Merge pull request #64 from christopher-mohr/prepare_release_1_1_0

Fix review comments

.github/workflows/awstest.yml

@@ -34,4 +34,4 @@ jobs:
           --job-name nf-core-epitopeprediction \
           --job-queue $AWS_JOB_QUEUE \
           --job-definition $AWS_JOB_DEFINITION \
-          --container-overrides '{"command": ["nf-core/epitopeprediction", "-r '"${GITHUB_SHA}"' -profile test --outdir s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/results-'"${GITHUB_SHA}"' -w s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/work-'"${GITHUB_SHA}"' -with-tower"], "environment": [{"name": "TOWER_ACCESS_TOKEN", "value": "'"$TOWER_ACCESS_TOKEN"'"}]}'epitopeprediction/work-'"${GITHUB_SHA}"' -with-tower"], "environment": [{"name": "TOWER_ACCESS_TOKEN", "value": "'"$TOWER_ACCESS_TOKEN"'"}]}'
+          --container-overrides '{"command": ["nf-core/epitopeprediction", "-r '"${GITHUB_SHA}"' -profile test --outdir s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/results-'"${GITHUB_SHA}"' -w s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/work-'"${GITHUB_SHA}"' -with-tower"], "environment": [{"name": "TOWER_ACCESS_TOKEN", "value": "'"$TOWER_ACCESS_TOKEN"'"}]}'

README.md

@@ -3,7 +3,7 @@
 [![GitHub Actions CI Status](https://github.com/nf-core/epitopeprediction/workflows/nf-core%20CI/badge.svg)](https://github.com/nf-core/epitopeprediction/actions)
 [![GitHub Actions Linting Status](https://github.com/nf-core/epitopeprediction/workflows/nf-core%20linting/badge.svg)](https://github.com/nf-core/epitopeprediction/actions)
 [![Nextflow](https://img.shields.io/badge/nextflow-%E2%89%A519.10.0-brightgreen.svg)](https://www.nextflow.io/)
-[![DOI](TODO)](todo)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3564666.svg)]((https://doi.org/10.5281/zenodo.3564666))
 
 [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg)](https://bioconda.github.io/)
 [![Docker](https://img.shields.io/docker/automated/nfcore/epitopeprediction.svg)](https://hub.docker.com/r/nfcore/epitopeprediction)
@@ -53,7 +53,7 @@ For further information or help, don't hesitate to get in touch on the [Slack `#
 
 ## Citation
 
-<!-- If you use  nf-core/epitopeprediction for your analysis, please cite it using the following doi: [10.5281/zenodo.XXXXXX](https://doi.org/10.5281/zenodo.XXXXXX) -->
+If you use  nf-core/epitopeprediction for your analysis, please cite it using the following doi: [10.5281/zenodo.3564666](https://doi.org/10.5281/zenodo.3564666)
 
 You can cite the `nf-core` publication as follows:
 

bin/epaa.py

@@ -717,7 +717,7 @@ def create_score_values(j, method):
 def create_affinity_values(allele, length, j, method, max_scores, allele_strings):
     if not pd.isnull(j):
         if 'syf' in method:
-            return max(0, round(((100.0 / float(max_scores[allele_strings[('%s_%s' % (str(allele), length))]]) * float(j)) / 100.0) * 100, 2))
+            return max(0, round((100.0 / float(max_scores[allele_strings[('%s_%s' % (str(allele), length))]]) * float(j)), 2))
         elif any(m in method for m in ['mhcnuggets','mhcflurry']):
             # mhcnuggets and mhcflurry return already IC50 affinity values
             return round(j, 2)

conf/test.config

@@ -4,7 +4,7 @@
  * -------------------------------------------------
  * Defines bundled input files and everything required
  * to run a fast and simple test. Use as follows:
- *   nextflow run nf-core/epitopeprediction -profile test_vcf
+ *   nextflow run nf-core/epitopeprediction -profile test,<docker/singularity>
  */
 
 params {

conf/test_full.config

@@ -12,8 +12,6 @@ params {
   config_profile_description = 'Full test dataset to check pipeline function'
 
