Privacy Issues

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 privacy concerns for 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 never sent over the network.

Someg hgvs 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 fully 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. The method signatures, including input arguments, are shown below with a discussion about privacy consequences.

fetch_seq(ac, start_i, end_i)

This method fetches reference sequence in the context of the variant and is required in order to validate, normalize, and replace variant reference sequences. By sending accession and coordinates, it reveals a specific region of interest (and therefore genes and possible clinical conditions).

The current implementation, which fetches transcripts and genomic sequences from UTA, NCBI, and Ensembl, is a measure until we complete a comprehensive sequence archive.

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_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.