Protein Data- Sequence Alignment
MeSH ID: D016415
Description:
The arrangement of two or more amino acid or base sequences from an organism or organisms in such a way as to align areas of the sequences sharing common properties. The degree of relatedness or homology between the sequences is predicted computationally or statistically based on weights assigned to the elements aligned between the sequences. This in turn can serve as a potential indicator of the genetic relatedness between the organisms.
Best practice for sharing this type of data:
Data may be stored in a text-based file format (eg. FASTA format). It is common practice to share sequence alignments in both text and graphical formats. Sequences should be presented in rows, where conserved segments are aligned and indicated as identical or similar via some coded system (eg. symbols, colour). If the study involves human data, then ethical considerations around sharing need to be evaluated: Subject Data Table (Tabular data)
Most suitable repositories:
Sequence Alignment data may be added to repositories such as Ensembl, Reference Sequence Database, Conserved Domain Database, European Nucleotide Archive, Fungal Nomenclature and Species Databank, Influenza Research Database, NCBI Trace Archive, PASS2, Pfam, Sequence Read Archive, The Consensus CDS, SILVA, and UniProt Knowledgebase.
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.
