1. CloudBurst
• CloudBurst : Highly Sensitive Short Read
Mapping with MapReduce
• New parallel read-mapping algorithm
optimized for mapping NGS data to the
human genome and other reference
genomes
• SNP discovery, genotyping, and personal
genomics

2. CloudBurst
• It is modeled after the short read mapping
program RMAP
• Reports either all alignments or the unambiguous
best alignment for each read with any number of
mismatches or differences
• This level of sensitivity could be prohibitively time
consuming, but CloudBurst uses the open-source
Hadoop implementation of MapReduce to
parallelize execution using multiple compute
nodes.

3. CloudBurst
• Running time
– scales linearly with the number of reads mapped
– with near linear speedup as the number of
processors increases.
• CloudBurst reduces the running time from
hours to mere minutes for typical jobs
involving mapping of millions of short reads to
the human genome.

4. Algorithm Overview
• CloudBurst uses seed-and-extend algorithms to
map reads to a reference genome.
• Seed
– k differences : the alignment must have a region of
length s=r/k+1 called a seed that exactly matches the
reference.
• Extend
– CloudBurst attempts to extend the alignment into an
end-to-end alignment with at most k mismatches or
differences

5. Algorithm Overview
• CloudBurst uses the Hadoop implementation of
MapReduce to catalog and extend the seeds
• Map phase emits
– all length-s k-mers from the reference sequences
– all non-overlapping length-s kmers from the reads
• Shuffle phase
– read and reference kmers are brought together
• Reduce phase
– the seeds are extended into end-to-end alignments

6. Algorithm Overview

7. Demo
Getting Started.docx 참고

9. Related Tools
• Bowtie: Ultrafast short read alignment
• SoapSNP: Accurate SNP/consensus calling
• Tophat: RNA-Seq splice junction mapper
• Cufflinks: Isoform assembly, quantitation
• Hadoop: Open Source MapReduce
• CloudBurst: Sensitive MapReduce alignment
• Crossbow: Read Mapping and SNP calling in the clouds
• Jnomics: Cloud-Scale Sequence Analysis
• Contrail: Cloud-based de novo assembly
• Myrna: Cloud-Scale differential expression of RNAseq

10. Q&A

11. Figure 1: A MapReduce approach for detecting genetic variants from high-throughput genome sequencing.
출처 : http://www.nature.com/nbt/journal/v30/n3/fig_tab/nbt.2134_F1.html