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MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies.

Kumar P, Halama A, Hayat S, Billing AM, Gupta M, Yousri NA, Smith GM, Suhre K - Biomed Res Int (2015)

Bottom Line: Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA), Biosample, Bioprojects, and Gene Expression Omnibus (GEO).Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study.Here we describe "MetaRNA-Seq," a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

View Article: PubMed Central - PubMed

Affiliation: Weill Cornell Medical College in Qatar, Education City, Doha, Qatar.

ABSTRACT
The number of RNA-Seq studies has grown in recent years. The design of RNA-Seq studies varies from very simple (e.g., two-condition case-control) to very complicated (e.g., time series involving multiple samples at each time point with separate drug treatments). Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA), Biosample, Bioprojects, and Gene Expression Omnibus (GEO). Although the NCBI web interface is able to provide all of the metadata information, it often requires significant effort to retrieve study- or project-level information by traversing through multiple hyperlinks and going to another page. Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study. Here we describe "MetaRNA-Seq," a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

No MeSH data available.


RNA-Seq metadata annotations in MetaRNA-Seq. Suggestions are based on a program-assisted search of all data available for a particular study. Custom annotation fields can be used in cases when the annotator feels that additional information is important and it cannot be stored using default options. The annotator can use as many custom annotation fields as required.
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Related In: Results  -  Collection


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fig2: RNA-Seq metadata annotations in MetaRNA-Seq. Suggestions are based on a program-assisted search of all data available for a particular study. Custom annotation fields can be used in cases when the annotator feels that additional information is important and it cannot be stored using default options. The annotator can use as many custom annotation fields as required.

Mentions: MetaRNA-Seq has a semiautomatic curation capability and provides an easy interface for annotating metadata for RNA-Seq studies, mostly with one mouse click (Figure 2). Categorization of most of the annotation fields is based on their impact and effect on RNA-Seq studies [20–23]. One can intuitively determine that transcript expression profiles in a case-control study involving a rare disease will be very different than a case-control study involving a complex disease. In MetaRNA-Seq, a RNA-Seq study can be annotated for study type, disease category, sample type, replicate type, and custom annotation. Study types are categorized broadly into case-control, time series, and treatment. Sample types are categorized into cell line, primary cells, tissue, blood, and plasma. If some of these fields are present in experiments or biosamples in the selected study, then the assistance is automatically generated with a certain degree of confidence. For example, while annotating a RNA-Seq study with accession “SRP010129,” automatic suggestions of cell line and tissue are provided for the sample types with hint text “Suggestion: Cell Lines - -> Yes: Cell line derived from Merkel Cell Carcinoma (10 samples) Confidence: 25%” and hint text “Suggestion: Tissue - -> Yes: FFPE Merkel Cell Carcinoma (16 samples), FFPE Basal Cell Carcinoma (6), FFPE Normal skin (6), FFPE Squamous Cell Carcinoma (2) Confidence: 40%,” respectively (Figure 2). The automatic hint provision can help annotators perform annotation more quickly in MetaRNA-Seq. Also, study type, sample type, or platform can be selected for multiple types. For example, in a complex RNA-Seq study, the study type can be both case-control and time series, sample types can be both cell line and primary cells, and platforms can be Illumina, Solid, and Roche 454.


MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies.

Kumar P, Halama A, Hayat S, Billing AM, Gupta M, Yousri NA, Smith GM, Suhre K - Biomed Res Int (2015)

RNA-Seq metadata annotations in MetaRNA-Seq. Suggestions are based on a program-assisted search of all data available for a particular study. Custom annotation fields can be used in cases when the annotator feels that additional information is important and it cannot be stored using default options. The annotator can use as many custom annotation fields as required.
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4561952&req=5

fig2: RNA-Seq metadata annotations in MetaRNA-Seq. Suggestions are based on a program-assisted search of all data available for a particular study. Custom annotation fields can be used in cases when the annotator feels that additional information is important and it cannot be stored using default options. The annotator can use as many custom annotation fields as required.
Mentions: MetaRNA-Seq has a semiautomatic curation capability and provides an easy interface for annotating metadata for RNA-Seq studies, mostly with one mouse click (Figure 2). Categorization of most of the annotation fields is based on their impact and effect on RNA-Seq studies [20–23]. One can intuitively determine that transcript expression profiles in a case-control study involving a rare disease will be very different than a case-control study involving a complex disease. In MetaRNA-Seq, a RNA-Seq study can be annotated for study type, disease category, sample type, replicate type, and custom annotation. Study types are categorized broadly into case-control, time series, and treatment. Sample types are categorized into cell line, primary cells, tissue, blood, and plasma. If some of these fields are present in experiments or biosamples in the selected study, then the assistance is automatically generated with a certain degree of confidence. For example, while annotating a RNA-Seq study with accession “SRP010129,” automatic suggestions of cell line and tissue are provided for the sample types with hint text “Suggestion: Cell Lines - -> Yes: Cell line derived from Merkel Cell Carcinoma (10 samples) Confidence: 25%” and hint text “Suggestion: Tissue - -> Yes: FFPE Merkel Cell Carcinoma (16 samples), FFPE Basal Cell Carcinoma (6), FFPE Normal skin (6), FFPE Squamous Cell Carcinoma (2) Confidence: 40%,” respectively (Figure 2). The automatic hint provision can help annotators perform annotation more quickly in MetaRNA-Seq. Also, study type, sample type, or platform can be selected for multiple types. For example, in a complex RNA-Seq study, the study type can be both case-control and time series, sample types can be both cell line and primary cells, and platforms can be Illumina, Solid, and Roche 454.

Bottom Line: Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA), Biosample, Bioprojects, and Gene Expression Omnibus (GEO).Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study.Here we describe "MetaRNA-Seq," a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

View Article: PubMed Central - PubMed

Affiliation: Weill Cornell Medical College in Qatar, Education City, Doha, Qatar.

ABSTRACT
The number of RNA-Seq studies has grown in recent years. The design of RNA-Seq studies varies from very simple (e.g., two-condition case-control) to very complicated (e.g., time series involving multiple samples at each time point with separate drug treatments). Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA), Biosample, Bioprojects, and Gene Expression Omnibus (GEO). Although the NCBI web interface is able to provide all of the metadata information, it often requires significant effort to retrieve study- or project-level information by traversing through multiple hyperlinks and going to another page. Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study. Here we describe "MetaRNA-Seq," a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

No MeSH data available.