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  • Originally posted by seq_GA View Post
    Hi Simon,
    Thanks for your response. I am trying to use this as part of the pipeline and hence didn't try it through win32 to access the linux server.

    Code:
    $ ./fastqc 
    Exception in thread "main" java.awt.HeadlessException:
    If you want to run the program as part of a pipeline you need to give it a list of files to process. If you don't supply any files then it will try to start up as an interactive graphical application (and you get the error you see because you're not running in a graphical environment).

    Just run it as:

    ./fastqc some_sequence_file.txt

    ..and it should work.

    Comment


    • Hi Simon,
      Thanks. It works. Its amazingly fast. Is tehre anyway that I can change the font of the graphs being drawn. because I am not able to read it clearly.

      If I view the windows version, the images are very clear and if I save them, again its bit difficult to read. Thanks again.

      Comment


      • Originally posted by seq_GA View Post
        Hi Simon,
        Thanks. It works. Its amazingly fast. Is tehre anyway that I can change the font of the graphs being drawn. because I am not able to read it clearly.
        It uses the default font in your JVM setup. A quick bit of googling says that you might be able to change this by altering your font.properties file, but I've never tried.

        Originally posted by seq_GA View Post
        If I view the windows version, the images are very clear and if I save them, again its bit difficult to read. Thanks again.
        What you save should be exactly the same as what you see in the interactive version. It's effectively just taking a screenshot of what would have been the onscreen display.

        Are you sure your viewer isn't downscaling the images in your display?

        Comment


        • I haven't changed any setting. Let me see how it goes!

          Comment


          • FastQC v0.6.0 has been released. This adds the ability to analyse SAM/BAM files directly (as well as retaining support for FastQ files). I've also made the line graphs a bit smoother than they were.

            You can get the new version from:



            [If you don't see the new version of any page hit shift+refresh to force our cache to update]

            Comment


            • Thanks again for all your hard work on this awesome tool!

              Comment


              • FastQC v0.6.1 has been released. This fixes a bug in the reading of BAM/SAM files where sequences which mapped to the reverse strand of the reference were being analysed in their reverse complemented state, and their qualities were being reversed before analysis.

                Thanks to Adrian Johnson for spotting this.

                You can get the new version from:



                [If you don't see the new version of any page hit shift+refresh to force our cache to update]

                Comment


                • Hi,

                  I am trying to run the FastQC program, but whenever I am trying to open a file I get an error:

                  Exception in thread "AWT-EventQueue-0" java.lang.ClassFormatError: Unknown constant tag 105 in class file uk/ac/bbsrc/babraham/FastQC/Modules/QCModule

                  Can you help me with that?

                  Comment


                  • Originally posted by agwe View Post
                    Hi,
                    Exception in thread "AWT-EventQueue-0" java.lang.ClassFormatError: Unknown constant tag 105 in class file uk/ac/bbsrc/babraham/FastQC/Modules/QCModule
                    That's really odd - it's an internal JVM error which suggests that either there's a problem with your JVM installation, or that the files you downloaded got corrupted somehow.

                    I've just downloaded the zip file distribution of fastqc and the sha256sum was:

                    bd823da721481d396f755f7a79b36eea84640a065e30678f05f335c119521b10 fastqc_v0.6.1.zip

                    Comment


                    • FastQC v0.7.0 has been released. This adds a new QC module which looks for enriched Kmers in the library. This can help find overrepresented sequences which are not aligned in the data, such as a library which is reading through its inserts into the adapters, but at varying points in the data.

                      You can see an example of the new plot here.

                      You can get the new version from:

                      http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/

                      [If you don't see the new version of any page hit shift+refresh to force our cache to update]
                      Last edited by simonandrews; 11-10-2010, 12:44 AM. Reason: Fixed a typo in the version number

                      Comment


                      • That's pretty neat, I'm downloading the new version.

                        Comment


                        • Hi,

                          I'm sorry if I'm asking a basic question but...

                          The Per Sequence Quality Scores module checks the most frequently observed mean quality. The docs say this: "A warning is raised if the most frequently observed mean quality is below 27 - this equates to a 0.2% error rate." How is this error rate calculated?

                          I am interested to know because I am writing a simple parser to parse the fastqc_data.txt file such, that a short text file summary can be presented to the user. I am looking to add a line like "The most observed mean quality score is ... (which means that the error rate is ...%)."

                          Cheers!

                          Comment


                          • Originally posted by Bruins View Post
                            The Per Sequence Quality Scores module checks the most frequently observed mean quality. The docs say this: "A warning is raised if the most frequently observed mean quality is below 27 - this equates to a 0.2% error rate." How is this error rate calculated?
                            Quality scores are just log transformed error rate predictions. You can just run the equation backwards to work out the error rate from the quality score.

                            100*(10**(27*-10)) = 0.2

                            This is using the Sanger conversion. The Illumina one is slightly different, but not so much that it's likely to matter under normal circumstances. The wikipedia fastq article has all of the relevant equations.

                            Whether the error rate predictions are accurate for low quality sequence is a whole different question, but theoretically that's what they mean.

                            Comment


                            • Hi Simon,

                              Thank you for your quick reply. I'll have a look at the article. Illumina now uses the Sanger convention as well, by the way (as of pipeline version 1.3).
                              Last edited by Bruins; 11-11-2010, 08:28 AM.

                              Comment


                              • Sorry for a basic question: has anyone done a benchmark to see how these quality scores affect the final output?

                                Thanks
                                Last edited by SongLi; 11-11-2010, 10:31 AM.

                                Comment

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