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| align="center" | [https://arrow.apache.org arrow] | | align="center" | [https://arrow.apache.org arrow] | ||
| align="center" | tools | | align="center" | tools | ||
| align="center" | 0.11.1, 0.15.1, 0.16.0, 0.17.1, 2.0.0, 5.0.0, 7.0.0, 8.0.0, 9.0.0, 10.0.1, 11.0.0, 12.0.1, 13.0.0, 14.0.0, 14.0.1, 15.0.1 | | align="center" | 0.11.1, 0.15.1, 0.16.0, 0.17.1, 1.0.0, 2.0.0, 5.0.0, 7.0.0, 8.0.0, 9.0.0, 10.0.1, 11.0.0, 12.0.1, 13.0.0, 14.0.0, 14.0.1, 15.0.1 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Apache Arrow is a cross-language development platform for in-memory data. Homepage: https://arrow.apache.org URL: https://arrow.apache.org Compatible modules: python/3.11, python/3.10 Keyword:tools<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Apache Arrow is a cross-language development platform for in-memory data. Homepage: https://arrow.apache.org URL: https://arrow.apache.org Compatible modules: python/3.11, python/3.10 Keyword:tools<br /><br /><br /></div> | ||
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| align="center" | bio | | align="center" | bio | ||
| align="center" | 3.0.4 | | align="center" | 3.0.4 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: BayesAss: Bayesian Inference of Recent Migration Using Multilocus Genotypes Homepage | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: BayesAss: Bayesian Inference of Recent Migration Using Multilocus Genotypes Homepage: http://www.rannala.org/?page_id=245 Keyword:bio<br /><br /><br /></div> | ||
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| align="center" | [http://www.rannala.org/inference-of-recent-migration bayesass3-snps] | | align="center" | [http://www.rannala.org/inference-of-recent-migration bayesass3-snps] | ||
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| align="center" | - | | align="center" | - | ||
| align="center" | 1.03 | | align="center" | 1.03 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: bgc implements Bayesian estimation of genomic clines to quantify introgression at many loci. Models are available for linked loci, genotype uncertainty and sequence errors. Models for genotype uncertainty and sequence error can be used to estimate genomic cline parameters from next-generation sequence data. Homepage: https://sites.google.com/site/bgcsoftware/<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: bgc implements Bayesian estimation of genomic clines to quantify introgression at many loci. Models are available for linked loci, genotype uncertainty and sequence errors. Models for genotype uncertainty and sequence error can be used to estimate genomic cline parameters from next-generation sequence data. Homepage: https://sites.google.com/site/bgcsoftware/ URL: https://sites.google.com/site/bgcsoftware/<br /><br /><br /></div> | ||
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| align="center" | [https://bitbucket.org/gavinband/bgen/src/default/ bgen] | | align="center" | [https://bitbucket.org/gavinband/bgen/src/default/ bgen] | ||
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| align="center" | bio | | align="center" | bio | ||
| align="center" | 1.30, 1.31 | | align="center" | 1.30, 1.31 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: FragGeneScan is an application for finding (fragmented) genes in short reads. Homepage | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: FragGeneScan is an application for finding (fragmented) genes in short reads. Homepage: http://omics.informatics.indiana.edu/FragGeneScan/ Keyword:bio<br /><br /><br /></div> | ||
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| align="center" | [http://grigoriefflab.janelia.org/frealign frealign] | | align="center" | [http://grigoriefflab.janelia.org/frealign frealign] | ||
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| align="center" | tools | | align="center" | tools | ||
| align="center" | 0.3.1 | | align="center" | 0.3.1 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: This is GLOST, the Greedy Launcher Of Small Tasks. Homepage: https://github.com/cea-hpc/glost Keyword:tools<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: This is GLOST, the Greedy Launcher Of Small Tasks. Homepage: https://github.com/cea-hpc/glost URL: https://github.com/cea-hpc/glost Keyword:tools<br /><br /><br /></div> | ||
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| align="center" | [https://www.gnu.org/software/glpk/ glpk] | | align="center" | [https://www.gnu.org/software/glpk/ glpk] | ||
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| align="center" | vis | | align="center" | vis | ||
| align="center" | 5.99.0 | | align="center" | 5.99.0 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Grace is a WYSIWYG 2D plotting tool for X Windows System and Motif. Homepage: http://freecode.com/projects/grace Keyword:vis<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Grace is a WYSIWYG 2D plotting tool for X Windows System and Motif. Homepage: http://freecode.com/projects/grace URL: http://freecode.com/projects/grace Keyword:vis<br /><br /><br /></div> | ||
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| align="center" | [http://grackle.readthedocs.io grackle] | | align="center" | [http://grackle.readthedocs.io grackle] | ||
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| align="center" | bio | | align="center" | bio | ||
| align="center" | 2.0.1 | | align="center" | 2.0.1 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Minimac3 is a lower memory and more computationally efficient implementation of the genotype imputation algorithms in minimac and minimac2. Minimac3 is designed to handle very large reference panels in a more computationally efficient way with no loss of accuracy. Homepage: http://genome.sph.umich.edu/wiki/Minimac3 Keyword:bio<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: Minimac3 is a lower memory and more computationally efficient implementation of the genotype imputation algorithms in minimac and minimac2. Minimac3 is designed to handle very large reference panels in a more computationally efficient way with no loss of accuracy. Homepage: http://genome.sph.umich.edu/wiki/Minimac3 URL: http://genome.sph.umich.edu/wiki/Minimac3 Keyword:bio<br /><br /><br /></div> | ||
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| align="center" | [https://genome.sph.umich.edu/wiki/Minimac4 minimac4] | | align="center" | [https://genome.sph.umich.edu/wiki/Minimac4 minimac4] | ||
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| align="center" | [https://repast.github.io/ repasthpc] | | align="center" | [https://repast.github.io/ repasthpc] | ||
| align="center" | bio | | align="center" | bio | ||
| align="center" | 2.2.0, 2.3.0 | | align="center" | 2.0, 2.2.0, 2.3.0 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: The Repast Suite is a family of advanced, free, and open source agent-based modeling and simulation platforms that have collectively been under continuous development for over 15 years: Repast for High Performance Computing 2.2.0, released on 30 September 2016, is a lean and expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers. Homepage: https://repast.github.io/ URL: https://repast.github.io/ Keyword:bio<br /><br /><br /></div> | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: The Repast Suite is a family of advanced, free, and open source agent-based modeling and simulation platforms that have collectively been under continuous development for over 15 years: Repast for High Performance Computing 2.2.0, released on 30 September 2016, is a lean and expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers. Homepage: https://repast.github.io/ URL: https://repast.github.io/ Keyword:bio<br /><br /><br /></div> | ||
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| align="center" | - | | align="center" | - | ||
| align="center" | 6.0.1.5, 8.6.1.6 | | align="center" | 6.0.1.5, 8.6.1.6 | ||
| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: NVIDIA TensorRT is a platform for high-performance deep learning inference Homepage: https://developer.nvidia.com/tensorrt URL: https://developer.nvidia.com/tensorrt Compatible modules: | | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: NVIDIA TensorRT is a platform for high-performance deep learning inference Homepage: https://developer.nvidia.com/tensorrt URL: https://developer.nvidia.com/tensorrt Compatible modules: python/3.10, python/3.11<br /><br /><br /></div> | ||
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| align="center" | [https://github.com/tesseract-ocr/tesseract tesseract] | | align="center" | [https://github.com/tesseract-ocr/tesseract tesseract] |