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Installation
$ pip3 install BinSanity
- Before testing be sure you have all of the dependencies below installed
Prior to installation via pip be sure all dependencies are also installed.
Versions used at time of last update to script are provided in parenthesis.
- Python (v2.7.13+)
- Numpy (v1.17.3)
- SciKit (v0.21.3)
- Biopython (v1.74)
- Pandas (v0.25.1)
- FeatureCounts(v1.5.3)
Programs used to prepare input files for BinSanity and associated utility scripts include:
Install CheckM
-
CheckM
- Follow installation insturctions found on the CheckM wiki
- to download pplacer (a dependency of CheckM) follow the instructions here or do the following:
- Go to the pplacer webpage and click on
latest release
. This will take you to the github page and contain source code. Download the filepplacer-linux-v1.1.alpha19.zip
. In that file are pre-compiled version ofpplacer
,guppy
, andrppr
. The location of these need to be exported to your path.
- Go to the pplacer webpage and click on
$ export PATH=/LOCATION/OF/PPLACER/:$PATH
Install numpy
$ pip install numpy
- If you recieve issues running BinSanity after installing numpy try rolling the distribution back to a previous version.
Install HMMER
- HMMER can be downloaded like this:
$ wget http://eddylab.org/software/hmmer3/3.1b2/hmmer-3.1b2.tar.gz
$ tar -zxvf hmmer-3.1b2.tar.gz
$ cd hmmer-3.1b2
$ ./configure && make && sudo make install
$ cd easel && make check && sudo make install
Install featureCounts
- To do this download the latest subread package (subread-1.x.x-source.tar.gz)
$ tar zxvf subread-1.*.*-source.tar.gz
$ cd subread-1.*.*-source/src
$ make -f Makefile.Linux ; cd ../
- This will produce a directory called
bin
in thesubread-1.x.x-source
file containing the executables forfeatureCounts
. These should be copied into your path.
The Infant Gut Metagenome collected and curated by Sharon et al. (2013) was clustered by us to test BinSanity. To confirm you have BinSanity working we have provided a folder
Example
containing the fasta file (INFANT-GUT-ASSEMBLY.fa
) containing contigs for the Infant Gut Metagenome provided by Eren et al. (2015). All files associated with our BinSanity run are also provided, which includes the combined coverage profile (produced using Bowtie2 v2.2.5 on defaults,contig-coverage-bam.py
, andcov-combine.py
.
To run the test use the following command using the igm.fa and Infant_gut_assembly.cov.x100.lognorm
$ Binsanity -f . -l igm.fa -p -10 -c Infant_gut_assembly.cov.x100.lognorm
The output should be as follows:
******************************************************
**********************BinSanity***********************
|____________________________________________________|
| |
| Computing Coverage Array |
|____________________________________________________|
Preference: -10.0
Maximum Iterations: 4000
Convergence Iterations: 400
Contig Cut-Off: 1000
Damping Factor: 0.95
Coverage File: Infant_gut_assembly.cov.x100.lognorm
Fasta File: igm.fa
Output directory: BINSANITY-RESULTS
logfile: binsanity-logfile.txt
(4189, 11)
______________________________________________________
| |
| Clustering Contigs |
|______________________________________________________|
Cluster 0: 5
Cluster 1: 14
Cluster 2: 75
Cluster 3: 105
Cluster 4: 54
Cluster 5: 20
Cluster 6: 34
Cluster 7: 43
Cluster 8: 27
Cluster 9: 105
Cluster 10: 35
Cluster 11: 10
Cluster 12: 39
Cluster 13: 30
Cluster 14: 727
Cluster 15: 256
Cluster 16: 574
Cluster 17: 7
Cluster 18: 620
Cluster 19: 508
Cluster 20: 350
Cluster 21: 551
Total Number of Bins: 22
*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*|*
_____________________________________________________
| |
| Creating Bins |
|_____________________________________________________|
_____________________________________________________
Putative Bins Computed
in 233.362998962 seconds
_____________________________________________________
UNDER DEVELOPMENT, WILL BE UPDATED ASAP
Please reach out if there are any questions or comments.