Common File Formats

Leonard, Shonda A.; Littlejohn, Timothy G.

doi:10.1002/0471250953.bia01bs05

Cited by 4 publications

(8 citation statements)

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“…For example, in meta-analysis of sequences an established and unified file standard is crucial (Ten Hoopen et al, 2017). FASTA (Pearson & Lipman, 1988), FASTQ (Cock et al, 2010), and SAM/BAM (Li et al, 2009) are famous examples of file standards that have allowed the effective exchange of information between numerous groups involved in the earliest sequencing projects (Leonard & Littlejohn, 2004;Ondřej & Dvořák, 2012;Zhang, 2016). Any disparities in the sampling method also have to be taken into account when biological material is concerned, so it is essential they are recorded appropriately (Ten Hoopen et al, 2017).…”

Section: Comparison and Integration Of Datasets And Databasesmentioning

confidence: 99%

The reuse of public datasets in the life sciences: potential risks and rewards

Sielemann

Hafner

Pucker

2020

PeerJ

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The ‘big data’ revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define ‘successful reuse’ as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.

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Section: Comparison and Integration Of Datasets And Databasesmentioning

confidence: 99%

The reuse of public datasets in the life sciences: potential risks and rewards

Sielemann

Hafner

Pucker

2020

PeerJ

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“…1. Run geneid on the first example (example1.fa) with default options: geneid -P param/human3iso.param samples/example1.fa geneid is a Unix command-line program that requires as input a file containing a DNA sequence in FASTA format (samples/example1.fa; see Leonard & Littlejohn, 2004, for discussion of FASTA format), and a parameter file. This is specified by using the option -P followed by the name of the parameter file.…”

Section: Geneid -Hmentioning

confidence: 99%

“…Users must input a DNA sequence in FASTA format (Leonard & Littlejohn, 2004) either from file or from the text area, while the external information in GFF format is optional. The process for building a graphical representation from the geneid output with the program Alioto et al…”

Section: Filesmentioning

confidence: 99%

“…After the set of lines corresponding to the exons of the predicted gene, the amino acid sequence of the gene is printed in FASTA format (Leonard & Littlejohn, 2004). In addition to the predicted genes, geneid provides a number of options that allow the investigator to print an exhaustive list of all the sequence signals and exons predicted along the query sequence (most of which are not included in the final gene prediction).…”

Section: Fields a Descriptionmentioning

confidence: 99%

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Using geneid to Identify Genes

Alioto

Blanco

Parra

et al. 2018

CP in Bioinformatics

123

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This unit describes the usage of geneid, an efficient gene‐finding program that allows for the analysis of large genomic sequences, including whole mammalian chromosomes. These sequences can be partially annotated, and geneid can be used to refine this initial annotation. Training geneid is relatively easy, and parameter configurations exist for a number of eukaryotic species. geneid produces output in a variety of standard formats. The results, thus, can be processed by a variety of software tools, including visualization programs. geneid software is in the public domain, and is undergoing constant development. It is easy to install and use. Exhaustive benchmark evaluations show that geneid compares favorably with other existing gene‐finding tools. © 2018 by John Wiley & Sons, Inc.

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“…GFF or PTT) (Leonard et al , 2007). It is also possible to open multiple FASTA files or raw sequence data, and there is an option for downloading sequence information from the NCBI web site http://www.ncbi.nlm.nih.gov/.…”

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confidence: 99%

DiProGB: the dinucleotide properties genome browser

et al. 2009

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Motivation: DiProGB is an easy to use new genome browser that encodes the primary nucleotide sequence by thermodynamical and geometrical dinucleotide properties. The nucleotide sequence is thus converted into a sequence graph. This visualization, supported by different graph manipulation options, facilitates genome analyses, because the human brain can process visual information better than textual information. Also, DiProGB can identify genomic regions where certain physical properties are more conserved than the nucleotide sequence itself. Most of the DiProGB tools can be applied to both, the primary nucleotide sequence and the sequence graph. They include motif and repeat searches as well as statistical analyses. DiProGB adds a new dimension to the common genome analysis approaches by taking into account the physical properties of DNA and RNA.Availability and Implementation: Source code and binaries are freely available for download at http://diprogb.fli-leibniz.de, implemented in C++ and supported on MS Windows and Linux (using e.g. WineHQ).Contact: maikfr@fli-leibniz.de; thomas.wilhelm@bbsrc.ac.uk

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Common File Formats

Cited by 4 publications

References 0 publications

The reuse of public datasets in the life sciences: potential risks and rewards

The reuse of public datasets in the life sciences: potential risks and rewards

Using geneid to Identify Genes

DiProGB: the dinucleotide properties genome browser

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