Tag: CNA

Copy Number Alteration and Loss or Heterozygosity

Copy Number Alteration and Loss or Heterozygosity 0 Dear all, I would appreciate having a piece of advice : Given the output from a copy number caller (FACETS, TitanCNA, Sequenza, Sclust) which criteria shall I apply on LogR and BAF (B allele frequency, minor allele frequency) in order to annotate…

Continue Reading Copy Number Alteration and Loss or Heterozygosity

LAMMPS simulation on silica with piston – LAMMPS Beginners

Hi everyone, I want to perform a simulation with a piston on fused silica. I have tried read the fused silica file, extend the dimensions of the simulation box and create atoms of the piston in the upper part of the box (blank region) but it gave an error. So…

Continue Reading LAMMPS simulation on silica with piston – LAMMPS Beginners

Legislator urges amendments to genetic data law

LEAKING TO CHINA: An academic said the source of genetic data leaks is the Chinese machines used for gene sequencing, raising national security concerns By Lee I-chia / Staff reporter Taiwan’s laws should be amended to help prevent genetic data from leaking to China and to establish a domestic genetic…

Continue Reading Legislator urges amendments to genetic data law

Generating variant read count matrix, total read count matrix and binary/ternary mutaion matrix for SNV from scDNAseq FASTQ files

Generating variant read count matrix, total read count matrix and binary/ternary mutaion matrix for SNV from scDNAseq FASTQ files 0 Leung et al., 2017 paper mentioned in Fig 1 data processing for CRC patients was sequenced as single cell for both SNV (with MDA WGA) and CNA (with DOP-PCR) parallelly….

Continue Reading Generating variant read count matrix, total read count matrix and binary/ternary mutaion matrix for SNV from scDNAseq FASTQ files

Copy number alteration features in pan-cancer homologous recombination deficiency prediction and biology

Data collection for HRD prediction model training and validation For the development of the HRD prediction model, 1854 samples (WGS data) from the pan-cancer analysis of whole genomes9 (PCAWG) and 560 breast cancer samples (SNP array data)16 are collected. To obtain a high-confidence training dataset of HRD, samples with BRCA1/2…

Continue Reading Copy number alteration features in pan-cancer homologous recombination deficiency prediction and biology

Treatment-Resistant Melanoma Genetic Signatures Emerge From Rapid Autopsy Analysis

NEW YORK — Researchers have uncovered genetic and gene expression changes in the organs of patients who died of precision treatment-resistant metastatic cutaneous melanoma. The patients had initially benefited from treatments such as MAPK inhibitors (MAPKi) and immune checkpoint blockade (ICB) but later acquired resistance and succumbed to the disease….

Continue Reading Treatment-Resistant Melanoma Genetic Signatures Emerge From Rapid Autopsy Analysis

WisecondorX (NIPT) np.array( ValueError)?

Hey there, I just started to work with WisecondorX for NIPT analysis. Everything went smooth until I get to the prediction step. When I use this command I get the error below; code; WisecondorX predict V350129651_L04_79.npz /data/storeData/project/1_Projects/NIPT/NIPT-REF/NIPT_REF_npz/niptref_mg.100kb.npz /data/storeData/project/1_Projects/NIPT/nipt_1/V350129651_L04_79 –plot –bed “[INFO – 2023-04-27 13:46:42]: Starting CNA prediction [INFO – 2023-04-27…

Continue Reading WisecondorX (NIPT) np.array( ValueError)?

Researchers discover pathway critical for lymphoma development

Activation of the polyamine-hypusine circuit is a hallmark of human cancer and of MYC-driven lymphoma. A, Copy number alterations (CNA) of EIF5A and EIFA2 (left), and of DHPS and DOHH (right) across different cancer types. Abbreviations for the indicated TCGA datasets are: prostate = PRAD; Liver Hepatocellular = LIHC; Diffuse…

Continue Reading Researchers discover pathway critical for lymphoma development

Convergent genomic diversity and novel BCAA metabolism in intrahepatic cholangiocarcinoma

Multi-omics analyses of the ICC samples Following multiregional sampling of primary ICC cases, we performed multi-omics analyses, including genome, transcriptome, proteome, and metabolome analysis. We used 10 (67 samples), 11 (88 samples), 10 (49 samples) and 10 (49 samples) ICC cases for WES, whole-transcriptome sequencing, proteomic analysis, and metabolomic analysis,…

