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