Various research groups have conducted spiking experiments and have developed their own peak libraries.
On average, we identified 10,000 - 11,000 genes with a high confidence TSS peak per library in experiments 1 and 3, as compared to 13,000 genes in experiment 2 (Table 1).
Since the charge states of the explained peaks in library spectra are already known, the mass shifts could be accurately determined.
The spectral dot-product score (SDP_Score) is calculated as: (1) where I L and I Q denote the intensities of the library peak and the query peak, respectively.
In this library, peak-to-peak amplitudes and root-mean-square (RMS) noise is calculated using established methods.
The identification of metabolites was confirmed by comparing spectrum and retention index of given peak with chemical library standards.
Interestingly, we did detect the P28 peak in a library constructed from Miwi protein immunoprecipitate [ 24], suggesting that 19-mers may associate with Miwi (Additional file 4A).
Briefly, the number of reads per million (RPM) was calculated for each peak in one library of our data set, and this number was compared to the RPM of the corresponding peak in a separate library using a Spearman's rank correlation analysis.
However, common features in both libraries (peak at 27nt, 5′-G bias, and mapping antisense to genes) suggested that EhAGO2-2 bound species are represented in the Rahman library.
However, there is at present no standard method for peak identification, and no library of chemical shifts of P forms analyzed under standardized, easily replicated conditions.
