Colleen Clarke
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Colleen Clarke has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
- Anthony Albano
Center for Applied Genomics, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
1 shared publication - Avni Santani
Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA. santani@.chop.edu
1 shared publication - Cecilia Kim
Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
1 shared publication - Emily Place
Division of Human Genetics, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
1 shared publication - Hakon Hakonarson
The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
1 shared publication - Hongbo Michael Xie
Center for Biomedical Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
1 shared publication
Latest Publications
- Open Access
- 19 October 2011
- Published by Springer Nature in BMC Bioinformatics
- Vol. 12 (1) , 402
Mitochondrial genome sequence analysis: A custom bioinformatics pipeline substantially improves Affymetrix MitoChip v2.0 call rate and accuracy
Mitochondrial genome sequence analysis is critical to the diagnostic evaluation of mitochondrial disease. Existing methodologies differ widely in throughput, complexity, cost efficiency, and sensitivity of heteroplasmy detection. Affymetrix MitoChip v2.0, which uses a sequencing-by-genotyping technology, allows potentially accurate and high-throughput sequencing of the entire human mitochondrial genome to be completed in a cost-effective fashion. However, the relatively low call rate achieved using existing software tools has limited the wide adoption of this platform for either clinical or research applications. Here, we report the design and development of a custom bioinformatics software pipeline that achieves a much improved call rate and accuracy for the Affymetrix MitoChip v2.0 platform. We used this custom pipeline to analyze MitoChip v2.0 data from 24 DNA samples representing a broad range of tissue types (18 whole blood, 3 skeletal muscle, 3 cell lines), mutations (a 5.8 kilobase pair deletion and 6 known heteroplasmic mutations), and haplogroup origins. All results were compared to those obtained by at least one other mitochondrial DNA sequence analysis method, including Sanger sequencing, denaturing HPLC-based heteroduplex analysis, and/or the Illumina Genome Analyzer II next generation sequencing platform.
- 19 October 2011
- Published by Springer Nature in BMC Bioinformatics
- Vol. 12 (1) , 402
Open AccessMitochondrial genome sequence analysis: A custom bioinformatics pipeline substantially improves Affymetrix MitoChip v2.0 call rate and accuracy
Mitochondrial genome sequence analysis is critical to the diagnostic evaluation of mitochondrial disease. Existing methodologies differ widely in throughput, complexity, cost efficiency, and sensitivity of heteroplasmy detection. Affymetrix MitoChip v2.0, which uses a sequencing-by-genotyping technology, allows potentially accurate and high-throughput sequencing of the entire human mitochondrial genome to be completed in a cost-effective fashion. However, the relatively low call rate achieved using existing software tools has limited the wide adoption of this platform for either clinical or research applications. Here, we report the design and development of a custom bioinformatics software pipeline that achieves a much improved call rate and accuracy for the Affymetrix MitoChip v2.0 platform. We used this custom pipeline to analyze MitoChip v2.0 data from 24 DNA samples representing a broad range of tissue types (18 whole blood, 3 skeletal muscle, 3 cell lines), mutations (a 5.8 kilobase pair deletion and 6 known heteroplasmic mutations), and haplogroup origins. All results were compared to those obtained by at least one other mitochondrial DNA sequence analysis method, including Sanger sequencing, denaturing HPLC-based heteroduplex analysis, and/or the Illumina Genome Analyzer II next generation sequencing platform.