  In the past decade, transcriptome data have become an important component of
many phylogenetic studies. Phylogenetic studies now regularly include genes
from newly sequenced transcriptomes, as well as publicly available
transcriptomes and genomes. Implementing such a phylogenomic study, however, is
computationally intensive, requires the coordinated use of many complex
software tools, and includes multiple steps for which no published tools exist.
Phylogenomic studies have therefore been manual or semiautomated. In addition
to taking considerable user time, this makes phylogenomic analyses difficult to
reproduce, compare, and extend. In addition, methodological improvements made
in the context of one study often cannot be easily applied and evaluated in the
context of other studies. We present Agalma, an automated tool that conducts
phylogenomic analyses. The user provides raw Illumina transcriptome data, and
Agalma produces annotated assemblies, aligned gene sequence matrices, a
preliminary phylogeny, and detailed diagnostics that allow the investigator to
make extensive assessments of intermediate analysis steps and the final
results. Sequences from other sources, such as externally assembled genomes and
transcriptomes, can also be incorporated in the analyses. Agalma tracks
provenance, profiles processor and memory use, records diagnostics, manages
metadata, and enables rich HTML reports for all stages of the analysis. Agalma
includes a test data set and a built-in test analysis of these data. In
addition to describing Agalma, we here present a sample analysis of a larger
seven-taxon data set. Agalma is available for download at
https://bitbucket.org/caseywdunn/agalma. Agalma allows complex phylogenomic
analyses to be implemented and described unambiguously as a series of
high-level commands. This will enable phylogenomic studies to be readily
reproduced, modified, and extended.
