Overhaul strandedness detection / comparison

docs/output.md

@@ -367,7 +367,7 @@ The majority of RSeQC scripts generate output files which can be plotted and sum
 
 </details>
 
-This script predicts the "strandedness" of the protocol (i.e. unstranded, sense or antisense) that was used to prepare the sample for sequencing by assessing the orientation in which aligned reads overlay gene features in the reference genome. The strandedness of each sample has to be provided to the pipeline in the input samplesheet (see [usage docs](https://nf-co.re/rnaseq/usage#samplesheet-input)). However, this information is not always available, especially for public datasets. As a result, additional features have been incorporated into this pipeline to auto-detect whether you have provided the correct information in the samplesheet, and if this is not the case then a warning table will be placed at the top of the MultiQC report highlighting the offending samples (see image below). If required, this will allow you to correct the input samplesheet and rerun the pipeline with the accurate strand information. Note, it is important to get this information right because it can affect the final results.
+This script predicts the "strandedness" of the protocol (i.e. unstranded, sense or antisense) that was used to prepare the sample for sequencing by assessing the orientation in which aligned reads overlay gene features in the reference genome. The strandedness of each sample has to be provided to the pipeline in the input samplesheet (see [usage docs](https://nf-co.re/rnaseq/usage#samplesheet-input)). However, this information is not always available, especially for public datasets. As a result, additional features have been incorporated into this pipeline to auto-detect whether you have provided the correct information in the samplesheet, and if this is not the case then the affected libraries will be flagged in the tale under 'Strandedness Checks' elsewhere in the report. If required, this will allow you to correct the input samplesheet and rerun the pipeline with the accurate strand information. Note, it is important to get this information right because it can affect the final results.
 
 RSeQC documentation: [infer_experiment.py](http://rseqc.sourceforge.net/#infer-experiment-py)
 

docs/usage.md

@@ -18,7 +18,7 @@ You will need to create a samplesheet with information about the samples you wou
 
 ### Multiple runs of the same sample
 
-The `sample` identifiers have to be the same when you have re-sequenced the same sample more than once e.g. to increase sequencing depth. The pipeline will concatenate the raw reads before performing any downstream analysis. Below is an example for the same sample sequenced across 3 lanes. If you set the strandedness value to `auto` the pipeline will sub-sample the input FastQ files to 1 million reads, use Salmon Quant to infer the strandedness automatically and then propagate this information to the remainder of the pipeline. If the strandedness has been inferred or provided incorrectly a warning will be present at the top of the MultiQC report so please be sure to check when looking at the QC for your samples.
+The `sample` identifiers have to be the same when you have re-sequenced the same sample more than once e.g. to increase sequencing depth. The pipeline will concatenate the raw reads before performing any downstream analysis. Below is an example for the same sample sequenced across 3 lanes. 
 
 ```csv title="samplesheet.csv"
 sample,fastq_1,fastq_2,strandedness
@@ -27,6 +27,10 @@ CONTROL_REP1,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz,a
 CONTROL_REP1,AEG588A1_S1_L004_R1_001.fastq.gz,AEG588A1_S1_L004_R2_001.fastq.gz,auto
 ```
 
+### Strandedness prediction
+
+If you set the strandedness value to `auto` the pipeline will sub-sample the input FastQ files to 1 million reads, use Salmon Quant to infer the strandedness automatically and then propagate this information to the remainder of the pipeline. If the strandedness has been inferred or provided incorrectly the sample will be flagged in the 'Strandedness Checks' section of the MultiQC report, so please be sure to check when looking at the QC for your samples.
+
 ### Full samplesheet
 
 The pipeline will auto-detect whether a sample is single- or paired-end using the information provided in the samplesheet. The samplesheet can have as many columns as you desire, however, there is a strict requirement for the first 4 columns to match those defined in the table below.

subworkflows/local/utils_nfcore_rnaseq_pipeline/main.nf

@@ -574,9 +574,9 @@ def calculateStrandedness(forwardFragments, reverseFragments, unstrandedFragment
 
     return [
         inferred_strandedness: strandedness,
-        forwardFragments: forwardFragments / (totalFragments as double),
-        reverseFragments: reverseFragments / (totalFragments as double),
-        unstrandedFragments: unstrandedFragments / (totalFragments as double)
+        forwardFragments: (forwardFragments / (totalFragments as double)) * 100,
+        reverseFragments: (reverseFragments / (totalFragments as double)) * 100,
+        unstrandedFragments: (unstrandedFragments / (totalFragments as double)) * 100
     ]
 }
 

subworkflows/local/utils_nfcore_rnaseq_pipeline/tests/main.function.nf.test.snap

@@ -49,8 +49,8 @@
         "content": [
             {
                 "inferred_strandedness": "unstranded",
-                "forwardFragments": 0.5,
-                "reverseFragments": 0.5,
+                "forwardFragments": 50.0,
+                "reverseFragments": 50.0,
                 "unstrandedFragments": 0.0
             }
         ],
@@ -65,7 +65,7 @@
             {
                 "inferred_strandedness": "reverse",
                 "forwardFragments": 0.0,
-                "reverseFragments": 1.0,
+                "reverseFragments": 100.0,
                 "unstrandedFragments": 0.0
             }
         ],
@@ -219,7 +219,7 @@
         "content": [
             {
                 "inferred_strandedness": "forward",
-                "forwardFragments": 1.0,
+                "forwardFragments": 100.0,
                 "reverseFragments": 0.0,
                 "unstrandedFragments": 0.0
             }
@@ -242,9 +242,9 @@
         "content": [
             {
                 "inferred_strandedness": "reverse",
-                "forwardFragments": 0.0074992500657742505,
-                "reverseFragments": 0.8360163982823675,
-                "unstrandedFragments": 0.1564843516518582
+                "forwardFragments": 0.749925006577425,
+                "reverseFragments": 83.60163982823676,
+                "unstrandedFragments": 15.64843516518582 
             }
         ],
         "meta": {

workflows/rnaseq/nextflow.config

@@ -29,7 +29,7 @@ if (!params.skip_alignment && params.aligner == 'star_salmon') {
             publishDir = [
                 path: { "${params.outdir}/${params.aligner}" },
                 mode: params.publish_dir_mode,
-                saveAs: { filename -> filename.equals('versions.yml') || filename.endsWith('_meta_info.json') ? null : filename }
+                saveAs: { filename -> filename.equals('versions.yml') || filename.endsWith('_meta_info.json') || filename.endsWith('_format_counts.json') ? null : filename }
             ]
         }