Jabba: Hybrid Error Correction for Long Sequencing Reads Using Maximal Exact Matches

Third generation sequencing platforms produce longer reads with higher error rates than second generation sequencing technologies. While the improved read length can provide useful information for downstream analysis, underlying algorithms are challenged by the high error rate. Error correction methods in which accurate short reads are used to correct noisy long reads appear to be attractive to generate high-quality long reads. Methods that align short reads to long reads do not optimally use the information contained in the second generation data, and suffer from large runtimes.

FloReMi, automated analysis for cytometry data

FloReMi (Flow density Regression using Minimal feature redundancy) is a tool for predicting survival times based on cytometry data, developed in the context of the FlowCAP IV challenge. FloReMi consists of 4 different steps, which might be relevant even if you are not working with survival data. First, we applied a quality control step, consisting of e.g. checking FSC vs time and performing automated doublet removal. This tool can be interesting if you want to ensure you only work with high quality measurements.


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