ArticleDatabase : the journal of biological databases and curation2014
A novel multi-alignment pipeline for high-throughput sequencing data.
Article in Database : the journal of biological databases and curation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 49 citations in OpenAlex.
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- Landscape of genomic imprinting and its functions in the mouse mammary gland.Journal of molecular cell biology · 2020Article
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Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Mapping reads to a reference sequence is a common step when analyzing allele effects in high-throughput sequencing data. The choice of reference is critical because its effect on quantitative sequence analysis is non-negligible. Recent studies suggest aligning to a single standard reference sequence, as is common practice, can lead to an underlying bias depending on the genetic distances of the target sequences from the reference. To avoid this bias, researchers have resorted to using modified reference sequences. Even with this improvement, various limitations and problems remain unsolved, which include reduced mapping ratios, shifts in read mappings and the selection of which variants to include to remove biases. To address these issues, we propose a novel and generic multi-alignment pipeline. Our pipeline integrates the genomic variations from known or suspected founders into separate reference sequences and performs alignments to each one. By mapping reads to multiple reference sequences and merging them afterward, we are able to rescue more reads and diminish the bias caused by using a single common reference. Moreover, the genomic origin of each read is determined and annotated during the merging process, providing a better source of information to assess differential expression than simple allele queries at known variant positions. Using RNA-seq of a diallel cross, we compare our pipeline with the single-reference pipeline and demonstrate our advantages of more aligned reads and a higher percentage of reads with assigned origins. Database URL: http://csbio.unc.edu/CCstatus/index.py?run=Pseudo.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.