Genetic Data- High-Throughput Nucleotide Sequencing
MeSH ID: D059014
Description:
Techniques of nucleotide sequence analysis that increase the range, complexity, sensitivity, and accuracy of results by greatly increasing the scale of operations and thus the number of nucleotides, and the number of copies of each nucleotide sequenced. The sequencing may be done by analysis of the synthesis or ligation products, hybridization to preexisting sequences, etc.
Best practice for sharing this type of data:
A .bam file (Sequence Alignment Map in binary format) or a .fastq file for each run should be made available, along with a .txt file of the settings used in the run and the quality score encoding. Sample names must be consistent with those in downstream analyses. The code used for data preparation and analysis must also be stored.
Most suitable repositories:
Sequences may be uploaded to ArrayExpress, NCBI Gene, Bgee DataBase for Gene Expression Evolution, Bioconductor, BioXpress, Genetic Testing Registry, Reference Sequence Database, Clinical Knowledgebase, CodeOcean, NCBI Genome, Database of small human non-coding RNAs, Gene Expression Omnibus, Genomic Expression Archive, MetaSRA, National Omics Data Encyclopedia, Plant Genome Integrative Explorer, SalmoBase,Sequence Read Archive, SILVA,TogoVar, and XenMine.
Best practice for indicating re-use of existing data:
For public datasets please provide a DOI or other stable identified for the dataset itself *and* include a citation for the dataset in the reference list. Be sure to indicate exactly which data has been re-used, particularly when multiple versions of the dataset exist. In many cases, this is best achieved by sharing the code used to extract the part of the data that you analyzed. In some cases it may be best to share the exact dataset(s) you analyzed as well.
For access-controlled data authors should provide a link to instructions for obtaining access (e.g. here is the information page for ADNI (Alzheimer's Disease Neuroimaging Initiative): http://adni.loni.usc.edu/data-samples/access-data/).
When re-using a private dataset from a previous study please contact the data owners to discuss how the data can be made public.
