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Get started

Clone the repo!

git clone https://github.com/pvtodorov/rotation_tune.git

Make the batch script executable.

cd rotation_tune
chmod 700 Scripts/run_pipeline.sh

Run the scripts

./Scripts/run_pipeline.sh

How to add studies

Scripts/get_sample_ids_from_meta.R ingests a YAML file. Here studies can be specified as follows:

  -
    Sample_series_id: GSE98519
  -
    Sample_series_id: GSE100599
    Sample_source_name_ch1: hypothalamus
  -
    Sample_series_id: GSE98356
    Sample_source_name_ch1: ['Hypothalamus_ad libitum (AL)',
                             'Hypothalamus_ad libitum after diet restricted',
                             'Hypothalamus_diet restricted']

These filter the metadata according to the specified key and values.

The Scripts

Script What it does
run_pipeline.sh Creates Outputs/ and Data/ directories if they do not exist. If the Data/ directory and thus the ARCHS4 mouse_matrix.h5 is not found, it will be downloaded using wget.
get_sample_ids_from_meta.R Given a path to the YAML configuration it loads the ARCHS4 h5 file and selects the studies and samples from it. The script then dumps a YAML file keyed to GSE with a list of indicies for the samples within the matrix.
get_gene_idxs.R Given a path to a YAML containing sample indicies and a per study and all study threshold it writes to a YAML file keyed to GSE with genes that are non-zero for n samples specified per study and all study threshold.
WGCNA_outlier_removal.R Takes in the the sample and gene indicies and applies per-study WGCNA outlier detection as performed by Gandall on arrays here. Dumps a YAML keyed to GSEs with sample indicies as values but with the outliers excluded.
batch_correction.R load all samples for all studies, performs batch correction using GSEs as batches, saves a CSV file with samples as columns and genes as rows.