Difference between revisions of "Khmer"
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__NOTOC__ | __NOTOC__ | ||
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| − | [[Category:Software]][[Category: | + | [[Category:Software]][[Category:Biology]][[Category:NGS]] |
{|<!--Main settings - REQUIRED--> | {|<!--Main settings - REQUIRED--> | ||
|{{#vardefine:app|khmer}} | |{{#vardefine:app|khmer}} | ||
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Use "import khmer" in your script or in an interactive python session. | Use "import khmer" in your script or in an interactive python session. | ||
<!--Modules--> | <!--Modules--> | ||
| − | == | + | ==Environment Modules== |
| − | + | Run <code>module spider {{#var:app}}</code> to find out what environment modules are available for this application. | |
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| − | |||
==System Variables== | ==System Variables== | ||
| − | * HPC_{{ | + | * HPC_{{uc:{{#var:app}}}}_DIR - installation directory |
* HPC_KHMER_BIN | * HPC_KHMER_BIN | ||
* HPC_KHMER_LIB | * HPC_KHMER_LIB | ||
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If you use any of khmer's published scientific methods, you should *also* cite the relevant paper(s), as directed below. | If you use any of khmer's published scientific methods, you should *also* cite the relevant paper(s), as directed below. | ||
| − | + | <div class="mw-collapsible mw-collapsed" style="width:70%; padding: 5px; border: 1px solid gray;"> | |
| + | ''Expand to view citation instructions.'' | ||
| + | <div class="mw-collapsible-content" style="padding: 5px;"> | ||
* Graph partitioning and/or compressible graph representation | * Graph partitioning and/or compressible graph representation | ||
: The load-graph.py, partition-graph.py, find-knots.py, load-graph.py, and partition-graph.py scripts are part of the compressible graph representation and partitioning algorithms described in: | : The load-graph.py, partition-graph.py, find-knots.py, load-graph.py, and partition-graph.py scripts are part of the compressible graph representation and partitioning algorithms described in: | ||
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:: arXiv:1309.2975 [q-bio.GN] | :: arXiv:1309.2975 [q-bio.GN] | ||
:: http://arxiv.org/abs/1309.2975 | :: http://arxiv.org/abs/1309.2975 | ||
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Latest revision as of 17:01, 14 December 2022
Description
Khmer - python scripts for k-mer counting, filtering and graph traversal.
Available scripts: abundance-dist.py, count-median.py, do-partition.sh, filter-abund.py, find-knots.py, load-into-counting.py, merge-partitions.py, normalize-by-median.py, partition-graph.py, annotate-partitions.py, count-overlap.py, extract-partitions.py, filter-stoptags.py, load-graph.py, make-initial-stoptags.py, normalize-by-kadian.py, normalize-by-min.py
Use "import khmer" in your script or in an interactive python session.
Environment Modules
Run module spider khmer to find out what environment modules are available for this application.
System Variables
- HPC_KHMER_DIR - installation directory
- HPC_KHMER_BIN
- HPC_KHMER_LIB
Citation
If you use the khmer software, you must cite:
- Crusoe et al., The khmer software package: enabling efficient sequence analysis. 2014. doi: 10.6084/m9.figshare.979190
If you use any of khmer's published scientific methods, you should *also* cite the relevant paper(s), as directed below.
Expand to view citation instructions.
- Graph partitioning and/or compressible graph representation
- The load-graph.py, partition-graph.py, find-knots.py, load-graph.py, and partition-graph.py scripts are part of the compressible graph representation and partitioning algorithms described in:
- Pell J, Hintze A, Canino-Koning R, Howe A, Tiedje JM, Brown CT
- Proc Natl Acad Sci U S A. 2012 Aug 14;109(33):13272-7
- doi: 10.1073/pnas.1121464109
- PMID: 22847406
- Digital normalization
- The normalize-by-median.py and count-median.py scripts are part of the digital normalization algorithm, described in:
- A Reference-Free Algorithm for Computational Normalization of Shotgun Sequencing Data
- Brown CT, Howe AC, Zhang Q, Pyrkosz AB, Brom TH
- arXiv:1203.4802 [q-bio.GN]
- http://arxiv.org/abs/1203.4802
- K-mer counting
- The abundance-dist.py, filter-abund.py, and load-into-counting.py scripts implement the probabilistic k-mer counting described in:
- These are not the k-mers you are looking for: efficient online k-mer counting using a probabilistic data structure
- Zhang Q, Pell J, Canino-Koning R, Howe AC, Brown CT.
- arXiv:1309.2975 [q-bio.GN]
- http://arxiv.org/abs/1309.2975