Cell type specific TFBS prediction

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Method, code, references Input data Algorithm Comment
TEPIC [1]

http://www.github.de/schulzlab/TEPIC.

Input:

  • open chromatin data (DNaseI-seq, NOMe-seq)
  • PWM (Jaspar, HOCOMOCO, Uniprobe)

Output:

  • TFBS (TF affinities)
  • TF-gene scores

1) TEPIC segments the genome into user specified regions and annotates those with TF binding using TRAP [2].

2) These predictions are aggregated to gene scores. Within this aggregation TEPIC offers exponential decay [3] and scaling of TF region scores using the signal of an open chromatin assay.

These can be used in downstream applications, e.g. to determine the influence of chromatin accessiblity on gene expression, without considering detailed information on TF binding.

BinDNase [4]

http://research.ics.aalto.fi/csb/software/bindnase/

No permission to access software on they site.

Ask the access.


References

Error fetching PMID 27899623:
Error fetching PMID 17098775:
Error fetching PMID 19995984:
Error fetching PMID 25957350:
  1. Error fetching PMID 27899623: [Schmidt217]
  2. Error fetching PMID 17098775: [Roider2007]
  3. Error fetching PMID 19995984: [Ouyang2007]
  4. Error fetching PMID 25957350: [Kahara2015]
All Medline abstracts: PubMed | HubMed
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