INDRA v1.11.0
Python compatibility
- This release of INDRA is compatible with Python 3.5+ only and 2.x is not supported anymore.
Package structure, dependencies
- The
protmapperpackage is a new dependency which takes over interfacing with UniProt (including file-based access and web service access). Consequently, almost all functionalities ofindra.databases.uniprot_clientandindra.databases.phosphosite_client, as well as the core ofindra.preassembler.site_mapperare now provided byprotmapper. The overall API of these INDRA modules has not changed, however. - INDRA is now also available as a Docker image on Dockerhub under
labsyspharm/indra, further instructions in the README - Installation instructions for the Python-Java bridge pyjnius have been updated,
INDRA's Java/Scala based dependencies can now work with versions of Java up to 11. - The
statements.pyfile has been refactored into its own module in
indra.statements, the overall API has not changed. - INDRA's logging is now fully hierarchical and follows the submodule
structure.
Input processors
- CWMS processor in
indra.sources.cwmscan extract temporal and geo-spatial
context. - Major overhaul of Hume processor in
indra.sources.hume, supporting latest
JSON-LD format and extracting temporal and geo-spatial context - An additional JSON-based API and processor is now available for SOFIA in
indra.sources.sofia, supporting text reading. - New input processor for the RLIMS-P reading system in
indra.sources.rlimsp. - The INDRA DB REST source in
indra.sources.indra_db_resthas been refactored
into multiple files and now provides a Processor class-based interface similar
to other input sources. - More robust handling of invalid identifiers in PyBEL inputs in
indra.sources.bel. - BioPAX input processor in
indra.sources.biopaxnow eliminates spurious
duplicate extractions by patterns - New analysis script is available in
indra.sources.tripsfor TRIPS/CWMS
extractions.
Core assembly modules
- Belief engine makes a new Bayesian scorer class available in
indra.belief
which allows integrating curation directly into belief scores. - Preassembler in
indra.preassemblerpreserves original grounding in addition
to the original entity texts upon Statement deduplication. - The SiteMapper has been substantially refactored to take its core functionality from the
protmapperpackage (https://github.com/indralab/protmapper). - A new disambiguation tool, DEFT (https://github.com/indralab/deft) is now
integrated into the grounding mapping process in
indra.preassembler.grounding_mapper. - Bug fixes and performance improvements in HierarchyManager in
indra.preassembler.hierarchy_manager. - Bug fixes and performance improvements in OntologyMapper in
indra.preassembler.ontology_mapper. - Assembly pipeline in
indra.tools.assemble_corpusnow supports merging
grounding from multiple evidences at the Statement level, as well as additional
preasssembly functionalities such as evidence flattening.
Tools
- New web service added for real-time curation of Statements with belief
updates, ontology extension, and re-grounding/re-assembly in
indra.tools.live_curation.
Output assemblers
- Major overhaul of the PySB Assembler in
indra.assemblers.pysbto refactor
into multiple files, support individual statement-level policies, and passing
in parameterization from outside. - CX assembler in
indra.assemblers.cxsupports setting custom network visual
styles. - Major improvements and many new features in the HTML assembler for curation in
indra.assemblers.html, including grouping and ranking of Statements - Fixes to the SBGN assembly format in
indra.assemblers.sbgn.
Literature and database clients
- PMC client in
indra.literature.pmcnow supports getting text from NXML - Protein lengths now available via the UniProt client in
indra.databases.uniprot_client
Resources
- All resource files updated to latest version as of 12/1/2018
- New ontology mapping resources for Hume and CWMS
REST API
- Multiple new input and assembly endpoints added to the REST API for Eidos,
CWMS, Sofia, and Hume, ontology mapping, and belief filtering.