five

GNPS Genomics Demo Submission

收藏
NIAID Data Ecosystem2026-03-09 收录
下载链接:
https://www.omicsdi.org/dataset/gnps/MSV000079531
下载链接
链接失效反馈
官方服务:
资源简介:
This is a demo GNPS-genomics submission, providing an example of a submission that is compatible with NRPquest / RiPPquest / Glycogenomics and other MS/MS-genomic tools that are becoming available at GNPS. MS/MS data should be uploaded as Peak List / Raw Spectrum as usual. Sequence data should be uploaded as "Sequence Databases" in fasta format. In addition, the user need to create an excel file described below, save it as "Tab Delimited Text (.txt)" with the name "metabolome_genome_link.txt", and upload it as "Supplementary Files". metabolome_genome_link.txt file should have a first row header "SpectrumFile SequenceFile" and then in each row, there should be a spectrum file and a sequence file that the spectrum file should be searched against. An example can be : SpectrumFile SequenceFile spectrum_1.mzXML sequence_1.fasta spectrum_2a.mzXML sequence_2.fasta spectrum_2b.mzXML sequence_2.fasta spectrum_3.mzXML sequence_3a.fasta spectrum_3.mzXML sequence_3b.fasta In this case, spectrum_1.mzXML gets searched against seqeunce_1.mzXML, spectrum_2a.mzXML and spectrum_2b.mzXML get searched against sequence_2.fasta, and spectrum_3.mzXML gets searched against both sequence_3a.fasta and sequence_3b.fasta. To avoid time-consuming sequence data uploads, the user also have the option to simply put refseq or genbank accession numbers instead of uploading a fasta file as "Sequence database". To do this, the user should enter "#RefSeq:" and "#GeneBank:" followed by RefSeq or GeneBank accession. For example both spectrum_albus.mzXML #RefSeq:GCF_000359525.1 and spectrum_albus.mzXML #GenBank:GCA_000359525.1 are valid entries, and they search spectrum_albus.mzXML against : http://www.ncbi.nlm.nih.gov/assembly/GCF_000359525.1/ Please see the demo dataset submission for more information.
创建时间:
2016-02-25
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作