pychopper 2.7.10-1 source package in Ubuntu

Changelog

pychopper (2.7.10-1) unstable; urgency=medium

  * Team upload
  * New upstream version 2.7.10
  * Remove build dependency on python3-six
  * Use dh-sequence-python3
  * Annotate sphinx dependencies as <!nodoc>
  * Add build dependency on python3-zombie-imp

 -- Alexandre Detiste <email address hidden>  Wed, 31 Jul 2024 14:25:07 +0200

Upload details

Uploaded by:
Debian Med
Uploaded to:
Sid
Original maintainer:
Debian Med
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

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Builds

Oracular: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
pychopper_2.7.10-1.dsc 2.8 KiB 73465b7622f99f40489caa6d560a2851f30bf3fc244513fb406acd6350b98156
pychopper_2.7.10.orig.tar.gz 59.6 MiB 99be3fd0f3e051868b7fcfa1dd88a12470e2ed0c54c326af95eba83311966595
pychopper_2.7.10-1.debian.tar.xz 4.7 KiB 6b326fcc803c53b9276e97ef6fa32c72ca04a51e56ad47a4fa238656b552d80e

Available diffs

No changes file available.

Binary packages built by this source

python3-pychopper: identify, orient and trim full-length Nanopore cDNA reads

 Pychopper v2 is a Python module to identify, orient and trim full-length
 Nanopore cDNA reads. It is also able to rescue fused reads and provides
 the script 'pychopper.py'. The general approach of Pychopper v2
 is the following:
 .
  * Pychopper first identifies alignment hits of the primers across the
    length of the sequence. The default method for doing this is using
    nhmmscan with the pre-trained strand specific profile HMMs, included
    with the package. Alternatively, one can use the edlib backend,
    which uses a combination of global and local alignment to identify
    the primers within the read.
  * After identifying the primer hits by either of the backends, the
    reads are divided into segments defined by two consecutive primer
    hits. The score of a segment is its length if the configuration of
    the flanking primer hits is valid (such as SPP,-VNP for forward reads)
    or zero otherwise.
  * The segments are assigned to rescued reads using a dynamic programming
    algorithm maximizing the sum of used segment scores (hence the amount
    of rescued bases). A crucial observation about the algorithm is that
    if a segment is included as a rescued read, then the next segment
    must be excluded as one of the primer hits defining it was "used
    up" by the previous segment. This put constraints on the dynamic
    programming graph. The arrows in read define the optimal path for
    rescuing two fused reads with the a total score of l1 + l3.
 .
 A crucial parameter of Pychopper v2 is -q, which determines the
 stringency of primer alignment (E-value in the case of the pHMM
 backend). This can be explicitly specified by the user, however by
 default it is optimized on a random sample of input reads to produce
 the maximum number of classified reads.