Fink

Recent Package Updates

2017-03-22: libzip2-0.11.2-2 (Library for handling zip archives)
Library for handling zip archives

commit log from danielj7:
New libversion libzip5 1.2.0
2017-03-21: libzip5-1.2.0-1 (Library for handling zip archives)
Library for handling zip archives

commit log from danielj7:
New libversion libzip5 1.2.0
2017-03-20: vim-nox-8.0.494-1 (Improved version of the editor "vi")
VIM adds many of the features that you would expect in an editor:
Unlimited undo, syntax coloring, split windows, visual selection,
graphical user interface (read: menus, mouse control, scrollbars,
text selection), and much much more.

commit log from htodd:
Welcome to Vim-8.0.494.
2017-03-20: vim-8.0.494-1 (Improved version of the editor "vi")
VIM adds many of the features that you would expect in an editor:
Unlimited undo, syntax coloring, split windows, visual selection,
graphical user interface (read: menus, mouse control, scrollbars,
text selection), and much much more.

commit log from htodd:
Welcome to Vim-8.0.494.
2017-03-19: numpy-py35-1.12.1-1 (N-dimensional array package for Python)
NumPy (formerly known as scipy_core) is the fundamental package needed
for scientific computing with Python. It contains among other things:

  - a powerful N-dimensional array object
  - sophisticated (broadcasting) functions
  - tools for integrating C/C++ and Fortran code
  - useful linear algebra, Fourier transform, and random number capabilities.

Besides its obvious scientific uses, NumPy can also be used as an
efficient multi-dimensional container of generic data. Arbitrary
data-types can be defined. This allows NumPy to seamlessly and
speedily integrate with a wide variety of databases.

commit log from dmacks:
new version (https://sourceforge.net/p/fink/package-submissions/4901/)
2017-03-19: numpy-py36-1.12.1-1 (N-dimensional array package for Python)
NumPy (formerly known as scipy_core) is the fundamental package needed
for scientific computing with Python. It contains among other things:

  - a powerful N-dimensional array object
  - sophisticated (broadcasting) functions
  - tools for integrating C/C++ and Fortran code
  - useful linear algebra, Fourier transform, and random number capabilities.

Besides its obvious scientific uses, NumPy can also be used as an
efficient multi-dimensional container of generic data. Arbitrary
data-types can be defined. This allows NumPy to seamlessly and
speedily integrate with a wide variety of databases.

commit log from dmacks:
new version (https://sourceforge.net/p/fink/package-submissions/4901/)
2017-03-19: numpy-py34-1.12.1-1 (N-dimensional array package for Python)
NumPy (formerly known as scipy_core) is the fundamental package needed
for scientific computing with Python. It contains among other things:

  - a powerful N-dimensional array object
  - sophisticated (broadcasting) functions
  - tools for integrating C/C++ and Fortran code
  - useful linear algebra, Fourier transform, and random number capabilities.

Besides its obvious scientific uses, NumPy can also be used as an
efficient multi-dimensional container of generic data. Arbitrary
data-types can be defined. This allows NumPy to seamlessly and
speedily integrate with a wide variety of databases.

commit log from dmacks:
new version (https://sourceforge.net/p/fink/package-submissions/4901/)
2017-03-19: numpy-py27-1.12.1-1 (N-dimensional array package for Python)
NumPy (formerly known as scipy_core) is the fundamental package needed
for scientific computing with Python. It contains among other things:

  - a powerful N-dimensional array object
  - sophisticated (broadcasting) functions
  - tools for integrating C/C++ and Fortran code
  - useful linear algebra, Fourier transform, and random number capabilities.

Besides its obvious scientific uses, NumPy can also be used as an
efficient multi-dimensional container of generic data. Arbitrary
data-types can be defined. This allows NumPy to seamlessly and
speedily integrate with a wide variety of databases.

commit log from dmacks:
new version (https://sourceforge.net/p/fink/package-submissions/4901/)
2017-03-19: cufflinks-2.2.1-4 (RNA-Seq assembler and expression tester)
Cufflinks assembles transcripts, estimates their abundances, and tests for 
differential expression and regulation in RNA-Seq samples. It accepts 
aligned RNA-Seq reads and assembles the alignments into a parsimonious set 
of transcripts. Cufflinks then estimates the relative abundances of these 
transcripts based on how many reads support each one, taking into account 
biases in library preparation protocols.

Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, et al. 
Differential gene and transcript expression analysis of RNA-seq 
experiments with TopHat and Cufflinks. Nat Protoc. 2012;7(3):562-78. Epub 
2012/03/03. doi: 10.1038/nprot.2012.016. PubMed PMID: 22383036; PubMed 
Central PMCID: PMC3334321.

commit log from nieder:
make it work with the new version of libbam.a
2017-03-19: samtools-1.4-1 (Tools for SAM alignment files)
SAM Tools provide various utilities for manipulating alignments in 
the SAM format, including sorting, merging, indexing and generating 
alignments in a per-position format.

commit log from nieder:
samtools and bcftools 1.4
2017-03-19: bcftools-1.4-1 (Tools for VCF/BCF files)
BCFtools is a set of utilities that manipulate variant calls in the
Variant Call Format (VCF) and its binary counterpart BCF. All commands
work transparently with both VCFs and BCFs, both uncompressed and
BGZF-compressed.

Most commands accept VCF, bgzipped VCF and BCF with filetype detected
automatically even when streaming from a pipe. Indexed VCF and BCF will
work in all situations. Un-indexed VCF and BCF and streams will work in
most, but not all situations. In general, whenever multiple VCFs are
read simultaneously, they must be indexed and therefore also compressed.

BCFtools is designed to work on a stream. It regards an input file "-"
as the standard input (stdin) and outputs to the standard output
(stdout). Several commands can thus be combined with Unix pipes.

commit log from nieder:
samtools and bcftools 1.4
2017-03-19: libhts2-shlibs-1.4-2 (Library for high-throughput sequencing data)
HTSlib is an implementation of a unified C library for accessing common 
file formats, such as SAM, CRAM, VCF, and BCF, used for high-throughput 
sequencing data.  It is the core library used by samtools and bcftools.

commit log from nieder:
new pkg libhts2 1.4
2017-03-19: tabix-0.2.6-1 (Indexer for TAB-delimited genome files)
Tabix indexes a TAB-delimited genome position file in.tab.bgz and 
creates an index file in.tab.bgz.tbi when region is absent from the 
command-line. The input data file must be position sorted and 
compressed by bgzip which has a gzip(1) like interface. After 
indexing, tabix is able to quickly retrieve data lines overlapping 
regions specified in the format "chr:beginPos-endPos". Fast data 
retrieval also works over network if URI is given as a file name 
and in this case the index file will be downloaded if it is not 
present locally.

commit log from nieder:
add upgrade note
2017-03-19: breseq-0.30.0-1 (Mutation finder in microbe evolution)
breseq is a computational pipeline for finding mutations relative to a 
reference sequence in short-read DNA re-sequencing data intended for 
haploid microbial genomes (<20 Mb). breseq is a command line tool 
implemented in C++ and R.

It reports single-nucleotide mutations, point insertions and deletions, 
large deletions, and new junctions supported by mosaic reads (such as 
those produced by new mobile element insertions) in an annotated HTML 
format.

Deatherage, D.E., Barrick, J.E. (2014) Identification of mutations
in laboratory-evolved microbes from next-generation sequencing
data using breseq. Methods Mol. Biol. 1151: 165-188.

commit log from nieder:
libhts bumped libN
2017-03-18: alpine-2.21-1 (Text based tool for managing emails)
Alpine is a fast, easy to use email client that is suitable for both the
inexperienced email user as well as for the most demanding of power users.
Alpine is based on the Pine(r) Message System, which was also developed at the
University of Washington. Alpine can be learned by exploration and the use of
context-sensitive help. The user experience is highly customizable through the
use of the Alpine Setup command.

commit log from htodd:
New upstream.