A5030209108- Genomics and Phylogenetic Studies
- Genomics and Chromatin Dynamics
- Molecular Biology Techniques and Applications
- Genomic variations and chromosomal abnormalities
- Chromosomal and Genetic Variations
McGill University
2016-2018
Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal any given dataset. In contrast, regions with without peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose supervised machine learning approach using labels that encode qualitative judgments about genomic contain or do peaks. The main idea to manually label small subset the genome, then learn...
Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which method and what parameters are optimal any given set. In contrast, peaks can easily be located by visual inspection of profile on a genome browser. We thus propose supervised machine learning approach to using annotated regions that encode an expert's qualitative judgments about contain or do peaks. The main idea manually annotate small subset the genome, then learn model makes...