Supplementary data are available at Bioinformatics online.

Small RNA (sRNA) Sequencing technology has revealed that microRNAs (miRNAs) are capable of exhibiting frequent variations from their canonical sequences, generating multiple variants: the isoforms of miRNAs (isomiRs). However, integrated tool to precisely detect and systematically annotate isomiRs from sRNA sequencing data is still in great demand. Here, we present an online tool, DeAnnIso (Detection and Annotation of IsomiRs from sRNA sequencing data). DeAnnIso can detect all the isomiRs in an uploaded sample, and can extract the differentially expressing isomiRs from paired or multiple samples. Once the isomiRs detection is accomplished, detailed annotation information, including isomiRs expression, isomiRs classification, SNPs in miRNAs and tissue specific isomiR expression are provided to users. Furthermore, DeAnnIso provides a comprehensive module of target analysis and enrichment analysis for the selected isomiRs. Taken together, DeAnnIso is convenient for users to screen for isomiRs of their interest and useful for further functional studies. The server is implemented in PHP + Perl + R and available to all users for free at: http://mcg.ustc.edu.cn/bsc/deanniso/ and http://mcg2.ustc.edu.cn/bsc/deanniso/.

SummaryNext-generation sequencing has been widely applied to understand the complexity of non-coding RNAs (ncRNAs) in the last decades. Here, we present CPSS 2.0, an updated version of CPSS 1.0 for small RNA sequencing data analysis, with the following improvements: (i) a substantial increase of supported species from 10 to 48; (ii) improved strategies applied to detect ncRNAs; (iii) more ncRNAs can be detected and profiled, such as lncRNA and circRNA; (iv) identification of differentially expressed ncRNAs among multiple samples; (v) enhanced visualization interface containing graphs and charts in detailed analysis results. The new version of CPSS is an efficient bioinformatics tool for users in non-coding RNA research.Availability and implementationCPSS 2.0 is implemented in PHP + Perl + R and can be freely accessed at http://114.214.166.79/cpss2.0/.Supplementary information Supplementary data are available at Bioinformatics online.

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Non-syndromic orofacial clefts (NSOC), which include cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO), are common congenital birth defects in humans. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) and microRNAs (miRNAs or miRs) play important roles in NSOC; however, the potential regulatory associations between them remain largely unknown. In this study, we performed next-generation RNA sequencing (RNA-seq) to identify transcriptome profiles, including mRNAs, lncRNAs and miRNAs, in patients with CL/P and CPO. A total of 36 lncRNAs, 1,341 mRNAs and 60 miRNAs were found to be differentially expressed in the CL/P group compared to the control group, and 57 lncRNAs, 1,255 mRNAs and 162 miRNAs were found to be differentially expressed in the CPO group compared to the control group. Subsequently, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to validate the expression of selected lncRNAs, miRNAs and mRNAs. In addition, bioinformatics methods were employed to explore the potential functions of ncRNAs and to construct lncRNA-miRNA-mRNA regulatory networks. To the best of our knowledge, this is the first study to comprehensively analyze regulated non-coding RNAs (ncRNAs) in CL/P and CPO, providing a novel perspective on the etiology of NSOC and laying the foundation for future research into the potential regulatory mechanisms of ncRNAs and mRNAs in NSOC.

BackgroundCopy number variations (CNVs) are the main genetic structural variations in cancer genome. Detecting CNVs in genetic exome region is efficient and cost-effective in identifying cancer associated genes. Many tools had been developed accordingly and yet these tools lack of reliability because of high false negative rate, which is intrinsically caused by genome exonic bias.ResultsTo provide an alternative option, here, we report Anaconda, a comprehensive pipeline that allows flexible integration of multiple CNV-calling methods and systematic annotation of CNVs in analyzing WES data. Just by one command, Anaconda can generate CNV detection result by up to four CNV detecting tools. Associated with comprehensive annotation analysis of genes involved in shared CNV regions, Anaconda is able to deliver a more reliable and useful report in assistance with CNV-associate cancer researches.ConclusionAnaconda package and manual can be freely accessed at http://mcg.ustc.edu.cn/bsc/ANACONDA/.Electronic supplementary materialThe online version of this article (10.1186/s12859-017-1833-3) contains supplementary material, which is available to authorized users.

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