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> **NB:** Dependency has been **updated** if both old and new version information is present.
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### Enhancements & fixes
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-[[#1011](https://github.com/nf-core/rnaseq/issues/1011)] - FastQ files from UMI-tools not being passed to fastp
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-[[#1018](https://github.com/nf-core/rnaseq/issues/1018)] - Ability to skip both alignment and pseudo-alignment to only run pre-processing QC steps.
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-[[#1018](https://github.com/nf-core/rnaseq/issues/1018)] - Ability to skip both alignment and pseudoalignment to only run pre-processing QC steps.
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-[PR #1016](https://github.com/nf-core/rnaseq/pull/1016) - Updated pipeline template to [nf-core/tools 2.8](https://github.com/nf-core/tools/releases/tag/2.8)
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-[PR #1025](https://github.com/nf-core/fetchngs/pull/1025) - Add `public_aws_ecr.config` to source mulled containers when using `public.ecr.aws` Docker Biocontainer registry
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-[PR #1038](https://github.com/nf-core/rnaseq/pull/1038) - Updated error log for count values when supplying `--additional_fasta`
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- Added options to skip several steps
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- Skip trimming using `--skipTrimming`
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- Skip BiotypeQC using `--skipBiotypeQC`
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- Skip Alignment using `--skipAlignment` to only use pseudo-alignment using Salmon
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- Skip Alignment using `--skipAlignment` to only use pseudoalignment using Salmon
15.Pseudo-alignment and quantification ([`Salmon`](https://combine-lab.github.io/salmon/) or ['Kallisto'](https://pachterlab.github.io/kallisto/); _optional_)
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15.Pseudoalignment and quantification ([`Salmon`](https://combine-lab.github.io/salmon/) or ['Kallisto'](https://pachterlab.github.io/kallisto/); _optional_)
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16. Present QC for raw read, alignment, gene biotype, sample similarity, and strand-specificity checks ([`MultiQC`](http://multiqc.info/), [`R`](https://www.r-project.org/))
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[Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) from [Ocean Genomics](https://oceangenomics.com/) and [Kallisto](https://pachterlab.github.io/kallisto/), from the Pachter Lab, are provided as options for pseudo-alignment. Both allow quantification of reads against an index generated from a reference set of target transcripts. By default, the transcriptome-level BAM files generated by STAR are provided to Salmon for downstream quantification, and Kallisto is not an option here (it does not allow BAM file input). But you can provide FASTQ files directly as input to either Salmon or Kallisto in order to pseudo-align and quantify your data by providing the `--pseudo_aligner (salmon or kallisto)` parameter. See the [Salmon](#salmon) and (Kallisto)[#kallisto] results sections for more details.
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[Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) from [Ocean Genomics](https://oceangenomics.com/) and [Kallisto](https://pachterlab.github.io/kallisto/), from the Pachter Lab, are provided as options for pseudoalignment. Both allow quantification of reads against an index generated from a reference set of target transcripts. By default, the transcriptome-level BAM files generated by STAR are provided to Salmon for downstream quantification, and Kallisto is not an option here (it does not allow BAM file input). But you can provide FASTQ files directly as input to either Salmon or Kallisto in order to pseudoalign and quantify your data by providing the `--pseudo_aligner salmon` or `--pseudo_aligner kallisto` parameter. See the [Salmon](#pseudoalignment) and [Kallisto](#pseudoalignment) results sections for more details.
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### STAR via RSEM
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Results generated by MultiQC collate pipeline QC from supported tools i.e. FastQC, Cutadapt, SortMeRNA, STAR, RSEM, HISAT2, Salmon, SAMtools, Picard, RSeQC, Qualimap, Preseq and featureCounts. Additionally, various custom content has been added to the report to assess the output of dupRadar, DESeq2 and featureCounts biotypes, and to highlight samples failing a mimimum mapping threshold or those that failed to match the strand-specificity provided in the input samplesheet. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see <http://multiqc.info>.
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## Pseudo-alignment and quantification
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## Pseudoalignment and quantification
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### Pseudo-alignment
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### Pseudoalignment
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The principal output files are the same between Salmon and Kallsto:
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-`abundance.h5`: a HDF5 binary file containing run info, abundance esimates, bootstrap estimates, and transcript length information length. This file can be read in by [sleuth](https://pachterlab.github.io/sleuth/about).
