trumpet: transcriptome-guided quality assessment of m6A-seq data

BACKGROUND

Methylated RNA immunoprecipitation sequencing (MeRIP-seq or m6A-seq) has been extensively used for profiling transcriptome-wide distribution of RNA N6-Methyl-Adnosine methylation. However, due to the intrinsic properties of RNA molecules and the intricate procedures of this technique, m6A-seq data often suffer from various flaws. A convenient and comprehensive tool is needed to assess the quality of m6A-seq data to ensure that they are suitable for subsequent analysis.

RESULTS

From a technical perspective, m6A-seq can be considered as a combination of ChIP-seq and RNA-seq; hence, by effectively combing the data quality assessment metrics of the two techniques, we developed the trumpet R package for evaluation of m6A-seq data quality. The trumpet package takes the aligned BAM files from m6A-seq data together with the transcriptome information as the inputs to generate a quality assessment report in the HTML format.

CONCLUSIONS

The trumpet R package makes a valuable tool for assessing the data quality of m6A-seq, and it is also applicable to other fragmented RNA immunoprecipitation sequencing techniques, including m1A-seq, CeU-Seq, Ψ-seq, etc.

Current concepts and clinical importance of glycemic variability

BACKGROUND AND AIMS

Evolving evidence indicate that variations in blood glucose levels are likely to be an important factor in developing diabetic complications. Monitoring glucose fluctuations in patients remains as a therapeutic challenge and more evidence needs to be created in order to bring GV into limelight. This review encapsulates the most important findings conducted and discusses on them to provide readers a better understanding on this emerging subject.

METHODS

Keyword-based comprehensive desktop search was conducted to gather the relevant literature. Triple-stage cascade type content analysis of the literature was conducted to draw relevant themes of discussions.

RESULTS

High glycemic variability is associated with an increased risk of development of diabetic complications especially in cardiac conditions. The widely used and accepted metrics to determine the variations in blood glucose are Standard deviation (SD), MAGE (Mean amplitude of glycemic excursions) and MODD (Mean of daily differences). Occurrence of blood glucose variations affects at a molecular level thereby causing more harm than the occurrence of hyperglycemia alone.

CONCLUSION

Available data suggest that Glycemic Variability should be used as an additional marker of glycemia. Additional research globally, and in India are required.

Collaboration Networks and Career Trajectories: What Do Metadata from Data Repositories Tell Us?

Science is increasingly carried out through scientific collaborations, allowing researchers pool their experience, knowledge, and skills. In this work we identify factors related to a scientist's collaboration capacity, their ability accumulate new collaborations over their career. To do this offer a new collaboration capacity framework and begin the work of validating it empirically by testing a number of hypotheses. We use data from GenBank, a cyberinfrastructure (CI)-enabled data repository that stores and manages scientific data. The data allow us to construct longitudinal networks, thereby giving us yearly scientific collaboration maps. We find that a scientist's network position at an early stage is related to their capacity to build new collaborations and that researchers who manage an upward trend in productivity tend to have higher collaboration capacity. Our work makes a contribution to science of science studies by offering a collaboration capacity framework and providing partial empirical support for it.

A haptic laparoscopic trainer based on affine velocity analysis: engineering and preliminary results

BACKGROUND

There is a general agreement upon the importance of acquiring laparoscopic skills outside the operation room through simulation-based training. However, high-fidelity simulators are cost-prohibitive and elicit a high cognitive load, while low-fidelity simulators lack effective feedback. This paper describes a low-fidelity simulator bridging the existing gaps with affine velocity as a new assessment variable. Primary validation results are also presented.

METHODS

Psycho-motor skills and engineering key features have been considered e.g. haptic feedback and complementary assessment variables. Seventy-seven participants tested the simulator (17 expert surgeons, 12 intermediates, 28 inexperienced interns, and 20 novices). The content validity was tested with a 10-point Likert scale and the discriminative power by comparing the four groups' performance over two sessions.

RESULTS

Participants rated the simulator positively, from 7.25 to 7.72 out of 10 (mean, 7.57). Experts and intermediates performed faster with fewer errors (collisions) than inexperienced interns and novices. The affine velocity brought additional differentiations, especially between interns and novices.

CONCLUSION

This affordable haptic simulator makes it possible to learn and train laparoscopic techniques. Self-assessment of basic skills was easily performed with slight additional cost compared to low-fidelity simulators. It could be a good trade-off among the products currently used for surgeons' training.