Move nanoplot to nf-core, remove references to removed tools

CITATIONS.md

@@ -30,8 +30,6 @@
 
   > Sović I, Šikić M, Wilm A, Fenlon SN, Chen S, Nagarajan N. Fast and sensitive mapping of nanopore sequencing reads with GraphMap. Nat Commun. 2016 Apr 15;7:11307. doi: 10.1038/ncomms11307. PMID: 27079541; PMCID: PMC4835549.
 
-- [Guppy](https://nanoporetech.com/nanopore-sequencing-data-analysis)
-
 - [JAFFAL](https://doi.org/10.1186/s13059-021-02588-5)
 
   > Davidson NM, Chen Y, Sadras T, Ryland GL, Blombery P, Ekert PG, Göke J, Oshlack A. JAFFAL: detecting fusion genes with long-read transcriptome sequencing. Genome Biol. 2022 Jan 6;23(1):10. doi: 10.1186/s13059-021-02588-5. PMID: 34991664; PMCID: PMC8739696.
@@ -62,10 +60,6 @@
 
   > De Coster W, D'Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics. 2018 Aug 1;34(15):2666-2669. doi: 10.1093/bioinformatics/bty149. PubMed PMID: 29547981; PubMed Central PMCID: PMC6061794.
 
-- [pycoQC](https://doi.org/10.21105/joss.01236)
-
-  > Leger A, Leonardi T, (2019). pycoQC, interactive quality control for Oxford Nanopore Sequencing. Journal of Open Source Software, 4(34), 1236, https://doi.org/10.21105/joss.01236
-
 - [qcat](https://github.com/nanoporetech/qcat)
 
 - [SAMtools](https://www.ncbi.nlm.nih.gov/pubmed/19505943/)

README.md

@@ -23,26 +23,24 @@ On release, automated continuous integration tests run the pipeline on a [full-s
 
 ## Pipeline Summary
 
-1. Basecalling and/or demultiplexing ([`Guppy`](https://nanoporetech.com/nanopore-sequencing-data-analysis), [`demux_fast5`](https://github.com/nanoporetech/ont_fast5_api#demux_fast5), or [`qcat`](https://github.com/nanoporetech/qcat); _optional_)
-2. Sequencing QC ([`pycoQC`](https://github.com/a-slide/pycoQC), [`NanoPlot`](https://github.com/wdecoster/NanoPlot))
-3. Raw read DNA cleaning ([NanoLyse](https://github.com/wdecoster/nanolyse); _optional_)
-4. Raw read QC ([`NanoPlot`](https://github.com/wdecoster/NanoPlot), [`FastQC`](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/))
-5. Alignment ([`GraphMap2`](https://github.com/lbcb-sci/graphmap2) or [`minimap2`](https://github.com/lh3/minimap2))
+1. Raw read cleaning ([NanoLyse](https://github.com/wdecoster/nanolyse); _optional_)
+2. Raw read QC ([`NanoPlot`](https://github.com/wdecoster/NanoPlot), [`FastQC`](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/))
+3. Alignment ([`GraphMap2`](https://github.com/lbcb-sci/graphmap2) or [`minimap2`](https://github.com/lh3/minimap2))
    - Both aligners are capable of performing unspliced and spliced alignment. Sensible defaults will be applied automatically based on a combination of the input data and user-specified parameters
    - Each sample can be mapped to its own reference genome if multiplexed in this way
    - Convert SAM to co-ordinate sorted BAM and obtain mapping metrics ([`samtools`](http://www.htslib.org/doc/samtools.html))
-6. Create bigWig ([`BEDTools`](https://github.com/arq5x/bedtools2/), [`bedGraphToBigWig`](http://hgdownload.soe.ucsc.edu/admin/exe/)) and bigBed ([`BEDTools`](https://github.com/arq5x/bedtools2/), [`bedToBigBed`](http://hgdownload.soe.ucsc.edu/admin/exe/)) coverage tracks for visualisation
-7. DNA specific downstream analysis:
+4. Create bigWig ([`BEDTools`](https://github.com/arq5x/bedtools2/), [`bedGraphToBigWig`](http://hgdownload.soe.ucsc.edu/admin/exe/)) and bigBed ([`BEDTools`](https://github.com/arq5x/bedtools2/), [`bedToBigBed`](http://hgdownload.soe.ucsc.edu/admin/exe/)) coverage tracks for visualisation
+5. DNA specific downstream analysis:
    - Short variant calling ([`medaka`](https://github.com/nanoporetech/medaka), [`deepvariant`](https://github.com/google/deepvariant), or [`pepper_margin_deepvariant`](https://github.com/kishwarshafin/pepper))
    - Structural variant calling ([`sniffles`](https://github.com/fritzsedlazeck/Sniffles) or [`cutesv`](https://github.com/tjiangHIT/cuteSV))
-8. RNA specific downstream analysis:
+6. RNA specific downstream analysis:
    - Transcript reconstruction and quantification ([`bambu`](https://bioconductor.org/packages/release/bioc/html/bambu.html) or [`StringTie2`](https://ccb.jhu.edu/software/stringtie/))
      - bambu performs both transcript reconstruction and quantification
      - When StringTie2 is chosen, each sample can be processed individually and combined. After which, [`featureCounts`](http://bioinf.wehi.edu.au/featureCounts/) will be used for both gene and transcript quantification.
    - Differential expression analysis ([`DESeq2`](https://bioconductor.org/packages/release/bioc/html/DESeq2.html) and/or [`DEXSeq`](https://bioconductor.org/packages/release/bioc/html/DEXSeq.html))
    - RNA modification detection ([`xpore`](https://github.com/GoekeLab/xpore) and/or [`m6anet`](https://github.com/GoekeLab/m6anet))
    - RNA fusion detection ([`JAFFAL`](https://github.com/Oshlack/JAFFA))
-9. Present QC for raw read and alignment results ([`MultiQC`](https://multiqc.info/docs/))
+7. Present QC for raw read and alignment results ([`MultiQC`](https://multiqc.info/docs/))
 
