Merge remote-tracking branch 'origin/staging'

.github/workflows/tests.yml

@@ -17,6 +17,13 @@ jobs:
         python-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
 
     steps:
+      - name: Maximize build space
+        uses: AdityaGarg8/remove-unwanted-software@v2
+        with:
+          remove-android: 'true'
+          remove-dotnet: 'true'
+          remove-haskell: 'true'
+          remove-codeql: 'true'
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v2
@@ -35,6 +42,8 @@ jobs:
         run: |
           pip install polars==0.16.18
           pip install pypandoc==1.7.2
+          pip install git+https://github.com/griffithlab/bigmhc.git#egg=bigmhc
+          pip install git+https://github.com/griffithlab/deepimmuno.git#egg=deepimmuno
           pip install -e .
           mhcflurry-downloads fetch
       - name: List installed packages

docs/conf.py

@@ -68,9 +68,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '4.0'
+version = '4.1'
 # The full version, including alpha/beta/rc tags.
-release = '4.0.8'
+release = '4.1.0'
 
 
 # The language for content autogenerated by Sphinx. Refer to documentation

docs/index.rst

@@ -54,79 +54,29 @@ Contents
 New in Release |release|
 ------------------------
 
-This is a bugfix release. It fixes the following problem(s):
-
-- pVACbind was not parsing the individual El prediction algorithm scores correctly
-  resulting in them being missing from the all epitopes file.
-- This release fixes some display issues in pVACview. It also implements a
-  Docker file and bash script for deploying pVACview to GCP.
-
-New in Version |version|
-------------------------
-
-This version adds the following features, outlined below. Please note that
-pVACtools 4.0 is not backwards-compatible and certain changes will break old
-workflows.
-
-Breaking Changes
-________________
-
-- pVACseq|pVACfuse|pVACbind report files have been reformatted to add some
-  additional information and, in the case of pVACfuse and pVACbind, remove
-  columns where all values were ``NA``. Existing output files will no longer
-  work with the standalone commands as well as pVACview.
-- The format of the Mutation Position column has been updated to no longer use
-  0 and n+1 to denote mutations starting before or ending after the epitope.
-  This column now only shows the actually mutated positions.
-
-New Features
-____________
-
-- We now support MHCflurry and NetMHCpanEL elution algorithms.
-- Users are now able to select specific amino acids that would be problematic for
-  vaccine manufacturing and have the pipelines mark epitopes with such amino
-  acids.
-- When running the reference proteome similarity step, users are now able to
-  specify a peptide fasta to search against instead of using BLAST. Any exact
-  matches against the entries in the peptide fasta are counted as a hit.
-- The aggregate report now takes into account many command line thresholds
-  when tiering candidates. We also refined the way we determine the Best
-  Peptide to take into account the biotype and TSL of the transcripts coding
-  for the peptide, and whether or not the candidate has any problematic
-  positions or fails the anchor criteria. Please see the :ref:`output file
-  section <pvacseq_best_peptide>` of the documentation for more details.
-- pVACview has been updated with a host of new features
-
-  - Users may adjust a wider variety of thresholds for retiering.
-  - Users are now able to reset the tiering thresholds to the ones originally
-    used when running pVACview.
-  - Transcripts resulting in the same set of epitope candidates are now
-    grouped together to make it easier to identify unique candidates.
-  - Elution data is displayed in the epitope details section of pVACview.
-  - Reference match details are displayed in the transcript set details
-    section of pVACview.
-
-- pVACfuse now supports output files from Arriba for fusion peptide
-  predictions.
-- Users may provide an optional STAR-fusion output file to their pVACfuse run
-  in order to extract expression and read support data for their candidates.
-  These will be used for filtering, as well as for tiering in the aggregate
-  report. Please see the :ref:`output file section <pvacfuse_output_files>` of the documention for
-  more details.
-- When running the ``pvacseq generate_protein_fasta`` command, users are now
-  able to specify an aggregated report as the ``--input-tsv``. When using such
-  a TSV, they can also use the ``--aggregate-report-evaluation`` to specify
-  Evaluation statuses to include in the protein fasta. This is useful when creating
-  a peptide fasta for vaccine ordering after using pVACview
-  to select vaccine candidates and exporting the results to a new TSV.
-
-Minor Changes
-_____________
-
-- The reference proteome step is now run on the aggregated report instead of
-  the filtered report.
-- A new parameter ``--aggregate-inclusion-binding-threshold`` controls which
-  epitope candidates are included in the aggregate report.
+This is a minor feature release. It adds the following features:
+
+- This release adds support for two new prediction algorithms: BigMHC and
+  DeepImmuno (`#1063 <https://github.com/griffithlab/pVACtools/pull/1063>`_).
+  BigMHC includes predictions for elution (BigMHC_EL) and
+  immunogenicity (BigMHC_IM). DeepImmuno is a prediction algorithms for
+  immunogenicty.
+- This release includes several updates to pVACview (`#1012
+  <https://github.com/griffithlab/pVACtools/pull/1012>`_):
+
+  - The tab containing the anchor heatmaps for each well-binding peptide of a
+    variant has been moved to the "Transcript and Peptide Set Data" panel.
+  - The anchor heatmap tab now also contains a table of all the per-length and
+    per-allele anchor weights for each position in a peptide.
+  - The pVACtools version is now displayed at the bottom of the sidebar.
+  - A new panel has been added to show the tiering parameters currently
+    applied.
+  - Where there are multiple transcript sets for a variant, the one containing
+    the best peptide is now selected by default.
+
+- This release adds a new command ``pvactools download_wdls`` (`#1055
+  <https://github.com/griffithlab/pVACtools/pull/1055>`_). This command
+  can be used to download WDL workflow files for pVACseq and pVACfuse.
 
