LSC download

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    Copyright and installation instructions are contained within the package. We strongly recommend that you consult the tutorial before attempting to use LSC.

    The latest version of Novoalign is included in the binaries for your convienience. Novoalign is developed by Novocraft and details can be found on it website. We include Novoalign since there is no guarentee that any newer or older version will be compatible.

    LSC 0.2.4 Please see the release notes for more information
    LSC 0.2.3 Please see the release notes for more information
    LSC 0.2.2 This is the recommended version for everyone. Please see the release notes for more information
    LSC 0.2.1 Please see the release notes for more information
    LSC 0.2 Please see the release notes for more information

    LSC 0.2.4 - Release Notes

    1. Besides the default aligner Novoalign, BWA can be also used as the initial aligner from this version. Please find the new aligner options in the webpage ".cfg file format"

    2. Some uncertain corrections may exsit at the right ends of the long reads in the old LSC. LSC 0.2.4 settles this problem and likely improves the accuracy further.

    LSC 0.2.3 - Release Notes

    If you run LSC at the bin folder (the bin folder is the work directory) or set the bin as the default path, then you may meet a bug. LSC 0.2.3 fixes this bug of finding the correct bin folder.

    LSC 0.2.2 - Release Notes

    LSC 0.2.2 fixes the bug of the option "I_RemoveBothTails". LSC 0.2.1 ran this option even if you set "N". It may halt the process in LSC 0.2.1 because the read name does not allow "RemoveBothTails". Now you can choose to use this option or not.

    LSC 0.2.1 - Release Notes

    LSC 0.2.1 fixes the bug of python path. Another bug of removing redundant reads is also fixed. LSC takes a long read data sets (>=100bp) and a short reads data sets (50 - 100bp) as input. They should be in FASTA format. Running time is almost linear with the the number of threads.

    LSC 0.2 - Release Notes

    LSC 0.2 takes a long read data sets (>=100bp) and a short reads data sets (50 - 100bp) as input. They should be in FASTA format. Running time is almost linear with the the number of threads.