Copyright and installation instructions are contained within the package. We strongly recommend that you consult the tutorial before attempting to use LSC.
From LSC 0.3, we do not recommend you to use Novoalign any more, which makes LSC slow and lower sensitivity. However, you can still use it if you want to. Novoalign is developed by Novocraft and details can be found on it website.
|LSC 1.alpha||Please see the release notes for more information|
|LSC 0.3.1||Please see the release notes for more information|
|LSC 0.3||Please see the release notes for more information|
|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||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 1.alpha - Release Notes
In the LSC 0.3.0 or 0.3.1, we optimized the setting of bowtie2 and BWA to get much more short read alignment, which improve the the accuracy of error correction a lot/ However, the increase of alignments also requires much more running time (on both alignment and the following error correction step) and memory usage. Therefore, a few users met difficulty of running LSC 0.3.0 or 0.3.1.
In LSC 1.alpha, we apply probabilistic algorithm ("SCD" option) to select ""enough" short read alignment for error correction. LSC 1.alpha does NOT sacrifice the error correction performace (sensitivity and specificity). Please see http://www.healthcare.uiowa.edu/labs/au/LSC/LSC_manual.html#aligner Thus, we save running time and memory usage significantly. The running time is 30-50% of LSC 0.3.1. The peak memory usage decreases to ~10G regardless of the data size.
- Added probabilistic algorithm ("SCD" option) to pre-select SR alignments results based on LR-SR alignment coverage depth (Significant improvement in running time and memory usage)
- Removed requirement for loading SR dataset in memory to generate LR-SR mapping file (Significant improvement in memory usage)
- Added option "sort_max_mem" in run.cfg to control maximum memory used by unix sort command to avoid unexpected Mem crash
- Fixed a bug in generating FASTQ file (it affected some of QualityValue computation results)
LSC 0.3.1 - Release Notes
In LSC 0.3.1, we don't have pseudo chromosome, the alignment time reduced to ~10% (in Bowtie2 mode). And you can re-run some crashed jobs easily now.
- Remove pseudo-chr processing
- Accept compressed SR as input (should be named SR.fa.cps/SR.fa.cps.idx in any folder)
- Added "runLSC -cleanup" option to remove redundant files (per thread split, remaining _tmp files) if the run was successful at the end.
- Changed convertNav to sort reads and then generate LR_SR.map (memory optimization instead of loading all alignments in memory)
- Changed "print" to system.echo (messages were not printed out in qsub output files)
- Changed a little bit "cleanup" option to keep per thread data (*.aa, *.ab, ..). It was useful when one thread was crashed and we wanted to just re-run that at the end
LSC 0.3 - Release Notes
In LSC 0.3, we have a few updates. They are very IMPORTANT updates, new features and small fixes
Very IMPORTANT updates:
- Support for RazerS3 and Bowtie2 as initial aligners. Now, BWA, Bowtie2, RazerS3 and Novoalign work in LSC.
Added SR length coverage percentage on LR (SR-covered length/full length of corrected LR) to corrected_LR output file. Here is an example, where the last number 0.82 is the SR length coverage percentage on LR:
- Added support for three modes for step-wise runs:
- Generating fastq output format
Using the correction probability given coverage in the LSC paper and fitted a log function to it and then used the probability values to compute Sanger quality score: 33 - 10 * log10(1 - p).
For the locations:
- - without any SR coverage I used the default quality score of p = 0.725 (the same in your paper).
- - with SR coverage but without any correction point, I used the number of covered SRs
- - with SR coverage in a correction point (either because of compression or mismatch), I used number of SRs that had similar sequence with the substitute bases
(i.e. the number of covered SRs that have the max number of similar sequence not the total number covered SRs.)
- mode 0: end-to-end
- mode 1: generating LR_SR.map file
- mode 2: correction step
- Used the python path in the cfg file instead of default user\bin path
- Added option (-clean_up) to remove intermediate files or not (Note: important/useful ones will still be there in temp folder)
- Support for input fastq format for LR (long reads) and/or SR (short reads)
- Updated default BWA and novoalign commands options
- Printing out original LR names in the output file
- Support for printing out version number and (-v/-version) option
- Fixed in removing XZ pattern from end of uncorrected_LR file
- Fixed samParser bug (which was ignoring some valid alignments in case of BWA)
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.
- Python (version 2.6 or higher) should be installed in the default user bin "#!/usr/bin/python"
- Novoalign should be in your default path. The version V2.07.10 is recommended.
- A new option of using nonredandunt reads that save ~40% running time
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.
- More optional for raw data prefilter
- Multi-threading is avaiable
- Reduced redundant temp files