Gantt charts are a project management tool designed to visualise the tasks in a project, how long they will take and what order they must be completed. If you haven’t seen one before essentially they look like a modified horizontal bar chart. Along the horizontal axis is time with tasks along the vertical. Each task consists of a bar where the ends are the start and end times. Often there are also arrows indicating dependencies and a line showing the current date.

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Bioconductor 3.3 has just been released. You can find the complete list of new packages (and changes to existing packages) here but here are a few I thought might be interesting based on the description. I might have more to say once I’ve had time to try a few out. debrowser – Interactive plots and tables for differential expression DEFormats – convert between differential expression formats EBSEA – exon based differential expression EmpiricalBrownsMethod – combining dependent p-values Linnorm – normalisation for parametric tests, simulation of RNA-seq data multiClust – feature selection and clustering analysis for transcriptomic data RGraph2js – interactive network visualisations with D3 tximport – import and summarise transcript-level estimates Single-cell These packages are specific to single-cell RNA-seq analysis.

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Recently this paper by Ilicic et al. suggested a method for assessing the quality of individual cells in a single-cell RNA-seq experiment. The basic idea is to extract various biological and technical features from each the reads for each cell, then use PCA with outlier detection or a SVM to classify cells as “high” or “low” quality. There are two pieces of software associated with the paper: cellity, an R package that performs the classification and Celloline, a Python script that performs alignment, summarisation and extraction of alignment statistics such as the number of reads aligned to exons, introns, intergenic regions etc.

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It’s come to the stage in my Master’s where I have to start thinking about writing my thesis. Apart from all the analysis I have to do before I can do that there is also the question of what I am going to use to construct the document itself. For the last year or so I have been writing using Markdown which is converted to Tex using Pandoc then used to produce a PDF.

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This Saturday I attended the first workshop run by Open Science Workshops at the Inspire9 collaborative workspace. Open Source Workshops is a new initiative aiming to promote open source tools and techniques to the scientific community. The workshop consisted of two main parts: an introduction to the basics of Github (creating repositories, commiting, forking, merging…) and the SageMathCloud; and a serious of talks: General discussion of how and why you should take an open approach to scientific research (Alex Ghitza, Pure Maths Lecturer, University of Melbourne).

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Luke Zappia

Bioinformatician in training

PhD student

Australia