SUMMARY: MicroRNAs (miRNAs) are master regulators of gene expression in cancers. Their sequence variants or isoforms (isomiRs) are highly abundant and possess unique functions. Given their short sequence length and high heterogeneity, mapping isomiRs can be challenging; without adequate depth and data aggregation, low frequency events are often disregarded. To address these challenges, we present the Tumor IsomiR Encyclopedia (TIE): a dynamic database of isomiRs from over 10 000 adult and pediatric tumor samples in The Cancer Genome Atlas (TCGA) and The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) projects. A key novelty of TIE is its ability to annotate heterogeneous isomiR sequences and aggregate the variants obtained across all datasets. Results can be browsed online or downloaded as spreadsheets. Here, we show analysis of isomiRs of miR-21 and miR-30a to demonstrate the utility of TIE. AVAILABILITY AND IMPLEMENTATION: TIE search engine and data are freely available to use at https://isomir.ccr.cancer.gov/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: MicroRNAs (miRNAs) are small RNA molecules (∼22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, the diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods. RESULTS: To overcome this situation, we present here a community-based project, miRNA Transcriptomic Open Project (miRTOP) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream isomiR analysis tools that are compatible with existing detection and quantification tools. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to create and manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, isomiR-SEA, sRNAbench, Prost! as well as BAM files. Some tools have also incorporated the mirGFF3 format directly into their code, such as, miRge2.0, IsoMIRmap and OptimiR. Its open architecture enables any tool or pipeline to output or convert results into mirGFF3. Collectively, this isomiR categorization system, along with the accompanying mirGFF3 and mirtop API, provide a comprehensive solution for the standardization of miRNA and isomiR annotation, enabling data sharing, reporting, comparative analyses and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps of miRNA detection, annotation and quantification. AVAILABILITY AND IMPLEMENTATION: https://github.com/miRTop/mirGFF3/ and https://github.com/miRTop/mirtop. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: MicroRNAs (miRNAs) function as master regulators of gene expression. Recent studies demonstrate that miRNA isoforms (isomiRs) play a unique role in cancer development. Here, we present QuagmiR, the first cloud-based tool to analyze isomiRs from next generation sequencing data. Using a novel and flexible searching algorithm designed for the detection and annotation of heterogeneous isomiRs, it permits extensive customization of the query process and reference databases to meet the user 's diverse research needs. AVAILABILITY AND IMPLEMENTATION: QuagmiR is written in Python and can be obtained freely from GitHub (https://github.com/Gu-Lab-RBL-NCI/QuagmiR). QuagmiR can be run from the command line on local machines, as well as on high-performance servers. A web-accessible version of the tool has also been made available for use by academic researchers through the National Cancer Institute-funded Seven Bridges Cancer Genomics Cloud (https://cancergenomicscloud.org). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.