This page provides details about how the hgvs package works, with a focus on privacy issues that users may have. The intent is to provide users with enough information to assess the risks for themselves and their institutions.
What’s not done¶
No biologically-relevant data are collected or aggregated from any use of the hgvs package for any purpose. Furthermore, variant manipulation is entirely local. Sequence variants are not sent over a network at any time.
Some operations require additional data. For example, mapping variants between a genomic reference and a transcript requires transcript-specific alignment information. Currently, fetching addition data requires a network connection.
(We are considering whether and how to provide self-contained installations and do not require network access, but such is not available at this time.)
Data Provider Queries¶
hgvs requires a lot of specialized addition data to validate, normalize, and map variants. All queries for data are consolidated into a data provider interface that consists of 11 queries. Their method signatures, including input arguments, are shown below with a discussion about privacy consequences.
fetch_seq(ac, start_i, end_i)This method, which fetches reference sequence for a given accession and sequence coordinates, is likely the most serious information leak in the hgvs package. It is required in order to validate, normalize, and replace reference sequences. By sending accession and coordinates, it reveals a specific region of interest (and therefore genes and possible clinical conditions). As currently implemented, this query fetches transcripts from UTA and genomic sequences from NCBI.data_version()schema_version()Queries for meta data about the data provider.get_acs_for_protein_seq(seq)get_gene_info(gene)get_tx_exons(tx_ac, alt_ac, alt_aln_method)get_tx_for_gene(gene)get_tx_identity_info(tx_ac)get_tx_info(tx_ac, alt_ac, alt_aln_method)get_tx_mapping_options(tx_ac)get_tx_seq(ac)For all of these queries, the inputs are combinations of transcript accession, reference accession, gene name. These are likely too broad to constitute serious privacy concerns.
Information about current connections¶
The following is an example of the kinds of information available about a current connection as collected by PostgreSQL.
datname uta usename anonymous application_name hgvs-shell/0.4.0rc2.dev20+n97ead5bf0fed.d20150831 client_addr 188.8.131.52 client_hostname invitae.static.monkeybrains.net client_port 38318 backend_start 2015-08-31 22:58:26.411654+00 query_start 2015-08-31 22:58:30.669956+00 state_change 2015-08-31 22:58:30.673533+00 waiting f state idle query select * from tx_exon_aln_v where tx_ac=’NM_170707.3’ and alt_ac=’NC_000001.10’ and alt_aln_method=’splign’ order by alt_start_i
Several of these merit discussion.
- Upon connection using the UTA data provider, a string containing the name of the python script and hgvs version are passed to the postgresql server. The string typically looks like
hgvs-shell/0.4.0rc2.dev20+n97ead5bf0fed.d20150831. Clients may override the application_name when calling connect().
- client_addr and client_hostname
- The source IP and hostname are available for current connections. For most clients, this will mean identifying an institution but not specific computers or individuals.
- The current or most recently executed query is visible. When accessed through the data provider, this field is limited to Data Provider Queries.
Historical connection information¶
Although we do have historical logs for database connections, they provide only date, time, and database connection. Currently, we do not log queries, although we might choose to periodically log certain queries for performance monitoring.