Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs

Abstract

The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less than 5 h with an accuracy of 99.4%. An integrative analysis of small RNAs from 1836 data sets (20 billion reads) indicated that context-specific miRNAs (e.g. miRNAs present only in one or few different tissues / cell types) still remain to be discovered while broadly expressed miRNAs appear to be largely known. In total, our analysis of known and novel miRNAs indicated nearly 22 000 candidates of precursors with one or two mature forms. Based on these, we designed a custom microarray comprising 11 872 potential mature miRNAs to assess the quality of our prediction. MiRMaster is a convenient-to-use tool for the comprehensive and fast analysis of miRNA NGS data. In addition, our predicted miRNA candidates provided as custom array will allow researchers to perform in depth validation of candidates interesting to them.

Deep sncRNA-seq of the PPMI cohort to study Parkinson’s disease progression

“…For the PPMI sncRNA-seq evaluation, BCL's were converted to FASTQ using bcltofastq v1.8.4, and FASTQ's were merged and processed with miRMaster v1.0 28 . Adapters with up to an edit distance of 1 and a minimum overlap of 10 nt were trimmed with miRMaster and the 4 random nucleotides at the 5' end of the sequence as well as in front of the adapter were removed.…”

“…The remarkable depth of the sequencing data facilitates calling of novel miRNA candidates. From an initial set of 30, 924 candidates reported by miRMaster 28 , 834 were manifested in a consistently detected readout across the sub-cohorts. For these high-profile candidates we repeated the differential expression analysis (Figure 2f-h).…”

miRSwitch: Detecting microRNA arm shift and switch events

“…To generate a reference map of human arm shift / switch events we collected 38, 252 human sncRNA-seq samples. The data set was compiled from three different sources, the Sequence Read Archive (SRA) [28] (16,415), TCGA [29] (10, 999), and samples that were made accessible by anonymous users of miRMaster [25] and who provided consent for aggregated secondary usage (10,838). Subsequently, we removed duplicated data sets that occurred after pooling the SRA and miRMaster samples.…”

“…To provide further insights into arm shifts in H. sapiens we integrated a reference map of arm shift events in different solid tissues and bio fluids. We collected 38, 252 sncRNA data sets from three different sources (the sequence read archive [28], the cancer genome atlas [29] and data collected by our tool miRMaster [25]). These data sets contain a total of 556 billion sequencing reads and can be annotated for 46 different tissue types.…”

“…An arm switch denotes a more extreme scenario where in one condition either arm is the dominant and vice versa in the other condition. The supported type of input of miRSwitch ranges from expression matrices over result files from common highthroughput tools such as miRDeep2 [24], miRMaster [25], or sRNAbench [26] to prominent data sources like The Cancer Genome Atlas (TCGA). Users can upload annotation files or manually annotate the samples before running an analysis.…”