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author | Petar Petrov <petar.petrov@student.oulu.fi> | 2013-12-14 21:36:42 +0700 |
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committer | Erik Hanson <erik@slackbuilds.org> | 2013-12-14 10:53:07 -0600 |
commit | af993d7297b601a7d1faa6e731d3e07aa2bd5726 (patch) | |
tree | 14eea3066ddf63f23f7c65eb4a569dded3c74bb6 /academic/cistrome-MACS/README | |
parent | c732454ecf95097afba466a66d2cef0e14730d36 (diff) |
academic/cistrome-MACS: Added (Model-based Analysis of ChIP-Seq).
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
Diffstat (limited to 'academic/cistrome-MACS/README')
-rw-r--r-- | academic/cistrome-MACS/README | 16 |
1 files changed, 16 insertions, 0 deletions
diff --git a/academic/cistrome-MACS/README b/academic/cistrome-MACS/README new file mode 100644 index 000000000000..d039cfacfd6e --- /dev/null +++ b/academic/cistrome-MACS/README @@ -0,0 +1,16 @@ +MACS: Model-based Analysis of ChIP-Seq + +Next generation parallel sequencing technologies made chromatin +immunoprecipitation followed by sequencing (ChIP-Seq) a popular +strategy to study genome-wide protein-DNA interactions, while creating +challenges for analysis algorithms. We present Model-based Analysis of +ChIP-Seq (MACS) on short reads sequencers such as Genome Analyzer +(Illumina / Solexa). 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. |