Running TRANSIT¶
TRANSIT can be run in either GUI mode or in console mode. GUI Mode will be run if TRANSIT is not given any command-line argumentsl. If any arguments are given, TRANSIT will run in console-mode.
The exact commands will vary depending on the method of installation. Details are given below:
GUI Mode¶
In general, if you installed TRANSIT as a python package (e.g. using pip install tnseq-transit), then the proper way to run TRANSIT in GUI mode is simply to type the following into a console:
transit
Note
In windows, you will likely have to navigate to C:Python2.7Scripts to be able to recognize the transit.exe file.
If, however, you installed transit by downloading and extracting the source-code archive, you can run TRANSIT in GUI mode by typing in the command line:
python PATH/src/transit.py
where PATH is the path to the TRANSIT installation directory. You might be able to double-click on icon for transit.py, if your OS associates .py files with python and automatically runs them.
Note
Note, because TRANSIT has a graphical user interface, if you are trying to run TRANSIT in GUI mode across a network, for example by running on a unix server but displaying on a desktop machine, you will probably need to use ‘ssh -Y’ and a local X11 client (like Xming or Cygwin/X on PCs). This will allow the GUI component to be properly displayed accross the network connection.
Command line Mode¶
TRANSIT can also be run purely the command line, without a GUI interface. This is convenient if you want to run many analyses in batch, as you can write a script that automatically runs several analyses in parallel or in sequence
If you installed TRANSIT as a python package, you can get a list of possible arguments by typing:
- ::
- transit -h
Or if you installed it by downloading and extracting an archive with the source code:
python PATH/src/transit.py -h
In most cases TRANSIT expects the user to specify which analysis method they wish to run as their first argument. The user will need to type the short-name of the analysis method desired, e.g. “gumbel”, “hmm”, or “resampling”. By choosing a method, and adding the “-h” flag, you will get a list of all the necessary parameters and optional flags for the chosen method.
If you installed TRANSIT as a python package, you can achieve this by typing:
- ::
- transit gumbel -h
Or if you installed it by downloading and extracting an archive with the source code:
python PATH/src/transit.py gumbel -h
Gumbel¶
To run the Gumbel analysis from the command line, type “python PATH/src/transit.py gumbel” followed by the following arguments:
| Argument | Type | Description | Default | Example |
|---|---|---|---|---|
| annotation | Required | Path to annotation file in .prot_table format | genomes/H37Rv. prot_table | |
| control_files | Required | Comma-separate d list of paths to the *.wig replicate datasets | data/glycerol_reads_rep1.w ig,data/glycer ol_reads_rep 2.wig | |
| output_file | Required | Name of the output file with the results. | results/gumbel _glycerol.dat | |
| -s SAMPLES | Optional | Number of samples to take. | 10000 | -s 20000 |
| -m MINREAD | Optional | Smallest read-count considered to be an insertion. | 1 | -m 2 |
| -b BURNIN | Optional | Burn in period, Skips this number of samples before getting estimates. See documentation. | 500 | -b 100 |
| -t TRIM | Optional | Number of samples to trim. See documentation. | 1 | -t 2 |
| -r REP | Optional | How to handle replicates read-counts: ‘Sum’ or ‘Mean’. | Sum | -r Mean |
| -iN IGNOREN | Optional | Ignore TAs occuring at X% of the N terminus. | 5 | -iN 0 |
| -iC IGNOREC | Optional | Ignore TAs occuring at X% of the C terminus. | 5 | -iC 10 |
python PATH/src/transit.py gumbel genomes/H37Rv.prot_table data/glycerol_reads_rep1.wig,data/glycerol_reads_rep2.wig test_console_gumbel.dat -s 20000 -b 1000
Tn5 Gaps¶
To run the Tn5 Gaps analysis from the command line, type “python PATH/src/transit.py tn5gaps” followed by the following arguments:
Argument Type Description Default Example annotation Required Path to annotation file in .prot_table format genomes/Salmonella- Ty2.prot_table control_files Required Comma-separated list of paths to the *.wig replicate datasets data/salmonella_2122_rep1.wig,data/salmonella_2122_rep2.wig output_file Required Name of the output file with the results. results/test_console_tn5gaps.dat -m MINREAD Optional Smallest read- count considered to be an insertion. 1 -m 2 -r REP Optional How to handle replicates read-counts: ‘Sum’ or ‘Mean’. Sum -r Sum
Example Tn5 Gaps command:
python PATH/src/transit.py tn5gaps genomes/Salmonella-Ty2.prot_table data/salmonella_2122_rep1.wig,data/salmonella_2122_rep2.wig results/test_console_tn5gaps.dat -m 2 -r Sum
Example HMM command:
python PATH/src/transit.py hmm genomes/H37Rv.prot_table data/glycerol_reads_rep1.wig,data/glycerol_reads_rep2.wig test_console_hmm.dat -r Sum
Resampling¶
To run the Resampling analysis from the command line, type “python PATH/src/transit.py resampling” followed by the following arguments:
| Argument | Type | Description | Default | Example |
|---|---|---|---|---|
| annotation | Required | Path to annotation file in .prot_table format | genomes/H37Rv. prot_table | |
| control_files | Required | Comma-separate d list of paths to the *.wig replicate datasets for the control condition | data/glycerol_reads_rep1.w ig,data/glycer ol_reads_rep 2.wig | |
| exp_files | Required | Comma-separate d list of paths to the *.wig replicate datasets for the experimental condition | data/cholester ol_reads_rep 1.wig,data/cho lesterol_read s_rep2.wig | |
| output_file | Required | Name of the output file with the results. | results/gumbel _glycerol.dat | |
| -s SAMPLES | Optional | Number of permutations performed. | 10000 | -s 5000 |
| -H | Optional | Creates histograms of the permutations for all genes. | Not set | -H |
| -a | Optional | Performs adaptive appoximation to resampling. | Not set | -a |
| -N | Optional | Select which normalizing procedure to use. Can choose between ‘TTR’, ‘nzmean’, ‘totreads’, ‘zinfnb’, ‘betageom’, and ‘nonorm’. See the parameters section for the Re-sampling method for a description of these normalization options. | nzmean | -N nzmean |
| -iN IGNOREN | Optional | Ignore TAs occuring at X% of the N terminus. | 5 | -iN 0 |
| -iC IGNOREC | Optional | Ignore TAs occuring at X% of the C terminus. | 5 | -iC 10 |
Example Resampling command:
python PATH/src/transit.py resampling genomes/H37Rv.prot_table data/glycerol_reads_rep1.wig,data/glycerol_reads_rep2.wig data/cholesterol_reads_rep1.wig,data/cholesterol_reads_rep2.wig,data/cholesterol_reads_rep3.wig test_console_resampling.dat -H -s 10000 -N nzmean