ZOOM Overview:
Next Generation Sequencing Software

ZOOM is designed to map millions of short reads, emerged by next-generation sequencing technology, back to the reference genomes, and carry out post-analysis. ZOOM is highly accurate, flexible and user-friendly, with speed being a critical priority.

SPEED: A single CPU with only 6.5G of memory is capable of mapping 15X coverage of a human genome in one day using ZOOM at full sensitivity while tolerating two mismatches.

ACCURACY: Using a unique spaced seed strategy, specially extended for short read mapping problems, guarantees 100% sensitivity for a wide range of read length and mismatches. Benchmark testing displays proven accuracy with the presence of insertions and deletions.

FLEXIBILITY:

• Supports Illumina/Solexa and ABI SOLiD instruments
• Easily maps reads 15 to 240 bps long
• Handles both mismatches and insertions/deletions
• Supports paired-end read mapping
• Reports uniquely mapping results or best N mapping results for each read
• Decode reads in color space into base space after automatically detecting and correcting sequencing errors for ABI SOLiD data
• Assess alignment probability using read sequence quality scores
• View graphs of mapping results in any scale desired
• Easily navigation among interested regions
• Integrated multiple sequence alignment and post-probability computing for consensus reconstruction and SNP identification
• Perform SNP analysis and view SNP candidates conveniently along with the alignments between the reads and the reference sequence
• Export mapping results or assembled sequences in multiple formats
• Support both Linux and Windows platforms

SCALABILITY. Whether running ZOOM on a single computer or a server, users can configure ZOOM to suit thier needs. This offers an ideal solution to extremely larege files as they can even be divided and scheduled to process across multiple computers and multiple CPUs automatically.

ELIMINATE FALSE POSITIVES. ZOOM increases uniquely mapped reads with quality scores and paired end statistics. This reduces the ambiguity of read mapping and increase the accurate identification.