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Code used to generate summaries, models and figures for article "A field-wide assessment of differential high throughput sequencing reveals widespread bias".

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Geo-htseq-paper

We analyzed the field of expression profiling by high throughput sequencing, or RNA-seq, in terms of replicability and reproducibility, using data from the GEO (Gene Expression Omnibus) repository. Our work puts an upper bound of 56% to field-wide reproducibility, based on the types of files submitted to GEO.

Getting data

Got to https://zenodo.org/record/6795313 and download data archive, let's say, to your Downloads folder.

Then create new folder, e.g. "geo-htseq" and enter this folder

mkdir geo-htseq
cd geo-htseq

Copy downloaded dataset to your working directory and uncompress:

cp ~/Downloads/geo-htseq.tar.gz .
tar -xzvf geo-htseq.tar.gz

Remove tar.gz archive from working directory:

rm geo-htseq.tar.gz

Now you should have dataset in "output" subdirectory ready for analysis.

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Code used to generate summaries, models and figures for article "A field-wide assessment of differential high throughput sequencing reveals widespread bias".

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