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-`abundance.tsv`: a plaintext file of the abundance estimates. It does not contains bootstrap estimates.
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-`run_info.json`: a json file containing information about the run.
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-`<SAMPLE>.log.txt`: standard output from the Kallisto process per sample.
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-`kallisto_quant.log`: standard output from the Kallisto process per sample.
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</details>
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As described in the [STAR and Salmon](#star-and-salmon) section, you can choose to pseudo-align and quantify your data with [Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) or [Kallisto](https://pachterlab.github.io/kallisto/) by providing the `--pseudo_aligner` parameter. By default, Salmon is 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. If Salmon or Kallisto are run in isolation, the outputs mentioned above will be found in a folder named `salmon` or `kallisto`. If Salmon is run alongside STAR, the folder will be named `star_salmon`.
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As described in the [STAR and Salmon](#star-and-salmon) section, you can choose to pseudoalign and quantify your data with [Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) or [Kallisto](https://pachterlab.github.io/kallisto/) by providing the `--pseudo_aligner` parameter. By default, Salmon is 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. If Salmon or Kallisto are run in isolation, the outputs mentioned above will be found in a folder named `salmon` or `kallisto`. If Salmon is run alongside STAR, the folder will be named `star_salmon`.
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Transcripts with large inferential uncertainty won't be assigned the exact number of reads reproducibly, every time Salmon is run. Read more about this on the [nf-core/rnaseq](https://github.com/nf-core/rnaseq/issues/585) and [salmon](https://github.com/COMBINE-lab/salmon/issues/613) Github repos.
Copy file name to clipboardexpand all lines: docs/usage.md
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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.
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You also have the option to pseudo-align 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.
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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.
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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 `kallisto_quant_strandednes` see the [Kallisto documentation](https://pachterlab.github.io/kallisto/manual).
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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 `--kallisto_quant_strandedness` see the [Kallisto documentation](https://pachterlab.github.io/kallisto/manual).
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When running Salmon in mapping-based mode via `--pseudo_aligner salmon` the entire genome of the organism is used by default for the decoy-aware transcriptome when creating the indices (see second bulleted option in [Salmon documentation](https://salmon.readthedocs.io/en/latest/salmon.html#preparing-transcriptome-indices-mapping-based-mode)).
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Two additional parameters `--extra_star_align_args` and `--extra_salmon_quant_args` were added in v3.10 of the pipeline that allow you to append any custom parameters to the STAR align and Salmon quant commands, respectively. Note, the `--seqBias` and `--gcBias` are not provided to Salmon quant by default so you can provide these via `--extra_salmon_quant_args '--seqBias --gcBias'` if required. You can now also supply additional arguments to Kallisto via `--extra_kallisto_quant_args`.
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> **NB:** You can use `--skip_alignment --skip_pseudo_alignment` if you only want to run the pre-processing QC steps in the pipeline like FastQ, trimming etc. This will skip alignment, pseudo-alignment and any post-alignment processing steps.
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> **NB:** You can use `--skip_alignment --skip_pseudo_alignment` if you only want to run the pre-processing QC steps in the pipeline like FastQ, trimming etc. This will skip alignment, pseudoalignment and any post-alignment processing steps.
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## Quantification options
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The current options align with STAR and quantify using either Salmon (`--aligner star_salmon`) / RSEM (`--aligner star_rsem`). You also have the option to pseudo-align and quantify your data with Salmon or Kallisto by providing the `--pseudo_aligner salmon` or `--pseudo_aligner kallisto` parameter, respectively.
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The current options align with STAR and quantify using either Salmon (`--aligner star_salmon`) / RSEM (`--aligner star_rsem`). You also have the option to pseudoalign and quantify your data with Salmon or Kallisto by providing the `--pseudo_aligner salmon` or `--pseudo_aligner kallisto` parameter, respectively.
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Since v3.0 of the pipeline, featureCounts is no longer used to perform gene/transcript quantification, however it is still used to generate QC metrics based on [biotype](http://www.ensembl.org/info/genome/genebuild/biotypes.html) information available within GFF/GTF genome annotation files. This decision was made primarily because of the limitations of featureCounts to appropriately quantify gene expression data. Please see [Zhao et al., 2015](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141910#pone-0141910-t001) and [Soneson et al., 2015](https://f1000research.com/articles/4-1521/v1).
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