 Past release notes can be found on our :ref:`releases` page.
 

docs/install.rst

@@ -118,8 +118,7 @@ install it manually by running:
 
 .. note::
 
-   The ``mhcflurry`` package needs to be installed in the same python 3 conda
-   environment as the ``pvactools`` package.
+   The ``mhcflurry`` package needs to be installed in the same Python 3 environment as the ``pvactools`` package.
 
 Next, you will need to download the download the MHCflurry datasets and trained models:
 
@@ -165,7 +164,7 @@ install it manually by running:
 
 .. note::
 
-   The ``mhcnuggets`` package needs to be installed in the same python 3 conda
+   The ``mhcnuggets`` package needs to be installed in the same Python 3
    environment as the ``pvactools`` package.
 
 You can check that the ``mhcnuggets`` package was installed successfully by running:
@@ -185,6 +184,54 @@ tensorflow manually to version 1.5.0 should solve this problem:
 
    pip install tensorflow==1.5.0
 
+Installing BigMHC
+-----------------
+
+If you wish to run the BigMHC_EL or BigMHC_IM prediction algorithms, you will need to
+install BigMHC on your system. This package not a direct dependency of
+the the ``pvactools`` packages and needs to be installed manually by running:
+
+.. code-block:: none
+
+   pip install git+https://github.com/griffithlab/bigmhc.git#egg=bigmhc
+
+.. note::
+
+   BigMHC needs to be installed in the same python 3
+   environment as the ``pvactools`` package.
+
+You can check that BigMHC was installed successfully by running:
+
+.. code-block:: none
+
+   pip show bigmhc
+
+This should show information about the BigMHC installation.
+
+Installing DeepImmuno
+---------------------
+
+If you wish to run the DeepImmuno prediction algorithm, you will need to
+install DeepImmuno on your system. This package not a direct dependency of
+the the ``pvactools`` packages and needs to be installed manually by running:
+
+.. code-block:: none
+
+   pip install git+https://github.com/griffithlab/deepimmuno.git#egg=deepimmuno
+
+.. note::
+
+   DeepImmuno needs to be installed in the same python 3
+   environment as the ``pvactools`` package.
+
+You can check that DeepImmuno was installed successfully by running:
+
+.. code-block:: none
+
+   pip show deepimmuno
+
+This should show information about the DeepImmuno installation.
+
 .. _blast:
 
 Installing BLAST

docs/pvacbind/features.rst

@@ -73,6 +73,7 @@ MHC Class I Elution Prediction Algorithm Version Supports Percentile Rank
 NetMHCpanEL                              4.1     yes
 MHCflurryEL                                      | Processing Score: no;
                                                  | Presentation Score: yes
+BigMHC_EL                                        no
 ======================================== ======= ========================
 
 ========================================= ======= ========================
@@ -81,6 +82,13 @@ MHC Class II Elution Prediction Algorithm Version Supports Percentile Rank
 NetMHCIIpanEL                             4.1     yes
 ========================================= ======= ========================
 
+=============================================== ======= ========================
+MHC Class I Immunogenicity Prediction Algorithm Version Supports Percentile Rank
+=============================================== ======= ========================
+BigMHC_IM                                               no
+DeepImmuno                                              no
+=============================================== ======= ========================
+
 **Comprehensive filtering**
 
 Automatic filtering on the binding affinity ic50 (nm) value narrows down the results to only include

docs/pvacbind/output_files.rst

@@ -74,8 +74,15 @@ _______________________________________________
 - MHCflurryEL
 - NetMHCpanEL
 - NetMHCIIpanEL
+- BigMHC_EL
 
-Please note that when running pVACfuse with only elution algorithms, no
+Prediction Algorithms Supporting Immunogenicity Scores
+______________________________________________________
+
+- BigMHC_IM
+- DeepImmuno
+
+Please note that when running pVACfuse with only elution or immungenicity algorithms, no
 aggregate report is created.
 
