workflows/rna/rna_multisample

Description

Processing unimodal multi-sample RNA transcriptomics data.

Type

nextflow_script

License

MIT

Links

Repository

Contributors

Launch

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
id: "run"  
modality: [ "rna" ]  
output: "$id.$key.output.h5mu"  
highly_variable_features_var_output: [ "filter_with_hvg" ]  
highly_variable_features_obs_batch_key: [ "sample_id" ]  
highly_variable_features_flavor: [ "seurat" ]  
var_qc_metrics: [ "filter_with_hvg" ]  
top_n_vars: [ 50, 100, 200, 500 ]  
output_obs_num_nonzero_vars: [ "num_nonzero_vars" ]  
output_obs_total_counts_vars: [ "total_counts" ]  
output_var_num_nonzero_obs: [ "num_nonzero_obs" ]  
output_var_total_counts_obs: [ "total_counts" ]  
output_var_obs_mean: [ "obs_mean" ]  
output_var_pct_dropout: [ "pct_dropout" ]  
scaling_output_layer: [ "scaled" ]  
publish_dir: "output/"  
EOM

nextflow run https://packages.viash-hub.com/vsh/openpipeline.git \  
  -revision v4.0.0 \  
  -main-script target/nextflow/workflows/rna/rna_multisample/main.nf \  
  -params-file params.yaml

Inputs

Name	Type & Properties	Description
--id	string required	ID of the concatenated file
--input	file required	Path to the samples.
--modality	string	Modality to process.
--layer	string	Input layer to use. If not specified, .X is used.

Name

Type & Properties

--id

string

required

--input

file

required

--modality

string

--layer

string

Output

Name	Type & Properties	Description
--output	file required output	Destination path to the output.

Name

Type & Properties

--output

file

required

output

Filtering highly variable features

Name	Type & Properties	Description
--highly_variable_features_var_output --filter_with_hvg_var_output	string	In which .var slot to store a boolean array corresponding to the highly variable features.
--highly_variable_features_obs_batch_key --filter_with_hvg_obs_batch_key	string	If specified, highly-variable features are selected within each batch separately and merged. This simple process avoids the selection of batch-specific features and acts as a lightweight batch correction method. For all flavors, featues are first sorted by how many batches they are highly variable. For dispersion-based flavors ties are broken by normalized dispersion. If flavor = 'seurat_v3', ties are broken by the median (across batches) rank based on within-batch normalized variance.
--highly_variable_features_flavor --filter_with_hvg_flavor	string	Choose the flavor for identifying highly variable features. For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_features.
--highly_variable_features_n_top_features --filter_with_hvg_n_top_genes	integer	Number of highly-variable features to keep. Mandatory if filter_with_hvg_flavor is set to 'seurat_v3'.

Name

Type & Properties

--highly_variable_features_var_output

--filter_with_hvg_var_output

string

--highly_variable_features_obs_batch_key

--filter_with_hvg_obs_batch_key

string

--highly_variable_features_flavor

--filter_with_hvg_flavor

string

--highly_variable_features_n_top_features

--filter_with_hvg_n_top_genes

integer

QC metrics calculation options

Name	Type & Properties	Description
--var_qc_metrics	string multiple	Keys to select a boolean (containing only True or False) column from .var. For each cell, calculate the proportion of total values for genes which are labeled 'True', compared to the total sum of the values for all genes.
--top_n_vars	integer multiple	Number of top vars to be used to calculate cumulative proportions. If not specified, proportions are not calculated. `--top_n_vars 20,50` finds cumulative proportion to the 20th and 50th most expressed vars.
--output_obs_num_nonzero_vars	string	Name of column in .obs describing, for each observation, the number of stored values (including explicit zeroes). In other words, the name of the column that counts for each row the number of columns that contain data.
--output_obs_total_counts_vars	string	Name of the column for .obs describing, for each observation (row), the sum of the stored values in the columns.
--output_var_num_nonzero_obs	string	Name of column describing, for each feature, the number of stored values (including explicit zeroes). In other words, the name of the column that counts for each column the number of rows that contain data.
--output_var_total_counts_obs	string	Name of the column in .var describing, for each feature (column), the sum of the stored values in the rows.
--output_var_obs_mean	string	Name of the column in .obs providing the mean of the values in each row.
--output_var_pct_dropout	string	Name of the column in .obs providing for each feature the percentage of observations the feature does not appear on (i.e. is missing). Same as `--num_nonzero_obs` but percentage based.

Name

Type & Properties

--var_qc_metrics

string

multiple

--top_n_vars

integer

multiple

--output_obs_num_nonzero_vars

string

--output_obs_total_counts_vars

string

--output_var_num_nonzero_obs

string

--output_var_total_counts_obs

string

--output_var_obs_mean

string

--output_var_pct_dropout

string

RNA Scaling options

Name	Type & Properties	Description
--enable_scaling	boolean_true	Enable scaling for the RNA modality.
--scaling_output_layer	string	Output layer where the scaled log-normalized data will be stored.
--scaling_max_value	double	Clip (truncate) data to this value after scaling. If not specified, do not clip.
--scaling_zero_center	boolean_false	If set, omit zero-centering variables, which allows to handle sparse input efficiently."

Name

Type & Properties

--enable_scaling

boolean_true

--scaling_output_layer

string

--scaling_max_value

double

--scaling_zero_center

boolean_false