maq_cs_wrapper.py $output1 $output2 $ref $library_type.f3_reads $library_type.f3_qual $library_type.is_paired #if $library_type.is_paired == "yes": $library_type.r3_reads $library_type.r3_qual #else: "None" "None" #end if $min_mapqual $max_mismatch $output3 No Yes .. class:: infomark **What it does** This tool maps SOLiD color-space reads against the target genome using MAQ. It produces three output datasets: **ALIGNMENT INFO** : contains the read alignment information, **PILEUP** : contains the coverage and SNP statistics for every nucleotide of the target genome, **CUSTOM TRACK** : contains the coverage and SNP statistics as custom tracks displayable in the UCSC browser. ----- **The ALIGNMENT INFO dataset will contain the following fields:** * column 1 = read name * column 2 = chromosome * column 3 = position * column 4 = strand * column 5 = insert size from the outer coorniates of a pair * column 6 = paired flag * column 7 = mapping quality * column 8 = single-end mapping quality * column 9 = alternative mapping quality * column 10 = number of mismatches of the best hit * column 11 = sum of qualities of mismatched bases of the best hit * column 12 = number of 0-mismatch hits of the first 24bp * column 13 = number of 1-mismatch hits of the first 24bp on the reference * column 14 = length of the read * column 15 = read sequence * column 16 = read quality **The PILEUP dataset will contain the following fields:** * column 1 = chromosome * column 2 = position * column 3 = reference nucleotide * column 4 = coverage (number of reads that cover this position) * column 5 = number of SNPs * column 6 = number of As * column 7 = number of Ts * column 8 = number of Gs * column 9 = number of Cs