Journal: Nature communications

Article Title: Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors.

doi: 10.1038/s41467-017-00965-y

Figure Lengend Snippet: Fig. 2 Comparison of whole-exome sequencing of cfDNA to whole-exome sequencing of matched tumor biopsies. a Fraction of clonal (≥0.9 cancer cell fraction, CCF) and subclonal (<0.9 CCF) SSNVs detected by MuTect in WES of tumor biopsies and confirmed (i.e., supported by ≥3 variant reads) in WES of cfDNA. Sites with <3 reads that had power <0.9 for mutation calling were not included when computing the fraction of SNVs confirmed (“Methods”). b Fraction of clonal and subclonal SSNVs detected in WES of cfDNA and confirmed in WES of tumor biopsies. For 18 patients with WES of cfDNA at a second time point t2, SSNVs not detected in the matched tumor biopsy but confirmed at t2 are indicated with black. c Analysis of clonal dynamics in an ER+ breast cancer patient diagnosed with metastatic disease 1.5 years (yrs) prior to biopsy and cfDNA collection (t1, Day 0). Clustering analysis of CCF for SSNVs between matched tumor biopsy and cfDNA (t1) is shown in the left panel. The right panel shows the CCF of four mutation clusters, one containing ESR1 L536P (Subclonal Cluster 1, orange) and the other containing ESR1 D538G (Subclonal Cluster 2, light blue), at t1 and t2 (51 days apart) from a patient with ER+ metastatic breast cancer being treated with a SERD. The lymph node biopsy was taken at the same time as cfDNA t1. Mutations were clustered by the CCFs for each pair of samples using Phylogic39 (“Methods”). Error bars represent the 95% credible interval of the joint posterior density of the clusters. Mutations, excluding indels, having ≥90% estimated power based on coverage in both samples are shown; clusters with fewer than three mutations are excluded. The number of mutations in each cluster is indicated in the legend in parentheses

Article Snippet: Matched tumor biopsies were processed and sequenced through the Broad Institute Genomics Platform’s Research Whole Exome Sequencing deep coverage pipeline (http://genomics.broadinstitute.org/data-sheets/DTS_WES_1Page_52016_0.pdf).

Techniques: Comparison, Sequencing, Variant Assay, Mutagenesis

Journal: NPJ Microgravity

Article Title: Rad-Bio-App: a discovery environment for biologists to explore spaceflight-related radiation exposures

doi: 10.1038/s41526-021-00143-x

Figure Lengend Snippet: The data within dashboard #4 of the Rad-Bio-App contains radiation data from Martian, lunar and spaceflight missions and ground-based radiation experiments. These data were filtered using radiation levels recorded on the lunar surface by the Chang’e 4 lander, with limits set to span a 2-fold range around the average dose rate (0.55 mGy/d). Results of this filtering were then exported to build a listing of spaceflight experiment datasets within the GeneLab data repository where their radiation exposure lies within this range of dose rates. Green numbers in table, datasets pre-processed by either the GeneLab uniform microarray or RNAseq analysis pipelines.

Article Snippet: These RR6 datasets were from five different tissues: dorsal skin, thymus, spleen, colon, and lung, respectively (i.e., GLDS 243, 244, 246, 247, and 248) and they were processed using the GeneLab RNAseq pipeline .

Techniques: Microarray