ArticlePloS one2014
Development and validation of an Haemophilus influenzae supragenome hybridization (SGH) array for transcriptomic analyses.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Beyond the pan-genome: current perspectives on the functional and practical outcomes of the distributed genome hypothesis.Biochemical Society transactions · 2020Review
- Identification and Characterization of msf, a Novel Virulence Factor in Haemophilus influenzae.PloS one · 2016Article
- Streptococcus pneumoniae Supragenome Hybridization Arrays for Profiling of Genetic Content and Gene Expression.Current protocols in microbiology · 2015Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
We previously carried out the design and testing of a custom-built Haemophilus influenzae supragenome hybridization (SGH) array that contains probe sequences to 2,890 gene clusters identified by whole genome sequencing of 24 strains of H. influenzae. The array was originally designed as a tool to interrogate the gene content of large numbers of clinical isolates without the need for sequencing, however, the data obtained is quantitative and is thus suitable for transcriptomic analyses. In the current study RNA was extracted from H. influenzae strain CZ4126/02 (which was not included in the design of the array) converted to cDNA, and labelled and hybridized to the SGH arrays to assess the quality and reproducibility of data obtained from these custom-designed chips to serve as a tool for transcriptomics. Three types of experimental replicates were analyzed with all showing very high degrees of correlation, thus validating both the array and the methods used for RNA profiling. A custom filtering pipeline for two-condition unpaired data using five metrics was developed to minimize variability within replicates and to maximize the identification of the most significant true transcriptional differences between two samples. These methods can be extended to transcriptional analysis of other bacterial species utilizing supragenome-based arrays.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.