Title :
Workshop: Graph compression approaches in assembly
Author :
Pell, Jason ; Hintze, Arend ; Canino-Koning, Rosangela ; Howe, A. ; Tiedje, James M. ; Brown, C. Titus
Author_Institution :
Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
Using a probabilistic data structure to store DNA assembly graphs results in a significant memory savings over other methods. As long as the Bloom filter remains below a specific false positive rate, it remains possible to traverse the graph. Using a Bloom filter has many applications in metagenomics, mRNAseq, read filtering, and error correction. We are currently exploring these possibilities and more.
Keywords :
DNA; data structures; filtering theory; genomics; graph theory; molecular biophysics; probability; Bloom filter; DNA assembly graph; error correction; graph compression approach; mRNAseq; metagenomics; probabilistic data structure; read filtering; Assembly; Bioinformatics; DNA; Data structures; Educational institutions; Genomics; Soil; Bloom filters; de Bruijn graphs; k-mers; metagenomics; next-generation sequencing;
Conference_Titel :
Computational Advances in Bio and Medical Sciences (ICCABS), 2012 IEEE 2nd International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4673-1320-9
Electronic_ISBN :
978-1-4673-1319-3
DOI :
10.1109/ICCABS.2012.6182675
