Tag: ENA

EMBL2checklists 0.6 – Converts EMBL-formatted flatfiles to ENA Checklists

EMBL2checklists 0.6

:: DESCRIPTION

EMBL2checklists converts EMBL- or GenBank-formatted flat files to submission-ready checklists (i.e., tab-separated spreadsheets) for submission to ENA via the interactive Webin submission system.

::DEVELOPER

Michael Gruenstaeudl

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOs
  • Python

:: DOWNLOAD

EMBL2checklists

:: MORE INFORMATION

Citation

Gruenstaeudl M, Hartmaring Y.
EMBL2checklists: A Python package to facilitate the user-friendly submission of plant and fungal DNA barcoding sequences to ENA.
PLoS One. 2019 Jan 10;14(1):e0210347. doi: 10.1371/journal.pone.0210347. PMID: 30629718; PMCID: PMC6328100.

annonex2embl 1.0.3 – Preparation of Annotated DNA Sequences for Bulk Submissions to ENA

annonex2embl 1.0.3

:: DESCRIPTION

annonex2embl Converts an annotated DNA multi-sequence alignment (in NEXUS format) to an EMBL flatfile for submission to ENA via the Webin-CLI submission tool

::DEVELOPER

Michael Gruenstaeudl

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOs
  • Python

:: DOWNLOAD

 annonex2embl 

:: MORE INFORMATION

Citation

Gruenstaeudl M.
annonex2embl: automatic preparation of annotated DNA sequences for bulk submissions to ENA.
Bioinformatics. 2020 Jun 1;36(12):3841-3848. doi: 10.1093/bioinformatics/btaa209. PMID: 32227202.

ENA 1.3-0 – Ensemble Network Aggregation

ENA 1.3-0

:: DESCRIPTION

ENA is an approach which leverages the inverse-rank-product (IRP) method to combine networks. This package provides the capabilities to use IRP to bootstrap a dataset using a single method, to aggregate the networks produced by multiple methods, or to aggregate the networks produced on different datasets.

::DEVELOPER

The Quantitative Biomedical Research Center (QBRC)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • R

:: DOWNLOAD

  ENA

:: MORE INFORMATION

Citation

PLoS One. 2014 Nov 12;9(11):e106319. doi: 10.1371/journal.pone.0106319. eCollection 2014.
Ensemble-based network aggregation improves the accuracy of gene network reconstruction.
Zhong R, Allen JD, Xiao G, Xie Y