py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project

Fast Grain Mapping with Sub-Nanometer Resolution Using 4D-STEM with Grain Classification by Principal Component Analysis and Non-Negative Matrix Factorization

High-throughput grain mapping with sub-nanometer spatial resolution is demonstrated using scanning nanobeam electron diffraction (also known as 4D scanning transmission electron microscopy, or 4D-STEM) combined with high-speed direct electron detection. An electron probe size down to 0.5 nm in diameter is implemented and the sample investigated is a gold-palladium nanoparticle catalyst. Computational analysis of the 4D-STEM data sets is performed using a disk registration algorithm to identify the diffraction peaks followed by feature learning to map the individual grains. Two unsupervised feature learning techniques are compared: Principal component analysis (PCA) and non-negative matrix factorization (NNMF). The characteristics of the PCA versus NNMF output are compared and the potential of the 4D-STEM approach for statistical analysis of grain orientations at high spatial resolution is discussed

Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions.

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies

Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space

Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202

Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space

Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202

Evaluation of a Droplet Digital Polymerase Chain Reaction Format for DNA Copy Number Quantification

ABSTRACT: Droplet digital polymerase chain reaction (ddPCR) is a new technology that was recently commercialized to enable the precise quantification of target nucleic acids in a sample. ddPCR measures absolute quantities by counting nucleic acid molecules encapsulated in discrete, volumetrically defined, water-in-oil droplet partitions. This novel ddPCR format offers a simple workflow capable of generating highly stable partitioning of DNA molecules. In this study, we assessed key performance parameters of the ddPCR system. A linear ddPCR response to DNA concentration was obtained from 0.16 % through to 99.6 % saturation in a 20,000 droplet assay corresponding to more than 4 orders of magnitude of target DNA copy number per ddPCR. Analysis of simplex and duplex assays targeting two distinct loci in the Lambda DNA genome using the ddPCR platform agreed, within their expanded uncertainties, with values obtained using a lower density microfluidic chamber based digital PCR (cdPCR). A relative expanded uncertainty under 5 % was achieved for copy number concentration using ddPCR. This level of uncertainty is much lower than values typically observed for quantification of specific DNA target sequences using currently commercially available real-time and digital cdPCR technologies

Evolutionary potential and adaptation of Banksia attenuata (Proteaceae) to climate and fire regime in southwestern Australia, a global biodiversity hotspot

Substantial climate changes are evident across Australia, with declining rainfall and rising temperature in conjunction with frequent fires. Considerable species loss and range contractions have been predicted; however, our understanding of how genetic variation may promote adaptation in response to climate change remains uncertain. Here we characterized candidate genes associated with rainfall gradients, temperatures, and fire intervals through environmental association analysis. We found that overall population adaptive genetic variation was significantly affected by shortened fire intervals, whereas declining rainfall and rising temperature did not have a detectable influence. Candidate SNPs associated with rainfall and high temperature were diverse, whereas SNPs associated with specific fire intervals were mainly fixed in one allele. Gene annotation further revealed four genes with functions in stress tolerance, the regulation of stomatal opening and closure, energy use, and morphogenesis with adaptation to climate and fire intervals. B. attenuata may tolerate further changes in rainfall and temperature through evolutionary adaptations based on their adaptive genetic variation. However, the capacity to survive future climate change may be compromised by changes in the fire regime

Land-use effects on local biodiversity in tropical forests vary between continents

The file attached is the Published/publisher’s pdf version of the article

The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020

Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology