[Blends-commit] r2781 - in /projects/med/trunk/debian-med/tasks: bio bio-ngs
tille at users.alioth.debian.org
tille at users.alioth.debian.org
Mon Apr 25 20:46:57 UTC 2011
Author: tille
Date: Mon Apr 25 20:46:51 2011
New Revision: 2781
URL: http://svn.debian.org/wsvn/blends/?sc=1&rev=2781
Log:
Finished fixing Depends values and Pkg-Description; Some better formatting of a long description
Modified:
projects/med/trunk/debian-med/tasks/bio
projects/med/trunk/debian-med/tasks/bio-ngs
Modified: projects/med/trunk/debian-med/tasks/bio
URL: http://svn.debian.org/wsvn/blends/projects/med/trunk/debian-med/tasks/bio?rev=2781&op=diff
==============================================================================
--- projects/med/trunk/debian-med/tasks/bio (original)
+++ projects/med/trunk/debian-med/tasks/bio Mon Apr 25 20:46:51 2011
@@ -3824,18 +3824,20 @@
Published-In: Genome Biology
Published-Year: 2002
-Depends: eHive production system
+Depends: e-hive
Homepage: http://www.ensembl.org/info/docs/eHive/index.html
License: Not specified
+Pkg-Description: distributed processing system based on 'autonomous agents'
This is a distributed processing system based on 'autonomous agents' and
Hive behavioural structure of Honey Bees . It implements all functionality
of both data-flow graphs and block-branch diagrams which should allow it
to codify any program, algorithm, or parallel processing job control system.
It is not bound to any processing 'farm' system and can be adapted to any GRID.
-Depends: Chado
+Depends: chado
Homepage: http://gmod.org/wiki/Chado
License: Not specified
+Pkg-Description: relational database schema for data frequently encountered in modern biology
Chado is a relational database schema that underlies many GMOD installations.
It is capable of representing many of the general classes of data frequently
encountered in modern biology such as sequence, sequence comparisons,
@@ -3844,15 +3846,17 @@
be considered one of the most sophisticated relational schemas currently
available in molecular biology.
-Depends: CMap
+Depends: cmap
Homepage: http://gmod.org/wiki/CMap
License: Not specified
+Pkg-Description: view comparisons of genetic and physical maps
CMap is a web-based tool that allows users to view comparisons of genetic and
physical maps. The package also includes tools for curating map data.
-Depends: GBrowse_syn
+Depends: gbrowse-syn
Homepage: http://gmod.org/wiki/GBrowse_syn
License: Not specified
+Pkg-Description: Generic Synteny Browser
GBrowse_syn, or the Generic Synteny Browser, is a GBrowse-based synteny
browser designed to display multiple genomes, with a central reference
species compared to two or more additional species. It can be used to
@@ -3861,16 +3865,18 @@
GBrowse_syn is included with the standard GBrowse package (version 1.69 and
later). Working examples can be seen at TAIR and WormBase.
-Depends: JBrowse
+Depends: jbrowse
Homepage: http://gmod.org/wiki/JBrowse
License: Not specified
+Pkg-Description: genome browser with an AJAX-based interface
JBrowse is a genome browser with an AJAX-based interface. JBrowse renders most
tracks using client side JavaScript and JSON as its data transfer format.
JBrowse is the official successor to GBrowse.
-Depends: Tripal
+Depends: tripal
Homepage: http://www.genome.clemson.edu/software/tripal
License: GPL ( as Drupal a derivative )
+Pkg-Description: collection of Drupal modules for genomic research
Tripal is a collection of open-source freely available Drupal modules under
development at CUGI and a member of the GMOD family of tools. Tripal serve
as a web interface for the GMOD Chado database. Tripal intially started as
@@ -3882,8 +3888,9 @@
databases are projects of the Main Bioinformatics Laboratory at Washington
State University
-Depends: GeneMark
+Depends: genemark
Homepage: http://exon.biology.gatech.edu/
-License: Academic License Agreement ( http://exon.biology.gatech.edu/license_download.cgi )
+License: Academic License Agreement
+Pkg-Description: family of gene prediction programs
A family of gene prediction programs developed at Georgia Institute of
Technology, Atlanta, Georgia, USA.
