Tailseeker 3.1.7

Changes in tailseeker 3.1.7

• Fix the docker wrapper script to take up the environment variable TAILSEEKER_REFDBDIR correctly.
• Remove U3 and 7SL RNAs from contaminant database pipeline.
• Fix the compatibility issue with recent versions of snakemake.
• Add support for MiSeq v3 chemistry.
• Fix a crash issue in tailseq-dedup-perfect when it fails if more than 1024 alignments with less optimal TAIL-seq signals are followed after an alignment with better signals.
• Fix a problem in plotting a virtual gel with recent versions of pandas.

Notes

• tailseeker-3.1.7.tar.gz is a source release. You need to install few external programs to fulfill the dependencies and some build tools before installing it.
• tailseeker-3.1.7-bundle-ubuntu_xenial.tar.gz is a full bundle binary release with source codes. It contains pre-built binary files of tailseeker and many of its external dependencies. As the binaries were built on a Intel x64 machine with Ubuntu Linux 16.04, you may encounter some incompatibility problems on the other platforms. It is highly recommended to use the Docker image in those environments.

Tailseeker 3.1.6

Changes in tailseeker 3.1.6

• Fix an issue on error-tolerant duplicate matching that
  wrong tags are randomly discarded due to the uninitialized
  memory.

Notes

• tailseeker-3.1.6.tar.gz is a source release. You need to install few external programs to fulfill the dependencies and some build tools before installing it.
• tailseeker-3.1.6-bundle-ubuntu_xenial.tar.gz is a full bundle binary release with source codes. It contains pre-built binary files of tailseeker and many of its external dependencies. As the binaries were built on a Intel x64 machine with Ubuntu Linux 16.04, you may encounter some incompatibility problems on the other platforms. It is highly recommended to use the Docker image in those environments.

Tailseeker 3.1.4 is released

Changes:

• IUPAC degenerate bases are now accepted inside the
  delimiter sequence.
• External calls are now more adaptive when installed
  with a full-bundle binary package. PATH and
  LD_LIBRARY_PATH are set and handed over to the subprocess
  commands.

Notes:

• tailseeker-3.1.4.tar.gz is a source release. You need to install few external programs to fulfill the dependencies and some build tools before installing it.
• tailseeker-3.1.4-bundle-ubuntu_xenial.tar.gz is a full bundle binary release with source codes. It contains pre-built binary files of tailseeker and many of its external dependencies. As the binaries were built on a Intel x64 machine with Ubuntu Linux 16.04, you may encounter some incompatibility problems on the other platforms. It is highly recommended to use the Docker image in those environments.

Tailseeker 3.1.1

This version fixes several minor problems on using configurations generated through the newweb-based wizard. The entry command for the pipeline is changed to tseek instead of tseek run.

Tailseeker 3.1.0

This is the first experimental release, a.k.a. alpha, of the Tailseeker 3. This version produces significantly different measurements from those by previous versions. New features added are:

• Fully automatic discovery for internal poly(A) controls. Now, no training, inspections, or data pre-processing using poly(A) standards are required. Molecules with >120nt poly(A) tails are automatically picked up from the samples, and they are used as seeds for further processing.
• Adaptive poly(A) score cut-off determination. This version adds an iterative sampler for poly(A) score distributions. It starts finding poly(A) signals from the seeds explained above, and produces score thresholds to be used in the final measurements.
• Robust processing for low quality runs. The scripts are now use various strategies handling missing or outstanding values from low quality imaging or reactions. Most cases are handled reasonably without any manual tuning.
• Fair sampling for high abundant contaminants. Like ribosomal RNAs and snRNAs, highly abundant RNAs often skew the signal distribution of non-poly(A) tails into awkward positions. Now, the signal processor takes care of the sequence duplicity in negative case sampling.

In spite of the large version number, tailseeker is not a production-ready software, yet. You may find documentation and error handling are not very user-friendly.