 .. _pvacbind_all_ep_and_filtered:

docs/pvacfuse/features.rst

@@ -77,6 +77,7 @@ MHC Class I Elution Prediction Algorithm Version Supports Percentile Rank
 NetMHCpanEL                              4.1     yes
 MHCflurryEL                                      | Processing Score: no;
                                                  | Presentation Score: yes
+BigMHC_EL                                        no
 ======================================== ======= ========================
 
 ========================================= ======= ========================
@@ -85,6 +86,13 @@ MHC Class II Elution Prediction Algorithm Version Supports Percentile Rank
 NetMHCIIpanEL                             4.1     yes
 ========================================= ======= ========================
 
+=============================================== ======= ========================
+MHC Class I Immunogenicity Prediction Algorithm Version Supports Percentile Rank
+=============================================== ======= ========================
+BigMHC_IM                                               no
+DeepImmuno                                              no
+=============================================== ======= ========================
+
 **Comprehensive filtering**
 
 Automatic filtering on the binding affinity ic50 (nm) value narrows down the results to only include

docs/pvacfuse/output_files.rst

@@ -88,8 +88,15 @@ _______________________________________________
 - MHCflurryEL
 - NetMHCpanEL
 - NetMHCIIpanEL
+- BigMHC_EL
 
-Please note that when running pVACfuse with only elution algorithms, no
+Prediction Algorithms Supporting Immunogenicity Scores
+______________________________________________________
+
+- BigMHC_IM
+- DeepImmuno
+
+Please note that when running pVACfuse with only elution or immunogenicity algorithms, no
 aggregate report is created.
 
 all_epitopes.tsv and filtered.tsv Report Columns

docs/pvacseq/features.rst

@@ -81,6 +81,7 @@ MHC Class I Elution Prediction Algorithm Version Supports Percentile Rank
 NetMHCpanEL                              4.1     yes
 MHCflurryEL                                      | Processing Score: no;
                                                  | Presentation Score: yes
+BigMHC_EL                                        no
 ======================================== ======= ========================
 
 ========================================= ======= ========================
@@ -89,6 +90,13 @@ MHC Class II Elution Prediction Algorithm Version Supports Percentile Rank
 NetMHCIIpanEL                             4.1     yes
 ========================================= ======= ========================
 
+=============================================== ======= ========================
+MHC Class I Immunogenicity Prediction Algorithm Version Supports Percentile Rank
+=============================================== ======= ========================
+BigMHC_IM                                               no
+DeepImmuno                                              no
+=============================================== ======= ========================
+
 **Comprehensive filtering**
 
 Automatic filtering on the binding affinity ic50 (nm) value narrows down the results to only include

docs/pvacseq/output_files.rst

@@ -102,8 +102,15 @@ _______________________________________________
 - MHCflurryEL
 - NetMHCpanEL
 - NetMHCIIpanEL
+- BigMHC_EL
 
-Please note that when running pVACseq with only elution algorithms, no
+Prediction Algorithms Supporting Immunogenicity Scores
+______________________________________________________
+
+- BigMHC_IM
+- DeepImmuno
+
+Please note that when running pVACseq with only elution or immunogenicity algorithms, no
 aggregate report and pVACview files are created.
 
 .. _all_ep_and_filtered:

docs/pvacview/getting_started.rst

@@ -68,7 +68,8 @@ Specifically, the features can be separated into five categories:
 
   - Transcript sets for a selected variant in the main aggregate report table,
     where all transcripts in the set code for the same set of neoantigen
-    candidates
+    candidates. The transcript set that includes the best transcript is
+    highlighted in green and selected by default.
   - Reference proteome match details for the selected variant (if reference
     protome similarity feature was originally run)
   - Additional Data for the selected variant when a Additional Neoantigen Candidate Aggregate Report was uploaded
@@ -83,17 +84,17 @@ Specifically, the features can be separated into five categories:
 
 - :bold:`Selected Transcript Set Peptide information`
 
-  - All good binding peptides (for at least 1 HLA allele) in the selected
-    transcript set
+  - All well-binding peptides (for at least 1 HLA allele) in the selected
+    transcript set. The best peptide is highlighted in green.
   - MHC binding prediction scores for each MT and WT peptide pair
-  - Allele-specific anchor prediction heatmap
+  - Allele-specific anchor prediction heatmap and per-position and per-allele anchor weights
 
 - :bold:`Selected Peptide information`
 
   - Per-algorithm and HLA-allele MHC binding predictions for the selected peptide and its
     matched WT (IC50 and Percentile)
   - Violin plot for the IC50 and Percentile predictions
-  - Elution data for the selected peptide and its matched WT
+  - Elution and immunogenicity data for the selected peptide and its matched WT
 
 For detailed descriptions on individual sections, please refer to :ref:`features <features_pvacview_label>` page.
 
@@ -150,9 +151,11 @@ Additionally, you can regenerate the :ref:`Tiers <pvacseq_aggregate_report_tiers
     :figclass: align-left
 
 These parameters will default to the value used in your original pVACseq run.
-After adjusting and retiering your candidates, you can reset the tiers to the
-parameters used originally by clicking the ``Reset to original paramters``
-button in the ``Original Parameters for Tiering`` section.
+After adjusting and retiering your candidates, the currently applied tiering
+parameters are displayed in the ``Current Parameters for Tiering`` section.
+The parameters originally used for tiering are displayed in the ``Original
+Parameters for Tiering`` section. You can reset the tiers to the parameters
+used originally by clicking the ``Reset to original paramters`` button.
 
 Investigating Different Variants
 ********************************

docs/releases.rst

@@ -16,3 +16,4 @@ Release Notes
    releases/3_0
    releases/3_1
    releases/4_0
+   releases/4_1