Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Estimation of Forest Canopy Cover by Combining ICESat-2&#x002F;ATLAS Data and Geostatistical Method&#x002F;Co-Kriging

Accurately estimating forest canopy cover (FCC) is challenging by using traditional remote sensing images at the regional level due to the spectral saturation phenomenon. In this study, to improve the estimation accuracy, a new method of FCC wall-to-wall mapping was suggested based on ice, cloud, and land elevation satellite&#x002F;advanced topographic laser altimeter system (ATLAS) data. Specifically, one dataset of FCC&#x0027;s observations was combined with preprocessed ATLAS data and topographic factors to build a random forest regression (RFR) model. Moreover, the Co-Kriging method was used to generate spatially explicit values that are required by the RFR from the point data of ATLAS parameters, and then the wall-to-wall mapping of the FCC was conducted. The results showed that the RFR model had an accuracy of relative root-mean-square error (rRMSE) &#x003D; 0.09 with a coefficient of determination (R2) &#x003D; 0.91. The best-fit semivariogram models between primary variables and covariates were asr and TR (Model: Gaussian model, R2 &#x003D; 0.94, the residual sum of squares (RSS) &#x003D; 1.73 &#x00D7; 10&#x2212;6), landsat_perc and NDVI (Model: spherical model, R2 &#x003D; 0.46, RSS &#x003D; 1.58 &#x00D7; 10&#x2212;4), and photon_rate_can and slope (Model: exponential model, R2 &#x003D; 0.77, RSS &#x003D; 6.45 &#x00D7; 10&#x2212;4), respectively. FCC validation result showed that the FCC&#x0027;s wall-to-wall mapping was in great agreement with the dataset-2 (R2 &#x003D; 0.79; rRMSE &#x003D; 0.11)

Using Ring-Opening Metathesis Polymerization of Norbornene To Construct Thermally Activated Delayed Fluorescence Polymers: High-Efficiency Blue Polymer Light-Emitting Diodes

The exploitation of blue polymer emitters is of great importance for the application of solution-processed organic light-emitting diodes (OLEDs) in full color display. The highly efficient blue thermally activated delayed fluorescence (TADF) polymers are rarely reported up to now. Herein, we report an efficient approach to construct blue TADF polymers by ring-opening metathesis polymerization (ROMP) of norbornene. By side-chain engineering strategy, the polymers are endowed with distinct TADF features. By use of these blue polymeric emitters, the nondoped OLEDs achieved a maximum external quantum efficiency of 7.3% with the Commission Internationale de L’Eclairage (CIE) coordinates of (0.20, 0.29), which represents the state-of-the-art device performance for the TADF-based blue polymer light-emitting diodes (PLEDs)