Continue Reading Convergent genomic diversity and novel BCAA metabolism in intrahepatic cholangiocarcinoma

fitting a copy number profile to know CNV signatures

fitting a copy number profile to know CNV signatures 0 Dear all, I would like to ask for a suggestion on whether I could fit a CNA profile of a sample that I do have to known CNV signatures. I have used the package sigminer, that seems to focus entirely…

Continue Reading fitting a copy number profile to know CNV signatures

Google Data Cloud & AI Summit 2023: Highlights

The Google Data Cloud & AI Summit is an annual event and a part of Google’s digital cloud summit series. It focuses on revealing insights, solutions, business transformation opportunities, and the latest innovations in Google Data Cloud for AI, databases, data analytics, and business intelligence to enthusiasts, developers, business users,…

Continue Reading Google Data Cloud & AI Summit 2023: Highlights

Researchers discover native Taiwanese clam species

Taipei, April 11 (CNA) Taiwanese researchers have discovered a distinct new species of clam native to the Tamsui River that was previously thought to have originated in Japan. According to the Council of Agriculture, researchers stumble across the new species while working alongside the Tamsui Fisherman’s Association to restore clam…

Continue Reading Researchers discover native Taiwanese clam species

allelic copy number variation

allelic copy number variation 0 Dear all, I am working with sequenza output that has the following format – 1st line (www.ncbi.nlm.nih.gov/pmc/articles/PMC4269342/ ; Sequenza estimates the allelic specific copy numbers). How can I transform this output into numerical allele specific copy-numbers shown on the 2nd line ? chromosome position base.ref…

Continue Reading allelic copy number variation

CNA plots with gene names using GISTIC

CNA plots with gene names using GISTIC 0 I have the GISTIC plots with amplification and deletion for my data but the plots show chromosome region where as I want to have gene names on the peak positions. I have attach a demo diagram below. visualization CNA GISTIC • 72…

Continue Reading CNA plots with gene names using GISTIC

Your Guide To Generative AI Support In Vertex AI

Okay, so I initially suggested that I deliver the content of this blog as an interpretive dance video. My suggestion was turned down, and I’m sure you’re as disappointed as I am. But dancing or not, I’m really excited about Generative AI support in Vertex AI.  Vertex AI was launched…

Continue Reading Your Guide To Generative AI Support In Vertex AI

alelle – specific CNA/LOH

alelle – specific CNA/LOH 0 Dear all, I would appreciate having your help on the following : I would like to use a software that is called scarHRD to measure the degree of homologous recombination deficiency (HRD) in cancer cells. The link to the scarHRD package is : github.com/sztup/scarHRD ScarHRD…

Continue Reading alelle – specific CNA/LOH

Using Copy Number Alterations detected in other studies for the same tumor cell line

Using Copy Number Alterations detected in other studies for the same tumor cell line 0 Hello everybody, It is my first time working with cancer genomes and I have some doubts. I found this study in which they provide a lot of different sequencing data for the cell line HCC1395,…

Continue Reading Using Copy Number Alterations detected in other studies for the same tumor cell line

Bioconductor – ChAMPdata

DOI: 10.18129/B9.bioc.ChAMPdata   Data Packages for ChAMP package Bioconductor version: Release (3.16) Provides datasets needed for ChAMP including a test dataset and blood controls for CNA analysis. Author: Yuan Tian [ctb,aut], Tiffany Morris [cre,aut], Lee Stirling [ctb] and Andrew Teschendorff [ctb] Maintainer: Yuan Tian <champ450k at gmail.com> Citation (from within…

Continue Reading Bioconductor – ChAMPdata

Obtain the GenomicRanges from segmented CNA data and the corresponding TSS for EnrichedPlot

I want to plot the EnrichedHeatmap using the GenomicRanges of my CNA data. The normalizeToMatrix function returned mat1, which is filled with 0, resulting in Error: You should have at least two distinct break values. when I try to plot it. library(EnrichedHeatmap) library(GenomicRanges) library(data.table) library(ChIPseeker) library(tibble) library(AnnotationHub) library(IlluminaHumanMethylation450kanno.ilmn12.hg19) library(TxDb.Hsapiens.UCSC.hg19.knownGene) txdb…

Continue Reading Obtain the GenomicRanges from segmented CNA data and the corresponding TSS for EnrichedPlot

