ClaraGenomicsAnalysis Release 0.4.0

Release 0.4.0 adds several performance and API updates to the Clara Genomics Analysis SDK.

The following are highlights of this release -

1. CUDA Mapper

• Significant performance improvements to all-vs-all overlap generation using cudamapper.

2. CUDA POA

• New C++ and Python graph APIs for inspecting graphs generated during partial order alignment process.
• Bug fixes and general improvements.

3. CUDA Aligner

• Major bug fix for Myers Hirschberg implementation.

4. Pyclaragenomics

• Improvements to evaluate_paf script for comparing overlap files.

5. SDK Improvements

• New PyPI pcakages available for pyclaragenomics. Details in pyclaragenomics README.

ClaraGenomicsAnalysis Release 0.3.0

Release 0.3.0 adds new tools, functionality and APIs to the Clara Genomics Analysis SDK.

The following are highlights of this release -

1. CUDA Mapper
   New A CUDA-accelerated implementation of the minimap2 algorithm. This first release of cudamapper focuses primarily on single GPU all-to-all mapping.

2. CUDA Aligner*

• New Improved performance of Myers-Hirschberg implementation on batches with very long sequences (~64k)
• New Python API for CUDA Aligner

3. SDK Improvements

• New Debian and RPM packaging support for the SDK.
• New Online Doxygen documentation for C++ API

ClaraGenomicsAnalysis Release 0.2.0

Release v0.2.0 brings new features, APIs and performance improvements to the Clara Genomics Analysis SDK.

The following are the major additions to this release -

1. CUDAPOA

• New C++ API for creating CUDAPOA batches.
• New Python API bindings for CUDAPOA in pyclaragenomics
• New Python and C++ samples to guide usage of relevant APIs
• Lower memory footprint batches, requiring less than 50% of earlier versions, allowing more POA groups to be computed within a batch.
• Overall batched POA time down by ~20% on medium to large size batches (300-400 POA groups per batch).

2. CUDAALIGNER

• New Myers + Hirschberg implementation for global alignment, allowing for larger batches of longer sequences to be aligned on the GPU.

3. SDK Improvements

• New CUDA 9.0 support added to SDK

ClaraGenomicsAnalysis Release 0.1.0

This release is the first official release of ClaraGenomicsAnalysis SDK. The modules developed in this release are geared primarily towards long-read use cases, such as with data from Oxford Nanopore Technologies or PacBio.

The main components of this release are -

1. cudapoa - CUDA accelerated Partial Order Alignment, including support for consensus and multi-sequence alignment generation.
2. cudaaligner - CUDA accelerated batched global alignment based on Ukkonen's algorithm.