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Fig. 1 | BMC Bioinformatics

Fig. 1

From: TERIUS: accurate prediction of lncRNA via high-throughput sequencing data representing RNA-binding protein association

Fig. 1

Two-step schematic flow of TERIUS. In RPS, ribosome reads are mapped to transcripts and converted to sub-codon position signals. Then the signals are shifted to find the most-likely coding frame and adjusted before weighted relative entropy was calculated for ncRNA (gold) and mRNA (purple) sets. Resulting distribution was estimated to generate a model (x axis: WRE, y axis: density). Transcripts predicted as coding are classified as mRNA while ncRNA and low ribosome transcripts (LRT) are passed on to the second step, where they are further classified as bona fide lncRNAs or 3’UTR fragments depending on their association to UPF1. UAS classification is also based on density model. X axis represents UPF1 CLIP-seq RPM divided by RNA-seq RPM in log scale and y axis is density. The bar colored in yellow and purple in the left represents the fraction of transcripts without UPF1 association

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BMC Bioinformatics

ISSN: 1471-2105

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