Update docs

Author: pinin4fjords

docs/usage.md

@@ -128,7 +128,7 @@ The `--aligner hisat2` option is not currently supported using ARM architecture
 
 By default, the pipeline uses [STAR](https://github.com/alexdobin/STAR) (i.e. `--aligner star_salmon`) to map the raw FastQ reads to the reference genome, project the alignments onto the transcriptome and to perform the downstream BAM-level quantification with [Salmon](https://salmon.readthedocs.io/en/latest/salmon.html). STAR is fast but requires a lot of memory to run, typically around 38GB for the Human GRCh37 reference genome. Since the [RSEM](https://github.com/deweylab/RSEM) (i.e. `--aligner star_rsem`) workflow in the pipeline also uses STAR you should use the [HISAT2](https://ccb.jhu.edu/software/hisat2/index.shtml) aligner (i.e. `--aligner hisat2`) if you have memory limitations.
 
-You also have the option to pseudoalign and quantify your data directly with [Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) or [Kallisto](https://pachterlab.github.io/kallisto/) by specifying `salmon` or `kallisto` to the `--pseudo_aligner` parameter. The selected pseudoaligner will then be run in addition to the standard alignment workflow defined by `--aligner`, mainly because it allows you to obtain QC metrics with respect to the genomic alignments. However, you can provide the `--skip_alignment` parameter if you would like to run Salmon or Kallisto in isolation. By default, the pipeline will use the genome fasta and gtf file to generate the transcripts fasta file, and then to build the Salmon index. You can override these parameters using the `--transcript_fasta` and `--salmon_index` parameters, respectively.
+You also have the option to pseudoalign and quantify your data directly with [Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) or [Kallisto](https://pachterlab.github.io/kallisto/) by specifying `salmon` or `kallisto` to the `--pseudo_aligner` parameter. The selected pseudoaligner will then be run in addition to the standard alignment workflow defined by `--aligner`, mainly because it allows you to obtain QC metrics with respect to the genomic alignments. However, you can provide the `--skip_alignment` parameter if you would like to run Salmon or Kallisto in isolation. By default, the pipeline will use the genome fasta and gtf file to generate the transcripts fasta file, and then to build the Salmon index. You can override these parameters using the `--transcript_fasta` and `--salmon_index` parameters, respectively. By default, even `--skip_alignment set` Salmon will still use the genomic FASTA file, providing the sequences as 'decoys' (see [Salmon documentation](https://salmon.readthedocs.io/en/latest/salmon.html#preparing-transcriptome-indices-mapping-based-mode)), and this is the recommended mode of operation in this situation. However, if you do not supply a FASTA file, Salmon will run without those decoys, using only transcript sequences in the index.
 
 The library preparation protocol (library type) used by Salmon quantification is inferred by the pipeline based on the information provided in the samplesheet, however, you can override it using the `--salmon_quant_libtype` parameter. You can find the available options in the [Salmon documentation](https://salmon.readthedocs.io/en/latest/library_type.html). Similarly, strandedness is taken from the sample sheet or calculated automatically, and passed to Kallisto on a per-library basis, but you can apply a global override by setting the Kallisto strandedness parameters in `--extra_kallisto_quant_args` like `--extra_kallisto_quant_args '--fr-stranded'` see the [Kallisto documentation](https://pachterlab.github.io/kallisto/manual).
 
@@ -209,7 +209,7 @@ When supplying reference files as discussed below, it is important to be consist
 
 ### Explicit reference file specification (recommended)
 
-The minimum reference genome requirements for this pipeline are a FASTA and GTF file, all other files required to run the pipeline can be generated from these files. For example, the latest reference files for human can be derived from Ensembl like:
+The minimum reference genome requirements for this pipeline are a FASTA file (genome and/ or trnascriptome) and GTF file, all other files required to run the pipeline can be generated from these files. For example, the latest reference files for human can be derived from Ensembl like:
 
 ```
 latest_release=$(curl -s 'http://rest.ensembl.org/info/software?content-type=application/json' | grep -o '"release":[0-9]*' | cut -d: -f2)
@@ -227,6 +227,7 @@ Notes:
 - If `--gene_bed` is not provided then it will be generated from the GTF file.
 - If `--additional_fasta` is provided then the features in this file (e.g. ERCC spike-ins) will be automatically concatenated onto both the reference FASTA file as well as the GTF annotation before building the appropriate indices.
 - When using `--aligner star_rsem`, both the STAR and RSEM indices should be present in the path specified by `--rsem_index` (see [#568](https://github.com/nf-core/rnaseq/issues/568)).
+- If the `--skip_alignment` option is used along with `--transcript_fasta`, the pipeline can technically run without providing the genomic FASTA (`--fasta`). However, this approach is **not recommended**, as any dynamically generated Salmon index will lack decoys. To ensure optimal indexing with decoys, it is **highly recommended** to include the genomic FASTA (`--fasta`) whenever possible—unless a pre-existing decoy-aware Salmon index is supplied. For more details on the benefits of decoy-aware indexing, refer to the [Salmon documentation](https://salmon.readthedocs.io/en/latest/salmon.html#preparing-transcriptome-indices-mapping-based-mode).
 
 #### Reference genome
 
@@ -304,7 +305,7 @@ Notes:
 
 ### GTF filtering
 
-By default, the input GTF file will be filtered to ensure that sequence names correspond to those in the genome fasta file, and to remove rows with empty transcript identifiers. Filtering can be bypassed completely where you are confident it is not necessary, using the `--skip_gtf_filter` parameter. If you just want to skip the 'transcript_id' checking component of the GTF filtering script used in the pipeline this can be disabled specifically using the `--skip_gtf_transcript_filter` parameter.
+By default, the input GTF file will be filtered to ensure that sequence names correspond to those in the genome fasta file (where supplied), and to remove rows with empty transcript identifiers. Filtering can be bypassed completely where you are confident it is not necessary, using the `--skip_gtf_filter` parameter. If you just want to skip the 'transcript_id' checking component of the GTF filtering script used in the pipeline this can be disabled specifically using the `--skip_gtf_transcript_filter` parameter.
 
 ## Contamination screening options
 
@@ -332,6 +333,21 @@ nextflow run \
     -profile docker
 ```
 
+You can also run without a genomic FASTA file, provided you skip the alignment step and provide a transcriptome FASTA directly:
+
+```bash
+nextflow run \
+    nf-core/rnaseq \
+    --input <SAMPLESHEET> \
+    --outdir <OUTDIR> \
+    --gtf <GTF> \
+    --transcript_fasta <TRANSCRIPTOME FASTA> \
+    --skip_alignment \
+    -profile docker
+```
+
+This is not usually recommended unless you also supply a previously generated decoy-aware Salmon transcriptome.
+
 > **NB:** Loading iGenomes configuration remains the default for reasons of consistency with other workflows, but should be disabled when not using iGenomes, applying the recommended usage above.
 
 This will launch the pipeline with the `docker` configuration profile. See below for more information about profiles.