Generative AI by Google Cloud the next move in AI wars

Generative AI, that is, the ability to create text, images, code, videos, audio and more from simple natural language prompts is poised to welcome a new way of transforming user experience and how people interact with information. Google Cloud has announced that its new generative AI capabilities are now available…

Continue Reading Generative AI by Google Cloud the next move in AI wars

Google Cloud brings generative AI to developers, businesses

Generative AI is poised to usher in a new wave of interactive, multimodal experiences that transform how we interact with information, brands, and one another. Harnessing the power of decades of Google’s research, innovation, and investment in AI, Google Cloud is bringing businesses and governments the ability to generate text,…

Continue Reading Google Cloud brings generative AI to developers, businesses

Google unveils AI-powered ‘magic wand’ for Workspace

Google on Tuesday unveiled a ‘magic wand’ that creates marketing blogs, training plans and other text documents for users. The announcement is the tech giant’s new generative AI system rolling out to Google Workspace, adding new capabilities to Docs, Sheets, Slides and Gmail. The system will be able to summarize message threads…

Continue Reading Google unveils AI-powered ‘magic wand’ for Workspace

Interpreting ASCAT CNV output

Interpreting ASCAT CNV output 1 Hello, I have two queries w.r.t ASCAT CNV data: How does one go about getting the total copy number for a given locus or chromosome from the ASCAT CNV.output results. What is the optimal way to filter the dataset to reduce the noise? I would…

Continue Reading Interpreting ASCAT CNV output

Unexpected discrepancy between Ka/Ks (seqinr) and dn/ds (ape)

Ka/Ks and dn/ds are usually considered to be the same thing (also named ω). However, estimation of KaKs using seqinr and dnds using ape give different results. The two estimators refer to the same paper for details, although seqinr also refer to other papers. Calling dnds function, we cna understand…

Continue Reading Unexpected discrepancy between Ka/Ks (seqinr) and dn/ds (ape)

KEGG ENZYME: 1.7.1.4

Entry EC 1.7.1.4                  Enzyme                                  Name nitrite reductase [NAD(P)H];nitrite reductase (reduced nicotinamide adenine dinucleotide (phosphate));assimilatory nitrite reductase (ambiguous);nitrite reductase [NAD(P)H2];NAD(P)H2:nitrite oxidoreductase;nit-6 (gene name) Class Oxidoreductases;Acting on other nitrogenous compounds as donors;With NAD+ or NADP+ as acceptorBRITE hierarchy Sysname ammonia:NAD(P)+ oxidoreductase Reaction(IUBMB) NH3 + 3 NAD(P)+ + 2 H2O = nitrite + 3 NAD(P)H…

Continue Reading KEGG ENZYME: 1.7.1.4

Impact of gene alterations on clinical outcome in young adults with myelodysplastic syndromes

In general, more than half of MDS patients are diagnosed at age 75 years or older, and the incidence rate of MDS in patients under 50 years of age is as low as less than 1 per 100,000)3. The median number of gene mutations in patients with MDS has been found to…

Continue Reading Impact of gene alterations on clinical outcome in young adults with myelodysplastic syndromes

Bridging biological cfDNA features and machine learning approaches: Trends in Genetics

Early detection (pancreatic cancer) cfMeDIP-seq, 5hmC sequencing LR elastic-net Hierarchical clustering, t-SNE, LR with elastic-net penalization Methylation (5mC-5hmC) 208 (72/136) 24-feature 5mC, 27-features 5hmC, 51-features combined model SML, UML Combined 5mC and 5hmC AUC of 0.997 (sensitivity 0.938, specificity 0.955) Median total reads: 17.4 M, 0.8 nonduplicate mapping rate pms.cd120.com/PDAC/index.html…

Continue Reading Bridging biological cfDNA features and machine learning approaches: Trends in Genetics

Suitable anticancer agent for the lungs.

Introduction Cancer is a large group of diseases that have the same basic properties that are caused by cell division or uncontrolled cell proliferation. This irregular process of division produces a mass of cells in an organ or tissue, which leads to the formation of tumours.1,2 Cancer became one of…

Continue Reading Suitable anticancer agent for the lungs.

Scientist II, Bioinformatics Job Opening in South Plainfield, NJ at PTC Therapeutics, Inc.

Job Posting for Scientist II, Bioinformatics at PTC Therapeutics, Inc. Job Description Summary: The Scientist II, Bioinformatics is responsible for planning and performing scientific experiments that contribute to PTC’s research and drug discovery activities. The Scientist II is also responsible for communicating experimental results to his/her supervisor and…

Continue Reading Scientist II, Bioinformatics Job Opening in South Plainfield, NJ at PTC Therapeutics, Inc.

