Researchers from China and the US introduce an online tool for taking a look at transcription factor-DNA binding intensities in different cell types, along with the variants that affect them. The approach — known as "deep learning-based functional impact of non-coding variants evaluator," or DeFine — uses deep learning models to tease out transcription factor binding intensities and non-coding SNP impacts on these binding events based on chromatin immunoprecipitation sequencing data. The authors note that the strategy "accurately identifies the causal functional non-coding variants from disease-associated variants in GWAS," and is "an effective and easy-to-use tool" for prioritizing non-coding variants with potential functional roles.
A University of Queensland team describes GraftM, an open-source algorithm for classifying metagenomic sequence data using open reading frame data, gene family data, and phylogenetic relationships between organisms. After standardizing GraftM using in silico and in vitro metagenomic community data, the researchers applied it to 16S ribosomal RNA profiles and other data for wetland microbe communities, demonstrating that it could pick up new phylum-level sequence patterns. "Using conserved and metabolic markers," the study's authors say, "we demonstrate that GraftM outperforms similar tools in terms of runtime, search sensitivity, and classification accuracy."
Finally, University of California, Santa Cruz, researchers present a single-cell RNA sequencing method called Tn5Prime — a Smart-seq2 protocol that includes a Tn5 transposase-based 5'-capture step. "The Tn5Prime method dramatically streamlines the 5' capture process and is both cost effective and reliable," according to investigators, who applied the approach to both bulk RNA and individual cells — primary mouse B lymphocytes or human immune B cells isolated by peripheral blood mononuclear cell sorting — to generate quantifiable transcriptome data that included transcription start sites as well as assemblies for antibody light and heavy chains.