Bioinformatics and Genomics

Article commentary

Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds further light on metabolic potential of the Methanomassiliicoccales

Editor rating: 7 / 10

Peter Dunfield –– Will specificaly interest those working on methanogenesis, but more broadly the technical novelty may appeal to many microbial ecologists interested in mining metagenomic datases.
Exome sequencing study of 20 patients with high myopia

Editor rating: 7 / 10

Yong Wang –– This paper performed exom sequencing to study high myopia and identified several potential disease genes. The data and analysis provides a valuable resources for the field.
Plant data visualisation using network graphs

Editor rating: 7 / 10

Massimiliano Zanin –– An interesting demonstration on how data can be represented using new web-based technologies.
A minimal set of internal control genes for gene expression studies in head and neck squamous cell carcinoma

Section Editor rating: 7 / 10

Elena Papaleo –– An interesting solution to identify a subset of reference genes for qualitative qPCR of cancer samples
Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches

Editor rating: 7 / 10

Jun Chen –– The article provides a timely and informative comparison of the state-of-the-art error-correction pipelines. The presented results can guide the selection of appropriate pipelines that suit the research needs.
The Oyster River Protocol: a multi-assembler and kmer approach for de novo transcriptome assembly

Section Editor rating: 7 / 10

Keith Crandall –– De novo transcriptome assembly is a complex and difficult problem without a solid solution that works well across species. This helps move the needle in the right direction.
Detection and benchmarking of somatic mutations in cancer genomes using RNA-seq data

Editor rating: 7 / 10

Elena Papaleo –– An interesting read for the cancer biology and computational biology community on the usage of RNASeq to study somatic mutations.
Venomix: a simple bioinformatic pipeline for identifying and characterizing toxin gene candidates from transcriptomic data

Section Editor rating: 7 / 10

Keith Crandall –– This is a novel bioinformatic pipeline to find toxin genes from transcriptome data that looks to be broadly applicable across organisms.
Rapid multi-locus sequence typing direct from uncorrected long reads using Krocus

Section Editor rating: 7 / 10

Keith Crandall –– Krocus looks like a great piece of software now extended for long-read sequencing technology to identify MLST schemes.
Integrated analysis of differentially expressed profiles and construction of a competing endogenous long non-coding RNA network in renal cell carcinoma

Editor rating: 9 / 10

Min Zhao –– This is a good example to integrate data for lncRNAs in a specific cancer type.

Discussing these articles

Nice approach for using large-scale mining of specific genes to identify novel lineages of important metabolic genes https://t.co/Edf2AMrCCh via @thePeerJ

Plant data visualisation using network graphs https://t.co/jNhxh3QGUR @thePeerJ https://t.co/WtIvd7p08x

120 days ago
our recent paper on a minimal set of internal control genes for gene expression studies in head and neck squamous cell carcinoma busts old myths on housekeeping genes in hnscc gene expression studies https://t.co/vf1rBZuUl9 #openscience

Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches https://t.co/gdqfcA3Qhd w @BetaScience

Study constructs a competitive endogenous RNA network, suggests several lncRNAs of prognostic value in renal cell #kidneyCancer https://t.co/00othpy2X5 https://t.co/f0vg7PIoRR

Finally Published! The Oyster River Protocol: a multi-assembler and kmer approach for de novo transcriptome assembly. https://t.co/6Ss7TULCKQ

Happy #ToxinTuesday! Venomix: Toxin Gene Candidate Identifier https://t.co/V5ebCm9Lmv is now available (but was before on @Bitbucket and @PeerJPreprints) now via @thePeerJ.

Krocus for uncorrected long read MLST has been published today in @thePeerJ https://t.co/zlZchJRjM6 #Bioinformatics #Microbiology #Epidemiology