 ### Functionality Overview
 
@@ -81,9 +79,6 @@ The nf-core/nanoseq pipeline comes with documentation about the pipeline [usage]
 nextflow run nf-core/nanoseq \
     --input samplesheet.csv \
     --protocol DNA \
-    --input_path ./fast5/ \
-    --flowcell FLO-MIN106 \
-    --kit SQK-LSK109 \
     --barcode_kit SQK-PBK004 \
     -profile <docker/singularity/podman/institute>
 ```

docs/usage.md

@@ -19,42 +19,7 @@ You will need to create a file with information about the samples in your experi
 
 ### Skip demultiplexing
 
-As shown in the examples below, the accepted format of the file is slightly different if you would like to run the pipeline with or without demultiplexing.
-
-#### With demultiplexing
-
-##### Example `samplesheet.csv` for barcoded fast5 inputs
-
-```bash
-group,replicate,barcode,input_file,fasta,gtf
-WT_MOUSE,1,1,,mm10,
-WT_HUMAN,1,2,,hg19,
-WT_POMBE,1,3,,/path/to/local/genome.fa,
-WT_DENOVO,1,4,,,/path/to/local/transcriptome.fa
-WT_LOCAL,2,5,,/path/to/local/genome.fa,/path/to/local/transcriptome.gtf
-WT_UNKNOWN,3,6,,,
-```
-
-#### With no demultiplexing
-
-##### Example `samplesheet.csv` for non-barcoded fast5 inputs
-
-```bash
-group,replicate,barcode,input_file,fasta,gtf
-SAMPLE,1,1,/path/to/local/genome.fa,,
-```
-
-> Only a single sample can be specified if you would like to skip demultiplexing
-
-##### Example command for non-barcoded fast5 inputs
-
-```bash
-nextflow run nf-core/nanoseq \
-    --input samplesheet.csv \
-    --protocol cDNA \
-    --skip_demultiplexing \
-    -profile <docker/singularity/institute>
-```
+As shown in the examples below, the accepted samplesheet format is different depending on if you would like to run the pipeline with or without demultiplexing.
 
 #### With demultiplexing
 

nextflow_schema.json

@@ -10,10 +10,7 @@
             "type": "object",
             "fa_icon": "fas fa-terminal",
             "description": "Define where the pipeline should find input data and save output data.",
-            "required": [
-                "input",
-                "protocol"
-            ],
+            "required": ["input", "protocol"],
             "properties": {
                 "input": {
                     "type": "string",

subworkflows/local/qcfastq_nanoplot_fastqc.nf

@@ -2,7 +2,7 @@
  * FastQ QC with NanoPlot and fastqc
  */
 
-include { NANOPLOT     } from '../../modules/nf-core/nanoplot/main' 
+include { NANOPLOT     } from '../../modules/nf-core/nanoplot/main'
 include { FASTQC       } from '../../modules/nf-core/fastqc/main'
 
 workflow QCFASTQ_NANOPLOT_FASTQC {