The current academic culture facing women in science, technology, engineering, and math (STEM) fields in the United States has sparked the formation of grassroots advocacy groups to empower female scientists in training. However, the impact of these initiatives often goes unmeasured and underappreciated. Our Women in Science and Engineering (WiSE) organization serves postdoctoral researchers, graduate students, and research technicians (trainees) at a private research institute for biological sciences. Here we propose the following guidelines for cultivating a successful women-in-STEM-focused group based upon survey results from our own scientific community as well as the experience of our WiSE group leaders. We hope these recommendations can provide guidance to advocacy groups at other research and academic organizations that wish to strengthen their efforts. Whereas our own group specifically focuses on the underrepresented state of women in science, we hope these guidelines may be adapted and applied to groups that advocate for any minority group within the greater scientific community (i.e., those of gender, race/ethnicity, socioeconomic background, sexual orientation, etc.).

MOTIVATION: Most RNA-seq data analysis software packages are not designed to handle the complexities involved in properly apportioning short sequencing reads to highly repetitive regions of the genome. These regions are often occupied by transposable elements (TEs), which make up between 20 and 80% of eukaryotic genomes. They can contribute a substantial portion of transcriptomic and genomic sequence reads, but are typically ignored in most analyses. RESULTS: Here, we present a method and software package for including both gene- and TE-associated ambiguously mapped reads in differential expression analysis. Our method shows improved recovery of TE transcripts over other published expression analysis methods, in both synthetic data and qPCR/NanoString-validated published datasets. AVAILABILITY AND IMPLEMENTATION: The source code, associated GTF files for TE annotation, and testing data are freely available at http://hammelllab.labsites.cshl.edu/software. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.