Background
Full-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short.
Results
Here we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control.
Conclusions
Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.
We present a novel electrical technique to measure the tension of wires in multi-wire drift chambers. We create alternating electric fields by biasing adjacent wires on both sides of a test wire with a superposition of positive and negative DC voltages on an AC signal (V AC ± V DC ). The resulting oscillations of the wire will display a resonance at its natural frequency, and the corresponding change of the capacitance will lead to a measurable current. This scheme is scalable to multiple wires and therefore enables us to precisely measure the tension of a large number of wires in a short time. This technique can also be applied at cryogenic temperatures making it an attractive solution for future large time-projection chambers such as the DUNE detector. We present the concept, an example implementation and its performance in a real-world scenario and discuss the limitations of the sensitivity of the system in terms of voltage and wire length.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.