1. Trimming and Clustering Sugarcane ESTs Telles, Guilherme P. Silva, Felipe R. da

2. Trimming and Clustering Sugarcane ESTs Overview of pipeline Quality trimming Internal consistency External consistency Telles, Guilherme P. Silva, Felipe R. da

3. Overview of pipeline (I) Ribosomal RNA removal Vector screening Vector and poly-A removal Low quality read removal (291,689 reads) 2,9 % 2,7 % 0,6 %

4. Overview of pipeline (II) Terminal vector trimming Slipped read removal Terminal poly-A removal Short read removal (273,728 reads) 5,4 % 0,7 % 6,2 % (237,954 reads)

5. Quality trimming Based on: sliding window of 20 bases stop when < X bases have quality < Y Used selected reads with good BLAST hits Selected parameters where BLAST hit end correlates well with trimming point

6. Internal consistency In a good clustering, each read should align well with its consensus

7. External consistency In a good clustering, the consensi of distinct clusters should not exhibit overlap similarity

8. Final results Careful trimming is essential CAP3 tool of choice for clustering 43,141 clusters