Ten simple rules for an inclusive summer coding program for non-computer-science undergraduates.

Since 2015, we have run a free 9-week summer program that provides non-computer science (CS) undergraduates at San Francisco State University (SFSU) with experience in coding and doing research. Undergraduate research experiences remain very limited at SFSU and elsewhere, so the summer program provides opportunities for many more students beyond the mentoring capacity of our university laboratories. In addition, we were concerned that many students from historically underrepresented (HU) groups may be unable to take advantage of traditional summer research programs because these programs require students to relocate or be available full time, which is not feasible for students who have family, work, or housing commitments. Our program, which is local and part-time, serves about 5 times as many students as a typical National Science Foundation (NSF) Research Experiences for Undergraduates (REU) program, on a smaller budget. Based on our experiences, we present 10 simple rules for busy faculty who want to create similar programs to engage non-CS HU undergraduates in computational research. Note that while some of the strategies we implement are based on evidence-based publications in the social sciences or education research literature, the original suggestions we make here are based on our trial-and-error experiences, rather than formal hypothesis testing.

CpG-creating mutations are costly in many human viruses.

Mutations can occur throughout the virus genome and may be beneficial, neutral or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly than similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are indeed costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses.