Establishment of a read-count cutoff for accurate fold-change assessment
In RNA-Seq experiments, pre-filtering genes with low read counts to reduce low-quality data is an important part of the analysis but is frequently done using arbitrarily defined thresholds. As we have shown in Determination of empirical minimum expression cutoffs using ERCC spike-ins. Each dot represents a subset of the 92 ERCC1 and ERCC2 transcripts for one paired sample grouped by average ERCC1 and ERCC2 abundance (on average 13 per abundance bin). The y-axis summarizes the Spearman correlation between the empirical logIn this section, we highlighted a new algorithm that utilizes internal ERCC spike-ins for determining an optimal read-count threshold for each dataset independently. The 