Recruitment Data Challenge

The Bioinformatics & Biostatistics Group @ The Francis Crick Institute

Introduction

Here you will find the data from an RNA-Seq and ATAC-Seq experiment. Both experiments have the same design. There is a treatment and control group each containing three replicates making a total of six samples per experiment. The data files are defined as follows (all files are tab delimited text files):

RNA-Seq Data

• rnaseq_design.txt - Sample ids and corresponding condition labels.
• rnaseq_gene_counts.txt - Raw (not normalised) gene-level read counts for each sample.
• rnaseq_annotation.txt - Gene level annotation.

ATAC-Seq Data

• atacseq_design.txt - Sample ids and corresponding condition labels.
• atacseq_peak_counts.txt - Raw (not normalised) ATAC-Seq peak level counts for each sample.
• atacseq_peaks.bed - A bed file defining the peak loci

All sequence data were aligned to the human genome reference hg38.

The Challenge

The treatment here is thought to activate a transcriptional program via remodelling of the chromatin architecture.

Suggested aims:

1. Identify genes that may be transcriptionally regulated by chromatin remodelling.
2. Identify the possible transcriptional programs involved.
3. Present candidate transcription factors that may be responsible for the underlying regulation.

Please produce a 20 minute presentation detailing your exploration of the data, your analysis approach and findings.

We recognise exposure to these types of data will be variable amongst candidates. Greater credit will be placed on a candidate's ability to discuss the rationale behind their approach, challenges faced and potential future analysis direction than necessarily a "correct" answer.