Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.

Mechanisms that control gene expression at the RNA level are often referred to as post-transcriptional regulation (PTR) mechanisms. Splicing and polyadenylation (PA) are well-known examples of PTR that can regulate not only gene expression but also their function. Alternative Polyadenylation (APA) has already been shown to be essential to many biological processes (e.g., proliferation, cell differentiation, etc) and has also been implicated in the development and progression of multiple diseases (e.g., cancer, hematological and immune disorders, etc.). Although several sequencing methods have been developed to sequence only the transcript termination site (TTS), the number of publicly available data derived from these methods is extremely limited in comparison to traditional RNA-Seq data. To overcome this limitation, we created a new framework - Compositional Regression of Polyadenylation Differences (CORE-PAD) - for the study of differential APA events using traditional bulk RNA-seq data. Through simulated data, we showed that CORE-PAD has higher accuracy than other methods (accuracy = 0.98) in detecting APA events. We applied CORE-PAD across prostate cancer (PCa) samples with impaired CDK12 and “wild” samples. We found multiple genes presented differential PA site usage, including DNA repair genes. Most notably, we notice that many genes that exhibit differential APA were not differentially expressed at gene level, meaning they are potentially “silent drivers” that cannot be capture through standard differential gene expression analysis. These findings highlight the importance of studying APA, which can help shed light into another layer of regulation occurring between transcription and translation. This is especially important since these events can be source of neoantigens or targeted mRNA degradation which could be explore for new treatments. Finally, the CORE-PAD framework was designed to take advantage of our recently published recount3 resource making over 750,000 RNA-Seq samples of human and mouse origin readily available for analysis, enabling studies of APA across thousands of phenotypes in an accurate and accessible way. Citation Format: Eddie L. Imada, Christopher Wilks, Ben Langmead, Luigi Marchionni. Unraveling alternative polyadenylation in prostate cancer with CORE-PAD [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1219.

Publishing cutting-edge research in today's STEM journals requires resources and administrative coordination that are not available to many academic institutions and national economies. Adequate training and support could help scientists in lower-income regions and resource-poor institutions produce career-enhancing STEM research. We present the rationale for leveraging existing resources to enable scientists in lower-resource institutions and countries to re-analyze published "-omics" data given training, support, and access to standard computing hardware and cloud-based resources.