FAQ
How do I get started?Why are there two buttons for loading "annotations"?
Why can't I see anything when I load my annotation file?
How do I close a track annotation?
How do I write a plug-in?
What file formats are supported?
What are the system requirements?
How do I get started?
If your data are already in FASTA and GFF format, it's probably safe to start with the quick start guide. If not, try the more detailed manual first.Why are there two buttons for loading "annotations"?
BioSAVE supports display of two distinct kinds of annotation (although it reads both from GFF format). The first of these is in the form of an "on sequence" annotation. Only one of these annotation files can be loaded at any one time (by clicking the "Load annotation" button), although each file may contain multiple annotations, as shown here:
The second kind of annotation is a "track" annotation, which is displayed along the bottom of the sequence view. Multiple track annotations can be loaded simultaneously, as depicted here:
Why can't I see anything when I load my annotation file?
If you're loading an "on sequence" annotation, first of all check that the file has loaded by verifying that the "Current annotation file" field in the middle of the main window contains the expected file path.If the path is present and looks correct, then check that some annotations have loaded in the annotation list at the bottom left of the main window, like these:
If no annotations are visible in this list, something has gone wrong with file parsing. If you used a script plug-in to pre-process the file, run the script independently of BioSAVE to verify that it is producing valid GFF output. If the output of the script is valid, please file a bug report by emailing rfp26 [at] mrc-lmb.cam.ac.uk with "bug" in the subject line. If possible, please either attach or provide a link to your sample data.
If annotations are visible in the motif list, select one or more of them, click the "Visible" check box (either in the list or to the right) and slide the cutoff sliders such that some of the annotations' scores lie between the values:
If there is still nothing visible in the view, remember that annotations are only shown for the currently selected sequence. If your sequence file contained multiple sequences, ensure that the appropriate one is selected from the sequence menu in the toolbar:
If the correct sequence is selected and the annotation cutoff values have been set appropriately, check that there is no "white space" (spaces, tabs etc.) at either end of the sequence name in the sequence and annotation files, as BioSAVE will include this as part of the name. If there isn't and you've tried all of the above, please email rfp26 [at] mrc-lmb.cam.ac.uk with "bug" in the subject line, preferably attaching any data for testing.
How do I close a track annotation?
Click once on the track to bring up the track configuration head-up display (HUD) and click on the "Close Track" button:
How do I write a plug-in?
Plug-ins for BioSAVE come in the form of shell scripts in the widest possible sense: bash, tcsh, ksh, perl, php, ruby, python etc. Basically, any script that can run at the command line can run as a BioSAVE plug-in, provided that it:- is able to write GFF formatted data to stdout
- is located in the ~/Application Support/BioSAVE directory
- has its second line formatted like this: # BioSAVE:Human-readable string where human-readable string is the string that will appear in the menu of available plugins
- is executable (it should start with a "shebang" line and have the executable permission bit set — chmod a+x pluginname.)
What file formats are supported?
Natively, BioSAVE supports FASTA files for protein and DNA sequence data and GFF files for any sequence annotation. However, through the script plug-in architecture, any file format may be parsed on-the-fly and read into the program from the comfort of the "Open" dialog box.What are the system requirements?
BioSAVE is a universal binary that will run on any Macintosh computer running Mac OS X 10.3.9 (Panther) or above. For larger data sets (e.g. above 3 Mb), a healthy amount of RAM and a fast processor (G5 or Intel) are recommended.