Researchers from Thomas Jefferson University present “Threshold-seq,” a new approach for determining thresholds in deep-sequencing datasets of short RNA transcripts. Threshold-seq addresses the critical question of how many reads need to support a short RNA molecule in a given dataset before it can be considered different from “background.” The proposed scheme is easy to implement and incorporate into existing pipelines.
Comparison of Threshold-seq with arbitrary RPM thresholds
The shown five samples were sequenced in seven technical replicates. In each case, we plot the obtained sensitivity (X-axis) vs. the obtained specificity (Y-axis) for different RPMM thresholds from 0.5 to 5 in increments of 0.5. Dark circles show the Threshold-seq equivalent metrics in each case.
Implementation and Availability: Source code of Threshold-seq is freely available as an R package at: http://cm.jefferson.edu/threshold-seq/.