Model-based analysis of ChIP-Seq (MACS).
We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, 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, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.
Zhang
Yong
Y
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02115, USA.
Liu
Tao
T
Meyer
Clifford A
CA
Eeckhoute
Jérôme
J
Johnson
David S
DS
Bernstein
Bradley E
BE
Nusbaum
Chad
C
Myers
Richard M
RM
Brown
Myles
M
Li
Wei
W
Liu
X Shirley
XS
D000465:Algorithms; D045744:Cell Line, Tumor; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D051541:Hepatocyte Nuclear Factor 3-alpha / Q000032:analysis / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*
C496499:FOXA1 protein, human; D051541:Hepatocyte Nuclear Factor 3-alpha
Cell. 2008 Mar 21;132(6):958-70
18358809
Nature. 2001 Jan 25;409(6819):533-8
11206552
Annu Rev Genomics Hum Genet. 2006;7:81-102
16722805
Science. 2000 Dec 22;290(5500):2306-9
11125145
Cell. 2007 May 18;129(4):823-37
17512414
Genome Biol. 2007;8(8):R178
17727723
Nat Methods. 2007 Aug;4(8):651-7
17558387
Proc Natl Acad Sci U S A. 2006 Aug 15;103(33):12457-62
16895995
Nature. 2006 Nov 23;444(7118):444-54
17122850
Nature. 2007 Aug 2;448(7153):553-60
17603471
Nat Genet. 2006 Nov;38(11):1289-97
17013392
Cell. 2006 Jan 13;124(1):207-19
16413492
Science. 2007 Jun 8;316(5830):1497-502
17540862