1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
|
Source: salmon
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Uploaders: Michael R. Crusoe <crusoe@debian.org>,
Kevin Murray <spam@kdmurray.id.au>
Section: science
Priority: optional
Build-Depends: debhelper-compat (= 13),
cmake,
libboost-filesystem-dev,
libboost-system-dev,
libboost-iostreams-dev,
libboost-thread-dev,
libboost-program-options-dev,
libboost-timer-dev,
libjellyfish-2.0-dev (>> 2.2.3-2),
libpthread-stubs0-dev,
libsparsehash-dev,
libdivsufsort-dev,
libbwa-dev,
pkg-config,
libjemalloc-dev,
libcereal-dev,
libtbb-dev,
libgff-dev (>> 2.0),
libstaden-read-dev,
libspdlog-dev,
libtclap-dev,
help2man,
sphinx-doc,
python3-sphinx,
python3-sphinx-rtd-theme,
zlib1g-dev,
libeigen3-dev,
libbz2-dev,
liblzma-dev,
rapmap-dev,
libsimde-dev
Standards-Version: 4.5.1
Vcs-Browser: https://salsa.debian.org/med-team/salmon
Vcs-Git: https://salsa.debian.org/med-team/salmon.git
Homepage: https://github.com/COMBINE-lab/salmon
Rules-Requires-Root: no
Package: salmon
Architecture: any-amd64 arm64
Built-Using: ${sphinxdoc:Built-Using}
Depends: ${shlibs:Depends},
${misc:Depends},
${sphinxdoc:Depends}
Description: wicked-fast transcript quantification from RNA-seq data
Salmon is a wicked-fast program to produce a highly-accurate, transcript-level
quantification estimates from RNA-seq data. Salmon achieves is accuracy and
speed via a number of different innovations, including the use of lightweight
alignments (accurate but fast-to-compute proxies for traditional read
alignments) and massively-parallel stochastic collapsed variational inference.
The result is a versatile tool that fits nicely into many different pipelines.
For example, you can choose to make use of the lightweight alignments by
providing Salmon with raw sequencing reads, or, if it is more convenient, you
can provide Salmon with regular alignments (e.g. computed with your favorite
aligner), and it will use the same wicked-fast, state-of-the-art inference
algorithm to estimate transcript-level abundances for your experiment.
|
