Sentence examples for quality tags from inspiring English sources

When taken separately, the personomy should generate worst quality tags comparing to the Web resource, which should generate worst quality tags when compared to the folksonomy.

After removing the adaptor/acceptor sequences, filtering the low quality tags and cleaning up the contamination formed by the adaptor-adaptor ligation, the occurrences of each unique sequence reads was counted as sequence tags.

After eliminating low quality tags (containing Ns), copy numbers less than 2 and adaptor sequences, the numbers of total clean tags were about 3.57, 3.54, 3.55 and 3.45 millions for eggs, larvae, pupae and adults, respectively.

After removing adaptor/acceptor sequences, filtering out low quality tags and cleaning up the contamination formed by the adaptor-adaptor ligation, 9,738,608 (64.84%) clean reads were obtained, representing 3,425,015 unique sequences.

After filtering the low quality tags, the total number of clean tags in each library ranged from 2.4 to 3.2 million (Table 1), and the percentage of clean tags among the raw tags in each library ranged from 86.67 to 91.53% (Fig. 4).

To map the DGE tags, the sequenced raw data were filtered to remove low quality tags (tags with unknown nucleotide "N"), empty tags (no tag sequence between the adaptors) and tags with only one copy number (which might result from sequencing errors).

The six DGE libraries were sequenced and generated 5.6 5.9 million high-quality tags.

Adaptor sequences and low-quality tags were removed to detect known and novel miRNAs in tomato.

The clean tags are tags that remained after filtering out dirty (low-quality) tags from the raw data.

"Clean Tags" were obtained by filtering off adaptor-only tags and low-quality tags (containing ambiguous bases).

Adaptor sequences were removed by custom PERL scripts and low-quality tags with ambiguous nucleotide(s) were discarded.