docs

docs/usage.md

@@ -42,13 +42,13 @@ nextflow run nf-core/airrflow \
 A typical command to run the pipeline from **single cell raw fastq files** is:
 
 ```bash
-nextflow run nf-core/airrflow -r dev \
+nextflow run nf-core/airrflow \
 -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> \
 --mode fastq \
 --input input_samplesheet.tsv \
 --library_generation_method sc_10x_genomics \
 --reference_10x reference/refdata-cellranger-vdj-GRCh38-alts-ensembl-5.0.0.tar.gz \
---outdir ./results
+--outdir results
 ```
 
 A typical command for running the pipeline departing from **single-cell AIRR rearrangement tables or assembled bulk sequencing fasta** data is:
@@ -123,7 +123,7 @@ If you wish to share such profile (such as upload as supplementary material for
 
 ## Input samplesheet
 
-### Fastq input samplesheet (bulk sequencing)
+### Fastq input samplesheet (bulk AIRR and bulk/sc RNA sequencing)
 
 The required input file for processing raw BCR or TCR bulk targeted sequencing data is a sample sheet in TSV format (tab separated). The columns `sample_id`, `filename_R1`, `filename_R2`, `subject_id`, `species`, `tissue`, `pcr_target_locus`, `single_cell`, `sex`, `age` and `biomaterial_provider` are required. An example samplesheet is:
 
@@ -511,6 +511,50 @@ nextflow run nf-core/airrflow -r dev \
 - The 10xGenomics reference can be downloaded from the [download page](https://www.10xgenomics.com/support/software/cell-ranger/downloads)
 - To generate a V(D)J segment fasta file as reference from IMGT one can follow the [cellranger docs](https://support.10xgenomics.com/single-cell-vdj/software/pipelines/latest/advanced/references#imgt).
 
+
+## Supported unselected RNA-seq based methods
+
+nf-core/airrflow supports unselected bulk or single-cell RNA-seq fastq files as input. [TRUST4](https://github.com/liulab-dfci/TRUST4) is used to extract TCR/BCR sequences from these files. The resulting AIRR tables are then fed into airrflow's Immcantation based workflow. <br>
+To use unselected RNA-seq based input, specify `--library_generation_method trust4`.
+
+### Bulk RNA-seq
+
+A typical command to run the pipeline from **bulk RNA-seq fastq files** is:
+
+```bash
+nextflow run nf-core/airrfow \
+-profile <docker/singularity/podman/shifter/charliecloud/conda/institute> \
+--mode fastq \
+--input input_samplesheet.tsv \
+--library_generation_method trust4 \
+--coord_fasta reference/IMGT+C.fa \
+--outdir results
+```
+
+### Single-cell RNA-seq
+
+A typical command to run the pipeline from **single-cell RNA-seq fastq files** is:
+
+```bash
+nextflow run nf-core/airrfow \
+-profile <docker/singularity/podman/shifter/charliecloud/conda/institute> \
+--mode fastq \
+--input input_samplesheet.tsv \
+--library_generation_method trust4 \
+--umi_position R1 \
+--read_format bc:0:15,um:16:27
+--coord_fasta reference/IMGT+C.fa \
+--outdir results
+```
+
+* If UMI's are present, the read containing them must be specified using the `--umi_position` parameter.
+* The `--read_format` parameter can be used to specify the Barcode and UMI position within the reads (see TRUST4 [docs](https://github.com/liulab-dfci/TRUST4?tab=readme-ov-file#10x-genomics-data-and-barcode-based-single-cell-data))
+
+#### Reference file
+
+TRUST4 requires a reference. This can provided using the `--coord_fasta` parameter.
+The reference fasta can be downloaded from IMGT and created using [TRUST4](https://github.com/liulab-dfci/TRUST4?tab=readme-ov-file#build-custom-vjc-gene-database-files-for--f-and---ref)
+
 ## Core Nextflow arguments
 
 :::note

nextflow_schema.json

@@ -487,9 +487,9 @@
             "fa_icon": "fab fa-pagelines"
         },
         "rnaseq_based_analysis_options": {
-            "title": "RNA seq based analysis options",
+            "title": "Unselected RNA-seq based analysis options",
             "type": "object",
-            "description": "Options specific for raw RNA seq input.",
+            "description": "Options specific for raw unselected RNA-seq input.",
             "default": "",
             "properties": {
                 "barcode_read": {