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种子大会和RNAseq成绩单无参考基因组注释稿

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Background. Transcriptomes are one of the first sources of high-throughput genomic data that have benefitted from the introduction of Next-Gen Sequencing. However, the interpretation of the large numbers of short reads and a quantitative estimation of gene expression presents a challenge, particularly in the absence of a reference genome. As sequencing technology becomes more accessible transcriptome sequencing will extend to multiple organisms for which genome sequence is unavailable. Results. Here we propose a computational workflow for the reconstruction of expressed gene transcripts, functional annotation and a quantitative estimation of transcript abundance that does not require a reference genome sequence and can be tolerant to low coverage. Instead of mapping reads to a reference genome or completely unsupervised clustering of reads we assemble the unknown transcriptome using nearest homologs from a public database as seeds. The workflow includes pre-existing free software a

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jf_sp.txt
makefile
xpress.c
xpress.exe
cluster_stats.c
cluster_stats.exe
Figure4.jpg
filter.c
filter_p.c

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