Specifications

File Formats

• Reads input as FASTQ
• Alignments output as SAM

General Needs

• Works in letter space with RNA-Seq data
• Works in colour space with SOLiD data
• Fast
• Small memory footprint
• Align against reference with dynamic splice graph
• Minimize the size of the driver (i.e. abstract functions into classes)
• Feedback loop of discovered SNPs back into reference

Read Specific Needs

• Works with 75bp reads, up to 128bp
• Rescue transcriptome reads with huge chunks of mismatched introns (e.g. NNNIIIII; I = intron)
• Split transcriptome reads to align across an intron junction
• Handle residual introns within exome reads (e.g. NNNIINNN)
• Handle resitual introns flanking exome reads (i.e. NNNNNNII)
• Prevent losing SNPs at the end of reads from clipping (e.g. NNNNNXN; N = base; X = SNP)

Alignment Specific Needs

• User-specified method of handling multimapped reads (i.e. read mapping equally well to multiple positions)
• Supports extended CIGAR encoding (including P for Padding)
• Confirm if traceback ever needs to return multiple best alignments

Quality Specific Needs

• Alignment Score (from alignment)
• Mapping Quality (as defined by MAQ, using Mosaik's implementation)
• Uniqueness (out of 100%, divided by number best mapped positions)
• Fragment Quality (PE specific value, probability that mapped fragment (flanked by PE) location is correct/incorrect)

Build and Complication

• Have CMake detect CPU architecture and link appropriate libraries
• Build as "Release" in ccmake for full optimization

Miscellaneous Questions

• Do we ever have to assume that the reference is circular (i.e. how to handle negative and out of range positions)
• Do we ever have to support positive penalty values?