CITATION.cff

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title: >-
  SpikeFlow: automated and flexible analysis of ChIP-Seq
  data with spike-in control 
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Davide
    family-names: Bressan
    email: davidebx96@gmail.com
    orcid: 'https://orcid.org/0000-0003-4757-2535'
    affiliation: University of Trento - Italy
identifiers:
  - type: doi
    value: 10.1093/nargab/lqae118
    description: Journal Article
  - type: doi
    value: 10.5281/zenodo.10686980
repository-code: 'https://github.com/DavideBrex/SpikeFlow'
abstract: >-
  ChIP with reference exogenous genome (ChIP-Rx) is widely
  used to study histone modification changes across
  different biological conditions. A key step in the
  bioinformatics analysis of this data is calculating the
  normalization factors, which vary from the standard
  ChIP-seq pipelines. Choosing and applying the appropriate
  normalization method is crucial for interpreting the
  biological results. However, a comprehensive pipeline for
  complete ChIP-Rx data analysis is lacking. To address
  these challenges, we introduce SpikeFlow, an integrated
  Snakemake workflow that combines features from various
  existing tools to streamline ChIP-Rx data processing and
  enhance usability. SpikeFlow automates spike-in data
  scaling and provides multiple normalization options. It
  also performs peak calling and differential analysis with
  distinct modalities, enabling the detection of enrichment
  regions for histone modifications and transcription factor
  binding. Our workflow runs in-depth quality control at all
  the processing steps and generates an analysis report with
  tables and graphs to facilitate results interpretation. We
  validated the pipeline by performing a comparative
  analysis with DiffBind and SpikChIP, demonstrating robust
  performances in various biological models. By combining
  diverse functionalities into a single platform, SpikeFlow
  aims to simplify ChIP-Rx data analysis for the research
  community.
keywords:
  - ChIP-seq
  - Normalisation
  - NGS
  - Spike-in
license: MIT
version: 1.1.0
date-released: '2024-02-21'