Because we only calculated uniquely mapped reads, we determined that a large number of multiple mapping were present in the uncovered regions of chromosomes 6 and Y.
After alignment, an average of 80%% of the reads, with 5%% representing multiple mapping, were mapped to the chicken reference transcriptome (Table 1).
A single map is one of many possible representations of the data, so making multiple maps is often part of a complete mapping effort.
Multiple maps were analysed using boolean logic models based on seven criteria set by a team comprising of a spatial ecologist, hydrologist, geologist, geomorphologist, an engineer and GIS/RS specialist, after a field work of one month.
Superscaffolds that were anchored in multiple maps were used as reference points to align the genetic positions in the three different maps.
Multiple position mapping was enabled and the weight of multiple mapping reads was considered.
For QTL mapping, a procedure similar to multiple interval mapping was implemented, based on a multi-SNP regression model, which accommodated multiple QTLs simultaneously.
In a last step, multiple interval mapping was performed including all the significant IM QTLs (single and 2 linked QTLs), and threshold was 0.05.
Sophisticated statistical methods such as multiple interval mapping are capable of fitting main and interacting QTL effects simultaneously, and iteratively converging on a best-fitting model.
