Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis

We provide the F1 Chip-Seq bigwigs, the parental lines variant call, result tables, ReMap 2022 bigwigs, Basenji trained model and all the code generated for the analysis.

The Chip-Seq bigwig tracks for all F1 crosses and conditions are available for download:

• Full F1 Chip-Seq bigwigs Repository

de novo variant call for the parental lines used to generate the F1 crosses:

Haplotype_joint_call_F1.vcf.gz, GATK joint haplotype variant call

Haplotype_joint_call_F1_stringent_filtering.vcf.gz, stringent cutoffs for variant filtering

Haplotype_joint_call_F1_lenient_filtering.vcf.gz, lenient cutoffs for variant filtering

Results tables:

Allelic Imbalance across all conditions

Chip-Seq peaks for all conditions

fimo motif scores

ProBound affinity scores

The full list of ReMap2022 bigwigs is available for download:

• ReMap 2022 Drosophila Metatable
• Full Drosophila ReMap 2022 bigwigs Repository

The Basenji model and training files are available for download:

Input sequences used for Basenji training

Basenji model

Variant scores from Basenji (predicted Allelic Imbalance)

The code used to generate all results and figures is available on GitLab.

You can find the raw data files on ArrayExpress:

MTAB-14209 – F1 Chip-Seq

MTAB-14210 – F1 genomic DNA