MultiQC: Summarize analysis results for multiple tools and samples in a single report

Bioinformatics

Volumn 32, Issue 19, 2016, Pages 3047-3048

  Ewels, Philip ^a   Magnusson, Måns ^b   Lundin, Sverker ^c   Käller, Max ^c  

^a STOCKHOLM UNIVERSITY   (Sweden)

^b KAROLINSKA INSTITUTE   (Sweden)

^c ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGY; HIGH THROUGHPUT SEQUENCING; QUALITY CONTROL; SOFTWARE;

COMPUTATIONAL BIOLOGY; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; QUALITY CONTROL; SOFTWARE;

EID: 84988570649     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btw354     Document Type: Article

References (6)

1. Hunter, J.D. (2007) Matplotlib: A 2D Graphics Environment. Comput. Sci. Eng., 9, 9095.
2. Leek, J.T. et al. (2010) Tackling the widespread and critical impact of batch effects in high-throughput data. Nat. Rev. Genet., 11, 733739.
3. Meyer, C.A. and Liu, X.S. (2014) Identifying and mitigating bias in next-generation sequencing methods for chromatin biology. Nat. Rev. Genet., 15, 709721.
4. Okonechnikov, K. et al. (2015) Qualimap 2: advanced multi-sample quality control for high-throughput sequencing data. Bioinformatics, 32, 292-294.
5. Taub, M.A. et al. (2010) Overcoming bias and systematic errors in next generation sequencing data. Genome Med., 2, 87.
6. Wang, L. et al. (2012) RSeQC: quality control of RNA-seq experiments. Bioinformatics, 28, 21845.