Difference between revisions of "Team:Uppsala/Transcriptomics/Bioinformatics"
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| − | <p>We decided to create our bioinformatics pipeline from scratch. Generally, a basic transcriptomics pipeline looks like the following: Alignment to a reference genome, gene counting and differential gene expression. However a couple of data processing steps were needed for the nanopore data beforehand such as demultiplexing and adapter trimming.</p> | + | <p>We decided to create our bioinformatics pipeline from scratch. Generally, a basic transcriptomics pipeline looks like the following: Alignment to a reference genome, gene counting and differential gene expression. However a couple of data processing steps were needed for the nanopore data beforehand such as demultiplexing and adapter trimming.</p><br><br> |
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| + | <h2>Demultiplexing and adapter trimming</h2> | ||
Revision as of 16:57, 15 October 2018
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Bioinformatics
After a succesfull sequencing has been performed and you’re left with raw data containing millions and millions (and millions) of lines of base sequences, all of this needs to be processed and interpreted. This is where the interdisciplinary field of bioinformatics comes in. A vast range of software tools are available, tailored to different kinds of analysis as well as being unique to the different sequencing methods being used.
Most of the tools we used were available through the free website Usegalaxy.org which as well let us do the processing on their servers. Because we also made use of nanopore sequencing, tailored tools used for the MinION data were available from their community hub which could be run from a terminal window.
Experiment
We decided to create our bioinformatics pipeline from scratch. Generally, a basic transcriptomics pipeline looks like the following: Alignment to a reference genome, gene counting and differential gene expression. However a couple of data processing steps were needed for the nanopore data beforehand such as demultiplexing and adapter trimming.