   // Input data for full size test
-  // TODO nf-core: Specify the paths to your full test data ( on nf-core/test-datasets or directly in repositories, e.g. SRA)
-  // Input data
   input = 'https://raw.githubusercontent.com/nf-core/test-datasets/epitopeprediction/testdata/variants/variants.vcf'
   alleles = 'https://raw.githubusercontent.com/nf-core/test-datasets/epitopeprediction/testdata/alleles/alleles.txt'
 }

conf/test_mhcflurry.config

@@ -4,7 +4,7 @@
  * -------------------------------------------------
  * Defines bundled input files and everything required
  * to run a fast and simple test. Use as follows:
- *   nextflow run nf-core/epitopeprediction -profile test
+ *   nextflow run nf-core/epitopeprediction -profile test_mhcflurry,<docker/singularity>
  */
 
 params {

conf/test_mhcnuggets.config

@@ -4,7 +4,7 @@
  * -------------------------------------------------
  * Defines bundled input files and everything required
  * to run a fast and simple test. Use as follows:
- *   nextflow run nf-core/epitopeprediction -profile test
+ *   nextflow run nf-core/epitopeprediction -profile test_mhcnuggets,<docker/singularity>
  */
 
 params {

conf/test_peptides.config

@@ -4,7 +4,7 @@
  * -------------------------------------------------
  * Defines bundled input files and everything required
  * to run a fast and simple test. Use as follows:
- *   nextflow run nf-core/epitopeprediction -profile test_peptides
+ *   nextflow run nf-core/epitopeprediction -profile test_peptides,<docker/singularity>
  */
 
 params {

conf/test_peptides_h2.config

@@ -4,7 +4,7 @@
  * -------------------------------------------------
  * Defines bundled input files and everything required
  * to run a fast and simple test. Use as follows:
- *   nextflow run nf-core/epitopeprediction -profile test_peptides_h2
+ *   nextflow run nf-core/epitopeprediction -profile test_peptides_h2,<docker/singularity>
  */
 
 params {

conf/test_proteins.config

@@ -4,7 +4,7 @@
  * -------------------------------------------------
  * Defines bundled input files and everything required
  * to run a fast and simple test. Use as follows:
- *   nextflow run nf-core/epitopeprediction -profile test_proteins
+ *   nextflow run nf-core/epitopeprediction -profile test_proteins,<docker/singularity>
  */
 
 params {

conf/test_variant_tsv.config

@@ -4,7 +4,7 @@
  * -------------------------------------------------
  * Defines bundled input files and everything required
  * to run a fast and simple test. Use as follows:
- *   nextflow run nf-core/epitopeprediction -profile test_variant_tsv
+ *   nextflow run nf-core/epitopeprediction -profile test_variant_tsv,<docker/singularity>
  */
 
 params {

docs/output.md

@@ -35,16 +35,16 @@ HVYLFLSNL 9 17 3336962 ENSG00000127780 ENST00000248384 ENSP00000248384 SNP syfpe
 
 The prediction results are given as allele-specific score and affinity values per peptide. The computation of these values depends on the applied prediction method:
 
