https://github.com/flatironinstitute/inferelator-prior

Gene regulatory network inference using DNA-binding motifs and chromatin accessibility data.
https://github.com/flatironinstitute/inferelator-prior

inference network

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Gene regulatory network inference using DNA-binding motifs and chromatin accessibility data.

• Host: GitHub
• URL: https://github.com/flatironinstitute/inferelator-prior
• Owner: flatironinstitute
• License: mit
• Created: 2019-07-03T19:51:02.000Z (over 5 years ago)
• Default Branch: release
• Last Pushed: 2024-11-01T14:14:03.000Z (3 months ago)
• Last Synced: 2024-11-01T15:19:33.821Z (3 months ago)
• Topics: inference, network
• Language: Python
• Homepage:
• Size: 6.23 MB
• Stars: 9
• Watchers: 2
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# inferelator-prior

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This is a set of pipelines to create expression, dynamic response, and prior matrices for network inference. 

They are designed to create data that is compatible with the [inferelator](https://github.com/flatironinstitute/inferelator) package. 

### Usage

    python -m inferelator_prior.network_from_motifs

    usage: network_from_motifs.py --motif motif_PWM_file.meme

                                  -f genome_fasta_file.fasta

                                  -g genome_annotation_file.gtf

                                  -o ~/output/path/prefix

                                  --species {yeast,fly,mouse,human}

                                  -b constraning_bed_file.bed

                                  --cpu num_cores

                                  --genes gene_list.txt

                                  --tfs tf_list.txt

                                  

This requires a motif PWM database (`-m PATH`), 

a genome to search (both sequence as a FASTA `-f PATH` and annotations `-g PATH`),

and an output prefix for several files (`-o PATH`).

In addition, default settings for a specific species can be set with (`--species`).

A BED file can be provided (`-b PATH`) based on some constraining experiment to restrict searching to 

specific genomic areas.

This will use multiple cores to search for motifs and process the resulting data.

By default, all available processors will be used, but this can be overridden with `--cpu N`.

A list of genes (on e per line in a text file) can be provided to `--genes` 

and a list of tfs (one per line in a text file) can be provided to `--tfs`.

A network will be built for only these genes or TFs.

The output from this script is an unsigned connectivity matrix (0, 1) connecting genes on rows to regulators on columns.

In addition, this produces an unfiltered score matrix (0, ) connecting genes on rows to regulators on columns.

### Requirements

In addition to

python dependencies, this package also requires 

[STAR](https://github.com/alexdobin/STAR),

[sra-tools](http://ncbi.github.io/sra-tools/), 

[bedtools](https://bedtools.readthedocs.io/en/latest/),

[samtools](http://www.htslib.org/), and

[fimo](http://meme-suite.org/doc/fimo.html).