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.
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.
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.
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.
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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