-* `Syfpeithi`:
-  * **Affinity**: Calculated as the half-max score of the corresponding matrix: `score(peptide) divided by the maximum score of the allele/length-specific matrix * 100`.
-  * **Score**: Sum of the values given by the allele-specific position-specific scoring matrix (PSSM) for the respective peptide sequence
-Peptides are considered binders if the affinity (half-max score) is higher than 50.
-* `MHCflurry`:
+* [`Syfpeithi`](http://www.syfpeithi.de) :
+  * **Affinity**: Calculated based on the score as the percentage of the maximum value of the corresponding matrix: `score(peptide) divided by the maximum score of the allele/length-specific matrix * 100`.
+  * **Score**: Sum of the values given by the allele-specific position-specific scoring matrix (PSSM) for the respective peptide sequence.
+Peptides are considered binders if the affinity is higher than 50.
+* [`MHCflurry`](https://github.com/openvax/mhcflurry):
   * **Affinity**: Predicted IC50 (threshold for binders: `<500 nmol/L`).
-  * **Score**: The provided score is calculated from the affinity and scaled to an interval of 0 to 1:  `1-log50000(aff)`. Thus, it is the log-transformed predicted binding affinity.
-* `MHCnuggets`:
+  * **Score**: The provided score is calculated from the log-transformed predicted binding affinity and scaled to an interval of 0 to 1:  `1-log50000(aff)`.
+* [`MHCnuggets`](https://github.com/KarchinLab/mhcnuggets):
   * **Affinity**: Predicted IC50 (threshold for binders: `<500 nmol/L`).
-  * **Score**: The provided score is calculated from the affinity and scaled to an interval of 0 to 1:  `1-log50000(aff)`. Thus, it is the log-transformed predicted binding affinity.
+  * **Score**: The provided score is calculated from the log-transformed predicted binding affinity and scaled to an interval of 0 to 1:  `1-log50000(aff)`.
 
 When the parameter `--fasta_output` is specified a `FASTA` file will be generated that contains the sequences of proteins that are affected by the provided genomic variants. The resulting `FASTA` file will contain the wild-type and mutated protein sequences.
 
@@ -55,7 +55,7 @@ When the parameter `--fasta_output` is specified a `FASTA` file will be generate
 
 ### Supported models
 
-When running the pipeline using the `--show_supported_models` parameter, the information about supported models for the available predictor tool versions will be written to the results folder as well.
+When running the pipeline using the `--show_supported_models` parameter, the information about supported models for the available predictor tool versions will be written to the results folder.
 
 **Output directory: `supported_models/`**
 

main.nf

@@ -20,17 +20,17 @@ def helpMessage() {
     nextflow run nf-core/epitopeprediction --input '*.vcf' -profile docker
 
     Mandatory arguments:
-      --input [file]                        Path to input data (must be surrounded with quotes)
-      --alleles [file]                      Path to the file containing the MHC alleles
+      --input [file]                        Path to input data (must be surrounded with quotes). Variants in VCF or TSV format.
+      --alleles [file]                      Path to the file containing the MHC alleles.
       -profile [str]                        Configuration profile to use. Can use multiple (comma separated)
                                             Available: conda, docker, singularity, test, awsbatch, <institute> and more
 
     Alternative inputs:
-      --peptides [file]                     Path to TSV file containing peptide sequences (minimum required: id and sequence column)
-      --proteins [file]                     Path to FASTA file containing protein sequences
+      --peptides [file]                     Path to TSV file containing peptide sequences (minimum required: id and sequence column).
+      --proteins [file]                     Path to FASTA file containing protein sequences.
 
     Main options:
-      --show_supported_models [bool]         Writes out supported models. Does not run actual prediction pipeline. Default: false.
+      --show_supported_models [bool]        Writes out supported models. Does not run actual prediction pipeline. Default: false.
       --filter_self [bool]                  Specifies that peptides should be filtered against the specified human proteome references. Default: false
       --wild_type  [bool]                   Specifies that wild-type sequences of mutated peptides should be predicted as well. Default: false
       --fasta_output [bool]                 Specifies that sequences of proteins, affected by provided variants, will be written to a FASTA file. Default: false
@@ -80,6 +80,7 @@ ch_check_alleles = Channel.empty()
 // Store input base name for later
 def input_base_name = ''
 
+// Validating parameters
 if ( !params.show_supported_models ){
     if ( params.peptides ) {
         if ( params.fasta_output ) {

nextflow.config

@@ -92,6 +92,7 @@ profiles {
   test_proteins { includeConfig 'conf/test_proteins.config' }
   test_mhcnuggets { includeConfig 'conf/test_mhcnuggets.config' }
   test_mhcflurry { includeConfig 'conf/test_mhcflurry.config' }
+  test_full { includeConfig 'conf/test_full.config' }
 }
 
 // Load igenomes.config if required