期刊
BIOINFORMATICS
卷 31, 期 20, 页码 3371-3373出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btv386
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资金
- BBSRC Project [BB/L00786X/1]
- Wellcome Trust [092545, 092096]
- CRUK [C6946/A14492]
- Wellcome Trust [103792/Z/14/Z] Funding Source: Wellcome Trust
- BBSRC [BB/L00786X/1] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/L00786X/1] Funding Source: researchfish
- Wellcome Trust [103792/Z/14/Z] Funding Source: researchfish
DamID is a powerful technique for identifying regions of the genome bound by a DNA-binding (or DNA-associated) protein. Currently, no method exists for automatically processing next- generation sequencing DamID (DamID-seq) data, and the use of DamID-seq datasets with normalization based on read-counts alone can lead to high background and the loss of bound signal. DamID-seq thus presents novel challenges in terms of normalization and background minimization. We describe here damidseq_pipeline, a software pipeline that performs automatic normalization and background reduction on multiple DamID-seq FASTQ datasets.
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