LANE runner


Version 2.0

'LANE runner' is a JAVA application developed to facilitate the annotation of de novo sequenced transcriptomes. It was extensively used for the Reptilian Brain Transcriptome project (Tzika et al. 2011) and for building the subsequent Reptilian Transcriptomes 2.0 database (Tzika et al. 2015).

‘LANE runner 2.0’ integrates:

    (1) Iterative BLAST+ searches (Camacho et al. 2009) against multiple databases,

    (2) Reciprocal Best BLAST Hits (RBBH) identification for homology assessment, and

    (3) Consensus sequence building to assemble sequences exhibiting the same annotation.

‘LANE runner 2.0’ can perform the BLAST+ searches either on a wwwblast server that we make available at the University of Geneva, or with a BLAST+ package made available by the NCBI. The user can also choose to locally install a wwwblast server rather than using the Geneva server.

Consensus sequences are built in ‘LANE runner 2.0’ using Clustal Omega (Sievers et al. 2011) and MUSCLE (Edgar 2004). Multiple additional tools are provided in ‘LANE runner 2.0’ to manipulate FASTA files (e.g. remove adaptor sequences and perform sequence-size selection), select RBBH, or prepare NEXUS files for phylogenetic analyses (that can be performed with MetaPIGA; Helaers & Milinkovitch 2010).

When using LANE runner v2.0, please cite Tzika et al. Genome Biol. Evol. 2015 (see full reference below).

Installation packages necessary for LANE runner to be fully functional

wwwblast server:

and/or BLAST+ package:

Clustal Omega (optional)

Python 2.7 (for Windows)

perl 5 (for Windows)


  1. Tzika A. C., Ullate-Agote A., Grbic D., & M. C. Milinkovitch
    Reptilian Transcriptomes v2.0: an extensive resource for Sauropsida genomics and transcriptomics
    Genome Biology & Evolution 2015, 7(6):1827-1841

References of methods and algorithms used in LANE runner v2.0

  1. Camacho C., Coulouris G., Avagyan V., Ma N., Papadopoulos J., Bealer K. & T. L. Madden
    BLAST+: architecture and applications
    BMC Bioinformatics 2009, 10:421

  2. Sievers F., Wilm A., Dineen D.G., Gibson T.J., Karplus K., Li W., Lopez R., McWilliam H., Remmert M., Söding J., Thompson J.D., & D.G. Higgins
    Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega
    Molecular Systems Biology 2011, 7:539

  3. Edgar, R.C.
    MUSCLE: multiple sequence alignment with high accuracy and high throughput
    Nucleic Acids Res. 2004, 32(5):1792-1797

Related publications

  1. Tzika A. C., Helaers R., Schramm G., & M. C. Milinkovitch
    Reptilian-transcriptome v1.0, a glimpse in the brain transcriptome of five divergent Sauropsida lineages and the phylogenetic position of turtles
    EvoDevo 2011, 2: 19

  2. Helaers R. & M.C. Milinkovitch
    MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics
    BMC Bioinformatics 2010, 11: 379

  3. Brykczynska U., Tzika A.C., Rodriguez I. & M. C. Milinkovitch
    Contrasted evolution of the vomeronasal receptor repertoires in Mammals and Squamate reptiles
    Genome Biology & Evolution 5: 389-401 (2013)