The Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework

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Abstract

Inflammatory bowel disease (IBD) is a class of chronic disorders whose etiogenesis is still unknown. Despite the high number of IBD-related omics studies, the RNA-sequencing data produced results that are hard to compare because of the experimental variability and different data analysis approaches. We here introduce the IBD Transcriptome and Metatranscriptome Meta-Analysis (TaMMA) framework, a comprehensive survey of publicly available IBD RNA-sequencing datasets. IBD TaMMA is an open-source platform where scientists can explore simultaneously the freely available IBD-associated transcriptomics and microbial profiles thanks to its interactive interface, resulting in a useful tool to the IBD community.

Abstract

Massimino et al. propose the Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework, an open-source platform for expediting the investigation of IBD-specific transcriptomics and metatranscriptomics signatures.

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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Trimmomatic: a flexible trimmer for Illumina sequence data

Anthony M. Bolger, Marc Lohse, Bjoern Usadel (2014)

Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.

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STAR: ultrafast universal RNA-seq aligner.

Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)

Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

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Author and article information

Contributors

Luca Massimino:

ORCID: http://orcid.org/0000-0003-3975-9148

admin@lucamassimino.com

Federica Ungaro:

ORCID: http://orcid.org/0000-0001-5395-7795

federica.ungaro@humanitasresearch.it

Journal

Journal ID (nlm-ta): Nat Comput Sci

Journal ID (iso-abbrev): Nat Comput Sci

Title: Nature Computational Science

Publisher: Nature Publishing Group US (New York )

ISSN (Electronic): 2662-8457

Publication date (Electronic): 20 August 2021

Publication date PMC-release: 20 August 2021

Publication date (Print): 2021

Volume: 1

Issue: 8

Pages: 511-515

Affiliations

[1 ]GRID grid.452490.e, Department of Biomedical Sciences, , Humanitas University, ; Pieve Emanuele, Milan Italy

[2 ]GRID grid.417728.f, ISNI 0000 0004 1756 8807, IBD Center, , IRCCS Humanitas Research Hospital, ; Rozzano, Milan Italy

[3 ]PhoenixLAB, Lodi, Italy

[4 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, Inserm NGERE, , University of Lorraine, ; Vandoeuvre-les-Nancy, France

[5 ]GRID grid.410527.5, ISNI 0000 0004 1765 1301, Nancy University Hospital, ; Vandoeuvre-les-Nancy, France

Author information

Luca Massimino http://orcid.org/0000-0003-3975-9148

Luigi Antonio Lamparelli http://orcid.org/0000-0002-9571-2582

Federica Ungaro http://orcid.org/0000-0001-5395-7795

Article

Publisher ID: 114

DOI: 10.1038/s43588-021-00114-y

PMC ID: 10766544

SO-VID: 15eeff23-3e08-48c0-a46b-d2dee544b9d5

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 30 April 2021

Date accepted : 16 July 2021

Funding

Funded by: FundRef https://doi.org/10.13039/501100010767, Innovative Medicines Initiative (IMI);

Award ID: 853995 to SV

Award ID: 853995 to SD

Award Recipient : Stefania Vetrano Silvio Danese

Funded by: FundRef https://doi.org/10.13039/501100002803, Fondazione Cariplo (Cariplo Foundation);

Award ID: 2018-0112 to FU

Funded by: Fondazione Amici ONLUS ITALIA, research prize to FU

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Keywords: inflammatory bowel disease,computational platforms and environments,rna sequencing

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Keywords: inflammatory bowel disease, computational platforms and environments, rna sequencing

The Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework

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Most cited references 32

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Trimmomatic: a flexible trimmer for Illumina sequence data

STAR: ultrafast universal RNA-seq aligner.

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