################################################################
## Which dimensions to use from the CCA to specify the neighbour search space
par_FindIntegrationAnchors_dim= 25
## merge Seurat objects
par_merge_seurat= "no"


############################################################################
# Parameters for normalization and scaling
# even if you opt to skip integration, adjust the following parameters
# Even if you opt to skip integration, adjust the following parameters
############################################################################
## Assay to perform normalization and scaling. For most use cases this will be RNA
## Assay to perform normalization and scaling (prior to integration). For most use cases this will be RNA
par_DefaultAssay= "RNA"

## Normalization method
par_normalization.method= "LogNormalize"

## Scale factor for normalization
## Scale factor
par_scale.factor= 10000


############################################################################
# Parameters for integration
############################################################################
## Method for detecting top variable features. vst, mean.var.plot (mvp), dispersion (disp)
par_selection.method= "vst"

## Number of features to select as top variable features
## Number of features to select as top variable features for integration
par_nfeatures= 2500

## Which dimensions to use from the CCA to specify the neighbour search space
par_FindIntegrationAnchors_dim= 25


############################################################################
# Parameters for linear dimensional reduction
# even if you opt to skip integration, adjust the following parameters
############################################################################
## The number of neighbouring points used in local approximations of manifold structure
par_RunUMAP_n.neighbors= 65

## Total Number of PCs to compute and store for RunPCA
par_RunPCA_npcs= 30

## Which dimensions to use as input features for RunUMAP
par_RunUMAP_dims= 30
## Which dimensions to use as input features for RunUMAP
par_RunUMAP_dims= 25

## The number of neighbouring points used in local approximations of manifold structure.
par_RunUMAP_n.neighbors= 45

## whether or not to perform JackStraw computation. This computation takes a long time.
## Whether or not to perform JackStraw computation. This computation takes a long time.
par_compute_jackstraw= "no"

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