Back

GBRAP: a tool to retrieve, parse and analyze GenBank files of viral and bacterial species

Vischioni, C.; Giaccone, V.; Catellani, P.; Alberghini, L.; Scapin, R. M.; Taccioli, C.

2021-09-24 bioinformatics
10.1101/2021.09.21.461110 bioRxiv
Show abstract

SummaryGenBank files contain genomic data of sequenced living organisms. Here, we present GBRAP (GenBank Retrieving, Analyzing and Parsing software), a tool written in Python 3 that can be used to easily download, parse and analyze viral and bacterial GenBank files, even when contain more than one genomic sequence for each species. GBRAP can analyze more files simultaneously through single command-line parameters that give as output a single table showing the genomic characteristics of each organism. It is also able to calculate Shannon, LZSS (Lempel-Ziv-Storer-Szymanski) and topological entropy for both the entire genome and its constitutive elements such as genes, rRNAs, tRNAs, tmRNAs and ncRNAs together with Chargaffs second parity rule scores obtained using different mathematical methods. Moreover, GBRAP can calculate, the number, the length and the nucleotides abundance of genomic components for each DNA strand and for the overlapping regions among the two complementary helixes. To our knowledge, this is the only software capable of providing this type of genomic analyses all together in a single tool, that, therefore can be used by the scientists interested in both genomics and evolutionary research. Availability and implementationThe data underlying this article are available from the corresponding author on reasonable request.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.