Sentence examples for using the decoy database from inspiring English sources

The false-positive rate for protein identification was <1% and <5% at the peptide level, as determined using the decoy database strategy.

A set of criteria considering the cross correlation score (Xcorr) and delta correlation (ΔCn) values along with tryptic cleavage and charge states were developed using the decoy database approach and applied for filtering the raw data to limit false positive identifications to <1% at the peptide level[23] [25].

Data filtering criteria based on the cross correlation score (Xcorr) and delta correlation (ΔCn) values along with tryptic cleavage and charge states were developed using the decoy database approach and applied for filtering the raw data to limit false positive identifications to <1% at the peptide level [22] [24].

Identified peptides were subjected to a 1%% false discovery rate (FDR) filter using the decoy database method.

In addition, a false discovery rate (FDR) threshold of 0.01 (using the decoy database approach) was applied at both peptide and protein levels.

The E-value threshold for each search was calculated for a 1% FDR using the decoy database search according to Kall et al.[ 47].

FDR was calculated as D/R × 100%, where D and R are the number of matches above identity threshold using the decoy and real databases, respectively.

Furthermore, randomized versions of the applied databases were appended to the original databases using the decoy perl script (Matrix Science, Boston, USA) downloadable at.

A repeated search against a randomized decoy database (http://www.matrixscience.com/help/decoy_help.html) using the decoy.pl script and identical search parameters let to a false-positive rate of 1.2%.

The false-positive rate for protein identification was estimated using the appropriate decoy database as below 1%.

A total false positive rate of 0.8%and0.2%2% for identification of peptide and polypeptide, respectively, was estimated using the reverse decoy database.