MaSC: Mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data

Bioinformatics

Volumn 29, Issue 4, 2013, Pages 444-450

  Ramachandran, Parameswaran ^a,b   Palidwor, Gareth A ^a   Porter, Christopher J ^a   Perkins, Theodore J ^a,b  

^a OTTAWA HOSPITAL RESEARCH INSTITUTE   (Canada)

^b UNIVERSITY OF OTTAWA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; CHROMOSOME MAP; EVALUATION; GENOMICS; HIGH THROUGHPUT SEQUENCING; HUMAN; METHODOLOGY; REPRODUCIBILITY; STATISTICAL ANALYSIS;

ALGORITHMS; CHROMOSOME MAPPING; DATA INTERPRETATION, STATISTICAL; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; REPRODUCIBILITY OF RESULTS;

MLCS; MLOWN;

EID: 84874299672     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt001     Document Type: Article

References (16)

1. Barrett, T. et al. (2011) NCBI GEO: archive for functional genomics data sets-10 years on. Nucleic Acids Res., 39 (Suppl. 1), D1005-D1010.
2. Feng, X. et al. (2011) Peakranger: a cloud-enabled peak caller for CHIP-seq data. BMC Bioinformatics, 12, 139.
3. Jothi, R. et al. (2008) Genome-wide identification of in vivo protein-DNA binding sites from ChIP-Seq data. Nucleic Acids Res., 36, 5221-5231.
4. Karolchik, D. et al. (2004) The UCSC table browser data retrieval tool. Nucleic Acids Res., 32 (Suppl. 1), D493-D496.
5. Kharchenko, P.V. et al. (2008) Design and analysis of CHIP-seq experiments for DNA-binding proteins. Nat. Biotechnol., 26, 1351-1359.
6. Koehler, R. et al. (2011) The uniqueome: a mappability resource for short-tag sequencing. Bioinformatics, 27, 272-274.
7. Landt, S.G. et al. (2012) ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res., 22, 1813-1831.
8. Mardis, E.R. (2011) A decades perspective on DNA sequencing technology. Nature, 470, 198-203.
9. Narzisi, G. and Mishra, B. (2011) Comparing de novo genome assembly: the long and short of it. PLoS ONE, 6, e19175.
10. Pepke, S. et al. (2009) Computation for CHIP-seq and RNA-seq studies. Nat. Methods, 6, S22-S32.
11. Rozowsky, J. et al. (2009) Peakseq enables systematic scoring of CHIP-seq experiments relative to controls. Nat. Biotechnol., 27, 66-75.
12. Sarkar, D. et al. (2012) Chipseq: A Package for Analyzing Chipseq Data. [R package]. version 1.6.1 http://www.bioconductor.org/packages/2.12/bioc/ manuals/chipseq/man/chipseq.pdf (20 January 2013, date last accessed).
13. Tuteja, G. et al. (2009) Extracting transcription factor targets from CHIP-seq data. Nucleic Acids Res., 37, e113.
14. Valouev, A. et al. (2008) Genome-wide analysis of transcription factor binding sites based on CHIP-seq data. Nat. Methods, 5, 829-834.
15. Wilbanks, E.G. and Facciotti, M.T. (2010) Evaluation of algorithm performance in CHIP-seq peak detection. PLoS ONE, 5, e11471.
16. Zhang, Y. et al. (2008)Model-based analysis of CHIP-seq (MACS). Genome Biol., 9, R137.