Prot multisample

Processing unimodal multi-sample ADT data.

Info

ID: prot_multisample
Namespace: workflows/prot

Example commands

You can run the pipeline using nextflow run.

View help

You can use --help as a parameter to get an overview of the possible parameters.

nextflow run openpipelines-bio/openpipeline \
  -r 1.0.1 -latest \
  -main-script target/nextflow/workflows/prot/prot_multisample/main.nf \
  --help

Run command

Example of params.yaml 
# Inputs
id: # please fill in - example: "concatenated"
input: # please fill in - example: "dataset.h5mu"
# layer: "foo"

# Outputs
# output: "$id.$key.output.h5mu"

# QC metrics calculation options
# var_qc_metrics: ["ercc", "highly_variable"]
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"

# Nextflow input-output arguments
publish_dir: # please fill in - example: "output/"
# param_list: "my_params.yaml"
nextflow run openpipelines-bio/openpipeline \
  -r 1.0.1 -latest \
  -profile docker \
  -main-script target/nextflow/workflows/prot/prot_multisample/main.nf \
  -params-file params.yaml
Note

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

Argument groups

Inputs

Name Description Attributes
--id ID of the concatenated file string, required, example: "concatenated"
--input Path to the samples. file, required, example: "dataset.h5mu"
--layer Input layer to use. If not specified, .X is used. string

Outputs

Name Description Attributes
--output Destination path to the output. file, required, example: "output.h5mu"

QC metrics calculation options

Name Description Attributes
--var_qc_metrics 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. Defaults to the value from –var_name_mitochondrial_genes. List of string, example: "ercc,highly_variable", multiple_sep: ";"
--top_n_vars 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. List of integer, default: 50, 100, 200, 500, multiple_sep: ";"
--output_obs_num_nonzero_vars 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. string, default: "num_nonzero_vars"
--output_obs_total_counts_vars Name of the column for .obs describing, for each observation (row), the sum of the stored values in the columns. string, default: "total_counts"
--output_var_num_nonzero_obs 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. string, default: "num_nonzero_obs"
--output_var_total_counts_obs Name of the column in .var describing, for each feature (column), the sum of the stored values in the rows. string, default: "total_counts"
--output_var_obs_mean Name of the column in .obs providing the mean of the values in each row. string, default: "obs_mean"
--output_var_pct_dropout 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 --output_var_num_nonzero_obs but percentage based. string, default: "pct_dropout"

Authors

  • Dries Schaumont (author)

Visualisation

flowchart TB
    v0(Channel.fromList)
    v18(clr)
    v129(Output)
    subgraph group_prot_qc [prot_qc]
        v30(filter)
        v48(grep_annotation_column)
        v61(mix)
        v70(calculate_qc_metrics)
        v90(publish)
    end
    v0-->v18
    v18-->v30
    v30-->v48
    v48-->v61
    v30-->v61
    v61-->v70
    v70-->v90
    v90-->v129
    style group_prot_qc fill:#F0F0F0,stroke:#969696;
    style v0 fill:#e3dcea,stroke:#7a4baa;
    style v18 fill:#e3dcea,stroke:#7a4baa;
    style v30 fill:#e3dcea,stroke:#7a4baa;
    style v48 fill:#e3dcea,stroke:#7a4baa;
    style v61 fill:#e3dcea,stroke:#7a4baa;
    style v70 fill:#e3dcea,stroke:#7a4baa;
    style v90 fill:#e3dcea,stroke:#7a4baa;
    style v129 fill:#e3dcea,stroke:#7a4baa;