The computer experiments of error correction of artificially generated sequences supported the effectiveness of our method, showing that 50 90% of errors were removed.
About 50% of the estimation errors were removed after applying the deconvolution method and aggregating derived proportion images to twice their dimensional pixel size.
Sequences with unusual insertions and/or deletions, stemming most likely from gene prediction errors, were removed, as were sequences that aligned very poorly (e.g. some protozoan parasite sequences).
The obtained results present an important improvement when the systematic errors are removed from the SLP fields, since the differences in the circulation types frequency between the models and the reanalysis are lower when compared to the results without the SLP corrections.
Identified errors were removed before analysis.
SNPs demonstrating Mendelian errors were removed.
Markers with suspected errors were removed from subsequent analyses.
The markers with Mendelian errors were removed from further analysis.
Finally, the QMTs were grouped and artifactual ±1 Da deisotoping errors were removed.
The flagged values were then manually evaluated and data entry errors were removed as indicated.
