Literature DB >> 33396959

DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification.

Athanasios Alexiou1,2, Dimitrios Zisis2, Ioannis Kavakiotis1, Marios Miliotis1,2, Antonis Koussounadis3, Dimitra Karagkouni1,2, Artemis G Hatzigeorgiou1,2,3.   

Abstract

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.

Entities:  

Keywords:  NGS; analysis; bioinformatics; expression; microRNA; pipeline; quantification; small RNA-Seq

Mesh:

Substances:

Year:  2020        PMID: 33396959      PMCID: PMC7823405          DOI: 10.3390/genes12010046

Source DB:  PubMed          Journal:  Genes (Basel)        ISSN: 2073-4425            Impact factor:   4.096


  28 in total

1.  Deep sequencing of the small RNA transcriptome of normal and malignant human B cells identifies hundreds of novel microRNAs.

Authors:  Dereje D Jima; Jenny Zhang; Cassandra Jacobs; Kristy L Richards; Cherie H Dunphy; William W L Choi; Wing Yan Au; Gopesh Srivastava; Magdalena B Czader; David A Rizzieri; Anand S Lagoo; Patricia L Lugar; Karen P Mann; Christopher R Flowers; Leon Bernal-Mizrachi; Kikkeri N Naresh; Andrew M Evens; Leo I Gordon; Micah Luftig; Daphne R Friedman; J Brice Weinberg; Michael A Thompson; Javed I Gill; Qingquan Liu; Tam How; Vladimir Grubor; Yuan Gao; Amee Patel; Han Wu; Jun Zhu; Gerard C Blobe; Peter E Lipsky; Amy Chadburn; Sandeep S Dave
Journal:  Blood       Date:  2010-08-23       Impact factor: 22.113

2.  Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown.

Authors:  Mihaela Pertea; Daehwan Kim; Geo M Pertea; Jeffrey T Leek; Steven L Salzberg
Journal:  Nat Protoc       Date:  2016-08-11       Impact factor: 13.491

3.  Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.

Authors:  Ben Langmead; Cole Trapnell; Mihai Pop; Steven L Salzberg
Journal:  Genome Biol       Date:  2009-03-04       Impact factor: 13.583

4.  miRBase: integrating microRNA annotation and deep-sequencing data.

Authors:  Ana Kozomara; Sam Griffiths-Jones
Journal:  Nucleic Acids Res       Date:  2010-10-30       Impact factor: 16.971

5.  DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data.

Authors:  Junko Tsuji; Zhiping Weng
Journal:  PLoS One       Date:  2016-10-13       Impact factor: 3.240

6.  QuickMIRSeq: a pipeline for quick and accurate quantification of both known miRNAs and isomiRs by jointly processing multiple samples from microRNA sequencing.

Authors:  Shanrong Zhao; William Gordon; Sarah Du; Chi Zhang; Wen He; Li Xi; Sachin Mathur; Michael Agostino; Theresa Paradis; David von Schack; Michael Vincent; Baohong Zhang
Journal:  BMC Bioinformatics       Date:  2017-03-20       Impact factor: 3.169

7.  Kraken: a set of tools for quality control and analysis of high-throughput sequence data.

Authors:  Matthew P A Davis; Stijn van Dongen; Cei Abreu-Goodger; Nenad Bartonicek; Anton J Enright
Journal:  Methods       Date:  2013-06-29       Impact factor: 3.608

8.  CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data.

Authors:  Zhifu Sun; Jared Evans; Aditya Bhagwate; Sumit Middha; Matthew Bockol; Huihuang Yan; Jean-Pierre Kocher
Journal:  BMC Genomics       Date:  2014-06-03       Impact factor: 3.969

9.  Manatee: detection and quantification of small non-coding RNAs from next-generation sequencing data.

Authors:  Ioannis S Vlachos; Artemis G Hatzigeorgiou; Joanna E Handzlik; Spyros Tastsoglou
Journal:  Sci Rep       Date:  2020-01-20       Impact factor: 4.379

10.  Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia.

Authors:  Carme Camps; Harpreet K Saini; David R Mole; Hani Choudhry; Martin Reczko; José Afonso Guerra-Assunção; Ya-Min Tian; Francesca M Buffa; Adrian L Harris; Artemis G Hatzigeorgiou; Anton J Enright; Jiannis Ragoussis
Journal:  Mol Cancer       Date:  2014-02-11       Impact factor: 27.401

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  4 in total

Review 1.  Technological Approaches in the Analysis of Extracellular Vesicle Nucleotide Sequences.

Authors:  Tine Tesovnik; Barbara Jenko Bizjan; Robert Šket; Maruša Debeljak; Tadej Battelino; Jernej Kovač
Journal:  Front Bioeng Biotechnol       Date:  2021-12-23

2.  DIANA-miTED: a microRNA tissue expression database.

Authors:  Ioannis Kavakiotis; Athanasios Alexiou; Spyros Tastsoglou; Ioannis S Vlachos; Artemis G Hatzigeorgiou
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

3.  A Bioinformatics Approach to MicroRNA-Sequencing Analysis Based on Human Saliva Samples of Patients with Endometriosis.

Authors:  Sofiane Bendifallah; Yohann Dabi; Stéphane Suisse; Ludmila Jornea; Delphine Bouteiller; Cyril Touboul; Anne Puchar; Emile Daraï
Journal:  Int J Mol Sci       Date:  2022-07-21       Impact factor: 6.208

Review 4.  miRNA in Molecular Diagnostics.

Authors:  Maja Matulić; Paula Gršković; Andreja Petrović; Valerija Begić; Suzana Harabajsa; Petra Korać
Journal:  Bioengineering (Basel)       Date:  2022-09-09
  4 in total

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