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ABySS 1.9.0
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by
Ben Vandervalk
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published
May 29, 2015
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last modified
May 29, 2015 03:55 PM
This release introduces a new paired de Bruijn graph mode for assembly. In paired de Bruijn graph mode, ordinary k-mers are replaced by k-mer pairs, where each k-mer pair is separated by a fixed-size gap. The primary advantage of paired de Bruijn graph mode is that the span of a k-mer pair can be arbitrarily wide without consuming additional memory, and thus provides improved scalability for assemblies of long sequencing reads.
This release also introduces a new tool called Sealer for closing scaffold gaps, new Konnector functionality for producing long pseudo-reads, and support for the DIDA (Distributed Indexing Disptached Alignment) parallel alignment framework.
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ABySS 2.0.0
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by
Ben Vandervalk
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published
Sep 01, 2016
This release introduces a new Bloom filter assembly mode that enables large genome assemblies with minimal memory (e.g. 34 GB for H. sapiens with 76X coverage bfc-corrected reads). Bloom filter assemblies are currently less contiguous than the default (MPI) assembly mode but are still of high quality (e.g. 3.5 Mbp vs. 4.8 Mbp scaffold NG50 for H. sapiens). Bloom filter assembly mode is enabled by adding three 'abyss-pe' parameters (B = *Bloom filter size*, H = *number of Bloom filter hash functions*, kc = *k-mer coverage threshold*). See 'README.md' for an example.
This release also updates several 'abyss-pe' parameter defaults to be more suitable for large genome assemblies with recent Illumina data. In addition, ABySS 2.0.0 includes minor usability improvements for 'abyss-sealer' and removes an unnecessary build dependency on sqlite3.
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ABySS 2.0.1
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by
Ben Vandervalk
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published
Sep 14, 2016
This release resolves some licensing issues with that were pointed out in 2.0.0. As of 2.0.1, ABySS is now available under a standard GPL-3 license, and the libraries included under `lib/rolling-hash` and `lib/bloomfilter` are now also licensed under GPL-3. For alternative licensing terms, please contact Patrick Rebstein (prebstein at bccancer.bc.ca).
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ABySS 2.0.2
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by
Ben Vandervalk
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published
Oct 21, 2016
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last modified
Jan 19, 2017 02:25 PM
Fix compile errors with gcc-6 and boost-1.62.
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ABySS 2.0.3
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by
Ben Vandervalk
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published
Mar 14, 2018
This minor release provides bug fixes and improved reliability for both MPI assemblies and Bloom filter assemblies on large datasets. In addition, many usability improvements have been made to the `abyss-samtobreak` program for misasssembly assessment.
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ABySS 2.1.0
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by
Ben Vandervalk
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published
Apr 13, 2018
This release adds support for misassembly correction and scaffolding
using linked reads, using Tigmint and ARCS. (Tigmint and ARCS must be installed separately.) In addition, simultaneous optimization of `s` (seed length) and `n` (min supporting read pairs / Chromium barcodes) is now supported during scaffolding.
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ABySS 2.1.1
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by
Ben Vandervalk
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published
Sep 11, 2018
This release provides bug fixes and modest improvements to
Bloom filter assembly contiguity/correctness. Parallelization
of Sealer has also been improved, thanks to contributions by
@schutzekatze.
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ABySS 2.1.2
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by
Ben Vandervalk
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published
Oct 24, 2018
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last modified
Oct 24, 2018 12:38 PM
This release improves scaffold N50 on human by ~10%, due to implementation of a new `--median` option for `DistanceEst` (thanks to @lcoombe!). This release also adds a new `--max-cost` option for `konnector` and `abyss-sealer` that curbs indeterminately long running times, particularly at low k values.
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ABySS 2.1.3
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by
Ben Vandervalk
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published
Nov 05, 2018
This release fixes a SAM-formatting bug that broke the ABySS-LR pipeline (Tigmint/ARCS).
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ABySS 2.1.4
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by
Ben Vandervalk
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published
Nov 09, 2018
This release provides major improvements to Bloom filter assembly contiguity
and correctness. Bloom filter assemblies now have equivalent scaffold contiguity
and better correctness than MPI assemblies of the same data, while still
requiring less than 1/10th of the memory. On human, Bloom filter assembly times
are still a few hours longer than MPI assemblies (e.g. 17 hours vs. 13 hours,
using 48 threads).
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