[med-svn] [Git][med-team/macs][master] Trim trailing whitespace.

[Jelmer Vernooij]

Jelmer Vernooij pushed to branch master at Debian Med / macs


Commits:
50c16d53 by Jelmer Vernooij at 2018-10-24T23:04:31Z
Trim trailing whitespace.
Fixed-Lintian-Tags: file-contains-trailing-whitespace

Fixes lintian: file-contains-trailing-whitespace
See https://lintian.debian.org/tags/file-contains-trailing-whitespace.html for more details.

- - - - -


2 changed files:

- debian/changelog
- debian/control


Changes:

=====================================
debian/changelog
=====================================
@@ -1,3 +1,9 @@
+macs (2.1.2.1-2) UNRELEASED; urgency=medium
+
+  * Trim trailing whitespace.
+
+ -- Jelmer Vernooij <jelmer at debian.org>  Wed, 24 Oct 2018 23:04:31 +0000
+
 macs (2.1.2.1-1) unstable; urgency=medium
 
   [ Jelmer Vernooij ]
@@ -103,7 +109,7 @@ macs (2.0.9.1-1ubuntu2) lucid; urgency=low
 
   * Package for PPA
   * Packaged from version 2.0.9-1
-  * Changed debian/rules to override dh_auto_clean to remove *.c files 
+  * Changed debian/rules to override dh_auto_clean to remove *.c files
 
  -- H. Soon Gweon (Key for package building) <soonio at gmail.com>  Thu, 05 Jan 2012 13:10:02 +0000
 


=====================================
debian/control
=====================================
@@ -22,11 +22,11 @@ Depends: ${python:Depends},
          ${shlibs:Depends},
          ${misc:Depends}
 Description: Model-based Analysis of ChIP-Seq on short reads sequencers
- MACS empirically models the length of the sequenced ChIP fragments, which 
- tends to be shorter than sonication or library construction size estimates, 
- and uses it to improve the spatial resolution of predicted binding sites. 
- MACS also uses a dynamic Poisson distribution to effectively capture local 
- biases in the genome sequence, allowing for more sensitive and robust 
- prediction. MACS compares favorably to existing ChIP-Seq peak-finding 
- algorithms, is publicly available open source, and can be used for ChIP-Seq 
+ MACS empirically models the length of the sequenced ChIP fragments, which
+ tends to be shorter than sonication or library construction size estimates,
+ and uses it to improve the spatial resolution of predicted binding sites.
+ MACS also uses a dynamic Poisson distribution to effectively capture local
+ biases in the genome sequence, allowing for more sensitive and robust
+ prediction. MACS compares favorably to existing ChIP-Seq peak-finding
+ algorithms, is publicly available open source, and can be used for ChIP-Seq
  with or without control samples.



View it on GitLab: https://salsa.debian.org/med-team/macs/commit/50c16d53bbbc440540784bd550a8f71b9b5e6746

-- 
View it on GitLab: https://salsa.debian.org/med-team/macs/commit/50c16d53bbbc440540784bd550a8f71b9b5e6746
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