Common File Formats

Leonard, Shonda A.; Littlejohn, Timothy G.; Baxevanis, Andreas D.

doi:10.1002/0471250953.bia01bs16

Cited by 14 publications

(9 citation statements)

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“…The 16S-rRNA gene sequence fasta files (the standard text based format for representing nucleotide sequence [ 37 , 38 ]) and quality data were extracted from the SFF files generated by the 454 Titanium sequencer (MR DNA, Shallowater, TX USA). Average read length before trimming and quality control was 405 bp.…”

Section: S-rdna Bacterial Community Analysismentioning

confidence: 99%

Microbial communities and inflammatory response in the endometrium differ between normal and metritic dairy cows at 5–10 days post-partum

Sicsic

Goshen

Dutta

et al. 2018

Vet Res

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Post-partum metritis is among the most prevalent disease in dairy cows affecting animal welfare and inflicting considerable economic loses. While post-partum contamination of the uterus is rife in dairy cows, only a fraction of these animals will develop metritis. Our main objective was to compare the bacterial communities and the inflammatory response in the endometrium of healthy and metritic dairy cows. Holstein–Friesian cows (n = 35) were sampled immediately following clinical classification as healthy (n = 21), suffering from metritis (n = 13) or septic metritis (n = 1), based on veterinary examination at 5–10 days post-partum. Polymorphonuclear cells (PMN) percentage in endometrial cytology was significantly higher in cows with metritis. Full-thickness uterine biopsy analysis revealed that the luminal epithelium in inter-caruncle areas was preserved in healthy cows, but in metritis it was compromised, with marked PMN infiltration particularly in the apical endometrium. Gram staining revealed that bacterial load and spatial distribution was associated with disease severity. 16S-rDNA bacterial community analysis revealed unique endometrial bacterial community composition in metritic cows, as compared to more diverse communities among healthy cows. The most abundant phyla in healthy cows were Proteobacteria (31.8 ± 9.3%), Firmicutes (27.9 ± 8.4%) and Bacteroidetes (19.7 ± 7.2%), while Bacteroidetes (60.3 ± 10.3%), Fusobacteria (13.4 ± 5.9%) and Firmicutes (10.5 ± 3.3%) were most abundant in the endometrial mucosa of metritic cows. Relative abundance of Bacteroidetes (19.7 ± 7.2% vs. 60.3 ± 10.3%), Fusobacteria (7.5 ± 5.2% vs. 13.4 ± 5.9%) and Proteobacteria (31.8 ± 9.3% vs. 7.3 ± 5.6%) phyla differed significantly between healthy and metritic cows. In summary, endometrial PMN abundance, spatial distribution and bacterial communities differed between healthy and metritic dairy cows at early post-partum.Electronic supplementary materialThe online version of this article (10.1186/s13567-018-0570-6) contains supplementary material, which is available to authorized users.

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Section: S-rdna Bacterial Community Analysismentioning

confidence: 99%

Microbial communities and inflammatory response in the endometrium differ between normal and metritic dairy cows at 5–10 days post-partum

Sicsic

Goshen

Dutta

et al. 2018

Vet Res

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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: Challenges Limitations and Risks Of Data Reuse And Possiblementioning

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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“…For any valid comparison between datasets from different databases or for integration of databases themselves, an established and unified file standard is crucial. FASTA (36), FASTQ (37), and SAM/BAM (38) are famous examples of file standards that allowed effective exchange of information between numerous groups involved in the earliest sequencing projects (39)(40)(41).…”

Section: Comparison and Integration Of Different Databasesmentioning

confidence: 99%

The Reuse of Public Datasets in the Life Sciences: Potential Risks and Rewards

Sielemann

Hafner

Pucker

2020

Preprint

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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 challenges, limitations and risks associated with it. Due to the prominence, abundance and wide distribution of sequencing results, we focus on the reuse of publicly available sequence datasets. Through selected examples of successful reuse of different data (genome, transcriptome, proteome, metabolome, phenotype and ecosystem), with their respective limitations and risks, we illustrate the enormous potential of the practice. A checklist to determine the reuse value and potential of particular dataset is also provided.

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Common File Formats

Cited by 14 publications

References 0 publications

Microbial communities and inflammatory response in the endometrium differ between normal and metritic dairy cows at 5–10 days post-partum

Microbial communities and inflammatory response in the endometrium differ between normal and metritic dairy cows at 5–10 days post-partum

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

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