1.4.5

This is a hotfix release. It fixes the following issues:

• In a previous version we implemented a faster method for reading data from the database in pVACapi. However, this would fail if the postgres user is not a superuser. This version fixes this issue by using the previous database file read method in this situation.
• This version marks certain columns of the output reports as not visualizable in pVACviz/pVACapi because they contain string content that cannot be plotted in a scatterplot.

1.4.4

This is a hotfix release. It fixes the following issues:

• This version starts enforcing a file size limit (14MB) to be able to visualize a result file in pVACviz. Larger files will no longer be visualizable in pVACviz since they take too long to load.

1.4.3

This is a hotfix release. It fixes the following issues:

• IEDB will output a warning if an epitope contains only amino acid symbols that could also be nucleotides. This would cause an error during parsing of the IEDB output files. This version updates the parser to ignore these warnings.
• We added some improvements to pVACapi regarding database file read speeds and transaction handling.

1.4.2

This is a hotfix release. It fixes the following issues:

• This releases fixes a concurrency issue with pVACapi/pVACviz that would occurr when users would try to visualize multiple files at the same time

1.4.1

This is a hotfix release. It fixes the following issues:

• In version 1.4 we updated our usage of conda to use conda activate instead of source activate to make it compatible with newer conda versions. However, this was leading to errors due to the way that we were calling conda. This has been updated and should resolve these types of errors.

1.4.0

This version adds the following features:

• pVACvector now tests spacers iteratively. During the first iteration, the first spacer in the list of --spacers gets tested. In the next iteration, the next spacer in the list gets added to the pool of spacers to tests, and so on. If at any point a valid ordering is found, pVACvector will finish its run and output the result. This might result in a slightly less optimal (but still valid) ordering but improves runtime significantly.
• If, after testing all spacers, no valid ordering if found, pVACvector will clip the beginning and/or ends of problematic peptides by one amino acid. The order finding process is then repeated on the updated list of peptides. This process may be repeated a number of times, depending on the value of the --max-clip-length parameter.
• This version adds a standalone command to create the pVACvector visualizations that can be run by calling pvacvector visualize using a pVACvector result file as the input.
• We removed the --aditional-input-file-list option to pVACseq. Readcount and expression information are now taken directly from the VCF annotations. Instructions on how to add these annotations to your input VCF can be found on the Input File Preparation page.
• We added support for variants to pVACseq that are only annotated as protein_altering_variant without a more specific consequence of missense_variant, inframe_insertion, inframe_deletion, or frameshift_variant.
• We resolved some syntax differences that prevented pVACtools from being run under python 3.6 or python 3.7. pVACtools should now be compatible with all python >=3.5 versions.

1.3.7

This version is a hotfix release. It fixes the following issues:

• The previous version accidentally removed the --additional-input-file-list option. It has been restored in this version. Please note that it is slated for permanent removal in the next feature release (1.4.0).

1.3.6

This version is a hotfix release. It fixes the following issues:

• Tensorflow is incompatible with multiprocessing when the parent process imports tensorflow or a tensorflow-dependent module. For this reason MHCflurry and MHCnuggets were removed from parallelization. In this release we moved to calling MHCflurry and MHCnuggets on the command line, which allowed us to remove our direct imports of these modules and allows us to parallelize the calls to these two prediction algorithms. All prediction algorithms supported by pVACtools can now be used in multiprocessing mode.
• Some users were reporting Illegal instruction (core dumped) errors because their hardware was incompatible with the version of tensorflow we were using. Pinning the tensorflow version to 1.5.0 with this release should solve this problem.
• When running in multiprocessing mode while using the IEDB API, users would experience a higher probability of failed requests to the API. The IEDB API would throw a 403 error when rejecting requests due to too many simultaneous requests. pVACtools would previously not retry on this type of error. This release now adds retries on this error code. We also improved the random wait time calculation between requests so that the likelihood of multiple retries hitting at the same time has now been reduced.
• When encountering a truncated input VCF, the VCF parser used by pVACtools would throw an error that was not indicative of the real error source. pVACseq now catches these errors and emmits a more descriptive error message when encountering a truncated VCF.
• One option when annotating a VCF with VEP is the -total-length flag. When using this flag, the total length would be written to the Protein_position field. pVACseq previously did not support a VCF with a Protein_position field in this format. This release adds support for it.
• When creating the combined MHC class I and MHC class II all_epitopes file, we were previously not correctly determining all necessary headers which would lead to incorrect output of the individual prediction algorithm score columns. This release fixes this issue.

1.3.5

This version is a hotfix release. It fixes the following issues:

• While the previous release fixed the issue of stalled processes when running IEDB-based prediction algorithms in multiprocessing mode, we were still experience a similar problem when running with MHCflurry and MHCnuggets. These two prediction algorithms are tensorflow-based which in the way it is currently used in pVACtools is not compatible with being run in multiprocessing mode. As a stop-gap measure this release removes MHCnuggets and MHCflurry from being run in multiprocessing mode. This resolves the problem until we can change our usage of these prediction algorithms to be multiprocessing-compatible.

1.3.4

This version is a hotfix release. It fixes the following issues:

• We were previously using nested multiprocessing which would cause defunct child jobs and stalled runs. Switching to single-level multiprocessing fixes this issue.
• When running pVACvector from a pVACseq result file the creation of the peptide fasta file might cause an error if the epitope was situated near the beginning of the transcript. This issue has been fixed.