Commit b4a90f6a authored by Sergio_Arredondo's avatar Sergio_Arredondo

Removing the display of the dataframe with the weights in the output

parent 6385457d
......@@ -145,113 +145,67 @@ species.
## 1 mlplasmids
## 6
##
## [Wed Jan 22 13:31:18 2020]
## Job 5: Extracting the links from the graph test/faecium_graph.gfa
## [Wed Jan 22 13:56:34 2020]
## Job 1: Extracting the nodes from the graph test/faecium_graph.gfa
##
## Activating conda environment: /home/sergi/gplas/.snakemake/conda/70552874
## [Wed Jan 22 13:31:23 2020]
## Finished job 5.
## [Wed Jan 22 13:56:38 2020]
## Finished job 1.
## 1 of 6 steps (17%) done
##
## [Wed Jan 22 13:31:23 2020]
## Job 1: Extracting the nodes from the graph test/faecium_graph.gfa
## [Wed Jan 22 13:56:38 2020]
## Job 5: Extracting the links from the graph test/faecium_graph.gfa
##
## Activating conda environment: /home/sergi/gplas/.snakemake/conda/70552874
## [Wed Jan 22 13:31:26 2020]
## Finished job 1.
## [Wed Jan 22 13:56:41 2020]
## Finished job 5.
## 2 of 6 steps (33%) done
##
## [Wed Jan 22 13:31:26 2020]
## [Wed Jan 22 13:56:41 2020]
## Job 3: Running mlplasmids to obtain the plasmid prediction using the nodes extracted from the graph. If this is the first time running mlplasmids, installation can take a few minutes
##
## Activating conda environment: /home/sergi/gplas/.snakemake/conda/70552874
## [Wed Jan 22 13:31:40 2020]
## [Wed Jan 22 13:56:54 2020]
## Finished job 3.
## 3 of 6 steps (50%) done
##
## [Wed Jan 22 13:31:40 2020]
## [Wed Jan 22 13:56:54 2020]
## Job 2: Extracting the sd k-mer coverage from the chromosome-predicted contigs
##
## R script job uses conda environment but R_LIBS environment variable is set. This is likely not intended, as R_LIBS can interfere with R packages deployed via conda. Consider running `unset R_LIBS` or remove it entirely before executing Snakemake.
## Activating conda environment: /home/sergi/gplas/.snakemake/conda/70552874
## WARNING: ignoring environment value of R_HOME
## [Wed Jan 22 13:31:52 2020]
## [Wed Jan 22 13:57:07 2020]
## Finished job 2.
## 4 of 6 steps (67%) done
##
## [Wed Jan 22 13:31:52 2020]
## [Wed Jan 22 13:57:07 2020]
## Job 4: Searching for plasmid-like walks using a greedy approach
##
## R script job uses conda environment but R_LIBS environment variable is set. This is likely not intended, as R_LIBS can interfere with R packages deployed via conda. Consider running `unset R_LIBS` or remove it entirely before executing Snakemake.
## Activating conda environment: /home/sergi/gplas/.snakemake/conda/70552874
## WARNING: ignoring environment value of R_HOME
## [Wed Jan 22 13:32:28 2020]
## [Wed Jan 22 13:57:50 2020]
## Finished job 4.
## 5 of 6 steps (83%) done
##
## [Wed Jan 22 13:32:28 2020]
## [Wed Jan 22 13:57:50 2020]
## Job 0: Generating weights for the set of new edges connecting plasmid unitigs
##
## R script job uses conda environment but R_LIBS environment variable is set. This is likely not intended, as R_LIBS can interfere with R packages deployed via conda. Consider running `unset R_LIBS` or remove it entirely before executing Snakemake.
## Activating conda environment: /home/sergi/gplas/.snakemake/conda/70552874
## WARNING: ignoring environment value of R_HOME
## NULL
## From_to To_from weight
## 1 18 33 116
## 2 18 47 142
## 3 18 31 94
## 4 18 60 100
## 5 18 50 108
## 6 18 52 314
## 7 18 57 360
## 8 18 54 148
## 9 18 46 38
## 10 33 47 100
## 11 31 33 88
## 12 33 60 90
## 13 33 50 92
## 14 33 52 124
## 15 33 57 136
## 16 33 54 50
## 17 33 46 46
## 18 31 47 142
## 19 47 60 152
## 20 47 50 164
## 21 47 52 106
## 22 47 57 140
## 23 47 54 50
## 24 46 47 64
## 25 31 60 220
## 26 31 50 186
## 27 31 52 92
## 28 31 57 108
## 29 31 54 42
## 30 31 46 120
## 31 50 60 232
## 32 52 60 94
## 33 57 60 110
## 34 54 60 38
## 35 46 60 118
## 36 50 52 98
## 37 50 57 118
## 38 50 54 42
## 39 46 50 108
## 40 52 57 342
## 41 52 54 130
## 42 46 52 40
## 43 54 57 252
## 44 46 57 44
## 45 46 54 14
## Algorithm Modularity Original_component Decision
## 1 Walktrap 0.13 1 No_split
## 2 Leading-eigen 0.13 1 No_split
## 3 Louvain 0.13 1 No_split
## null device
## 1
## [Wed Jan 22 13:32:45 2020]
## [Wed Jan 22 13:58:04 2020]
## Finished job 0.
## 6 of 6 steps (100%) done
## Complete log: /home/sergi/gplas/.snakemake/log/2020-01-22T133118.420801.snakemake.log
## Complete log: /home/sergi/gplas/.snakemake/log/2020-01-22T135633.934474.snakemake.log
## _______ .______ __ ___ _______.
## / _____|| _ \ | | / \ / |
## | | __ | |_) | | | / ^ \ | (----`
......@@ -431,24 +385,20 @@ Mandatory arguments:
Optional arguments:
- **-n**: Project name given to gplas. Default: ‘unnamed’
- **-t**: Threshold to predict plasmid-derived sequences. Integer
value ranging from 0 to 1. Default mlplasmids threshold: 0.5 Default
plasflow threshold: 0.7
- **-x**: Number of times gplas finds plasmid paths per each plasmid
starting node. Integer value ranging from 1 to infinite. Default: 20
- **-f**: Gplas filtering threshold score to reject possible outcoming
edges. Integer value ranging from 0 to 1. Default: 0.1
- **-q**: Modularity threshold to split components present in the
plasmidome network. Integer value ranging from 0 to 1. Default: 0.2
For benchmarking purposes you can pass a complete genome to gplas
and will generate a precision and completeness. Using this you can
assess the performance of gplas on a small set of genomes in which
perhaps you have generated long-reads.
For benchmarking purposes you can pass a complete genome to gplas and
will generate a precision and completeness. Using this you can assess
the performance of gplas on a small set of genomes in which perhaps you
have generated long-reads.
- **-r**: Path to the complete reference genome corresponding to the
graph given. For optimal results using this benchmarking flag,
......
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