Modified: projects/med/trunk/debian-med/tasks/bio-ngs
URL: http://svn.debian.org/wsvn/blends/projects/med/trunk/debian-med/tasks/bio-ngs?rev=2781&op=diff
==============================================================================
--- projects/med/trunk/debian-med/tasks/bio-ngs (original)
+++ projects/med/trunk/debian-med/tasks/bio-ngs Mon Apr 25 20:46:51 2011
@@ -129,41 +129,45 @@
This package was requested by William Spooner <whs at eaglegenomics.com> as
a competitor to MIRA2 and wgs-assembler.
-Depends: ECHO
+Depends: uc-echo
Homepage: http://uc-echo.sourceforge.net/
License: BSD License
+Pkg-Description: error correction algorithm designed for short-reads from next-generation sequencing
ECHO is an error correction algorithm designed for short-reads from
next-generation sequencing platforms such as Illumina's Genome Analyzer II.
The algorithm uses a Bayesian framework to improve the quality of the reads
in a given data set by employing maximum a posteriori estimation.
-Depends: ANNOVAR
+Depends: annovar
Homepage: http://www.openbioinformatics.org/annovar/
License: Open Source for non-profit
+Pkg-Description: annotate genetic variants detected from diverse genomes
ANNOVAR is an efficient software tool to utilize update-to-date information
- to functionally annotate genetic variants detected from diverse genomes
+ to functionally annotate genetic variants detected from diverse genomes
(including human genome hg18, hg19, as well as mouse, worm, fly, yeast and
many others). Given a list of variants with chromosome, start position, end
position, reference nucleotide and observed nucleotides, ANNOVAR can perform:
- 1) Gene-based annotation: identify whether SNPs or CNVs cause protein coding
- changes and the amino acids that are affected. Users can flexibly use RefSeq
- genes, UCSC genes, ENSEMBL genes, GENCODE genes, or many other gene definition
- systems.
- 2) Region-based annotations: identify variants in specific genomic regions,
- for example, conserved regions among 44 species, predicted transcription
- factor binding sites, segmental duplication regions, GWAS hits, database
- of genomic variants, DNAse I hypersensitivity sites, ENCODE
- H3K4Me1/H3K4Me3/H3K27Ac/CTCF sites, ChIP-Seq peaks, RNA-Seq peaks, or many
- other annotations on genomic intervals.
- 3) Filter-based annotation: identify variants that are reported in dbSNP,
- or identify the subset of common SNPs (MAF>1%) in the 1000 Genome Project,
- or identify subset of non-synonymous SNPs with SIFT score>0.05, or many
- other annotations on specific mutations.
- 4) Other functionalities: Retrieve the nucleotide sequence in any
- user-specific genomic positions in batch, identify a candidate gene list
- for Mendelian diseases from exome data, identify a list of SNPs from
- 1000 Genomes that are in strong LD with a GWAS hit, and many other
- creative utilities.
+ .
+ 1. Gene-based annotation: identify whether SNPs or CNVs cause protein coding
+ changes and the amino acids that are affected. Users can flexibly use RefSeq
+ genes, UCSC genes, ENSEMBL genes, GENCODE genes, or many other gene definition
+ systems.
+ 2. Region-based annotations: identify variants in specific genomic regions,
+ for example, conserved regions among 44 species, predicted transcription
+ factor binding sites, segmental duplication regions, GWAS hits, database
+ of genomic variants, DNAse I hypersensitivity sites, ENCODE
+ H3K4Me1/H3K4Me3/H3K27Ac/CTCF sites, ChIP-Seq peaks, RNA-Seq peaks, or many
+ other annotations on genomic intervals.
+ 3. Filter-based annotation: identify variants that are reported in dbSNP,
+ or identify the subset of common SNPs (MAF>1%) in the 1000 Genome Project,
+ or identify subset of non-synonymous SNPs with SIFT score>0.05, or many
+ other annotations on specific mutations.
+ 4. Other functionalities: Retrieve the nucleotide sequence in any
+ user-specific genomic positions in batch, identify a candidate gene list
+ for Mendelian diseases from exome data, identify a list of SNPs from
+ 1000 Genomes that are in strong LD with a GWAS hit, and many other
+ creative utilities.
+ .
In a modern desktop computer (3GHz Intel Xeon CPU, 8Gb memory), for
4.7 million variants, ANNOVAR requires ~4 minutes to perform
gene-based functional annotation, or ~15 minutes to perform stepwise
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