Project description:Single-cell RNA sequencing significantly deepened our insights into complex tissues and latest techniques are capable to analyze ten-thousands of cells simultaneously. With bigSCale, we provide an analytical framework being scalable to analyze millions of cells, addressing challenges of future large data sets. Unlike other methods, bigSCale does not constrain data to fit an a priori-defined distribution and instead uses an accurate numerical model of noise. We evaluate the performance of bigSCale using a biological model of aberrant gene expression and simulated data sets, which underlined its speed and accuracy. We further apply bigSCale to analyze 1.3 million cells from the mouse developing forebrain. The directed down-sampling strategy identified rare populations, such as Reelin positive Cajal-Retzius neurons, for which we determined a previously not recognized heterogeneity associated to distinct differentiation stages, spatial organization and cellular function. Together, bigSCale presents a perfect solution to address future challenges of large single-cell data sets.

2018-04-15 | GSE102934 | GEO

Rheology of Complex Topical Formulations: An Analytical Quality by Design Approach to Method Optimization and Validation.

Project description: Not available

| S-EPMC10385475 | biostudies-literature

Integrating analytical quality by design into bioanalytical method development: an HPLC-FLD method for quantification of alectinib in biological matrix.

Project description: Not available

| S-EPMC12372313 | biostudies-literature

A user-friendly chromatographic method to purify small regulatory RNAs

Project description:The discovery of the small regulatory RNA populations has changed our vision of cellular regulations. Indeed, loaded on Argonaute proteins they formed ribonucleoprotein complexes that target complementary sequences and achieved widespread silencing mechanisms conserved in most eukaryotes. The recent development of deep sequencing approaches highly contributed to their detection. Small RNA isolation form cells and/or tissues remains a crucial stage to generate robust and relevant sequencing data. In 2006, a novel strategy based on anion-exchange chromatography has been purposed as an alternative to the standard size-isolation purification procedure. However, the eventual biases of such a method have been poorly investigated. Moreover, this strategy not only relies on advanced technical skills and expensive material but is time consuming and requires an elevated starting biological material amount. Using bioinformatic comparative analysis of six independent small RNA-sequencing libraries of Drosophila ovaries, we here demonstrate that anion-exchange chromatography purification prior to small RNA extraction unbiasedly enriches datasets in bona fide reads (small regulatory RNA reads) and depletes endogenous contaminants (ribosomal RNAs and degradation products). The resulting increase of sequencing depth provides a major benefit to study rare populations. We then developed a fast and basic manual procedure to purify loaded small non coding RNAs using anion-exchange chromatography at the bench. We validated the efficiency of this new method and used this strategy to purify small RNAs from various tissues and organisms. We moreover determined that our manual purification increases the output of the previously described anion-exchange chromatography procedure.

2013-06-13 | GSE40748 | GEO

Quality by design-based approach for the development of an analytical method for quantifying ponatinib in rat plasma.

Project description: Not available

| S-EPMC11471595 | biostudies-literature