Researchers develop new machete technique to slice into cancer genome and study copy number alterations — ScienceDaily

MACHETE is a new CRISPR-based technique developed by researchers at the Sloan Kettering Institute (SKI) to study large-scale genetic deletions efficiently in laboratory models. People are already calling it the Machete Paper. Still, lead authors Francisco “Pancho” Barriga and Kaloyan Tsanov of the Sloan Kettering Institute don’t want the name…

Continue Reading Researchers develop new machete technique to slice into cancer genome and study copy number alterations — ScienceDaily

Phenotypic plasticity and genetic control in colorectal cancer evolution

Sample preparation and sequencing The method of sample collection and processing is described in a companion article (ref. 23). Sequencing and basic bioinformatic processing of DNA-, RNA- and ATAC-seq data are included there as well. Gene expression normalization and filtering The number of non-ribosomal protein-coding genes on the 23 canonical chromosome pairs…

Continue Reading Phenotypic plasticity and genetic control in colorectal cancer evolution

How can you score CNV for each sample (with TCGA data)?

How can you score CNV for each sample (with TCGA data)? 0 Hi, I’m looking at TCGA CNV data, and trying to get a sense of how copy number altered each sample is. TCGA gives “Segment_Mean” values for varying sized regions of the genome for each sample, which to my…

Continue Reading How can you score CNV for each sample (with TCGA data)?

Group comparison of CNA between primary and metastatic samples

Group comparison of CNA between primary and metastatic samples 1 Dear all, I am trying to find significantly different CNA between human cancer primary samples and their metastatic samples. My data is from WGS and I have already segmentaiton file. GISTIC2.0 provides significant CNA evet in a cohort, but does…

Continue Reading Group comparison of CNA between primary and metastatic samples

Analytics Insight Announces ‘Top 10 Data Science Leaders of 2021’

SAN JOSE, Calif. & HYDERABAD, India, November 24, 2021–(BUSINESS WIRE)–Analytics Insight has named ‘Top 10 Data Science Leaders of 2021’ in its November magazine issue. The issue focuses on trailblazing leaders who are changing the industry dynamics with top-notch data science skills. The magazine issue recognizes ten leaders who are…

Continue Reading Analytics Insight Announces ‘Top 10 Data Science Leaders of 2021’

Genome-Wide cfDNA Analysis Detects Therapy Response in B-Cell Lymphoma – Hematology

Image: The Bio-Rad QX200 Droplet Digital PCR (ddPCR) reader (Photo courtesy of University of California Santa Barbara) Diffuse large B-cell lymphoma (DLBCL) is the most common, aggressive type of non-Hodgkin lymphoma. Although 50% to 60% of individuals achieve cure with chemoimmunotherapy, outcomes are poor for relapsed/refractory disease. Chimeric antigen receptor…

Continue Reading Genome-Wide cfDNA Analysis Detects Therapy Response in B-Cell Lymphoma – Hematology

Benchmarking pipelines for subclonal deconvolution of bulk tumour sequencing data

Somatic point mutation calling suggests Mutect2 is best for subclonal variants We applied four somatic variant callers (Mutect211, Strelka212, VarScan213 and Lancet14) to a highly mutated tumour dataset (S3R3) at 100% tumour purity across all sequencing depths. Runtimes differed substantially between methods, with Strelka2 being fastest and Mutect2 taking longest…

Continue Reading Benchmarking pipelines for subclonal deconvolution of bulk tumour sequencing data

Copy Number to Log2_ratio for autosomal

Copy Number to Log2_ratio for autosomal 0 Hi, I want to transform some ASCAT data into log2_r values. The file contains at total copy number column. I would then take fold ratio of the total copy number versus the natural ploidy, correct? Can I assume the natural ploidy for all…

Continue Reading Copy Number to Log2_ratio for autosomal

Get Allele specific copy number regions from WGS data using ASCAT?

Get Allele specific copy number regions from WGS data using ASCAT? 0 Hi, I have some paired samples(normal vs. tumour) and want to do allele specific CNA analysis. can you help me to check if I use the right pipeline? I use bcftools mpileup and call to call snp from…

Continue Reading Get Allele specific copy number regions from WGS data using ASCAT?

Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model | BMC Biology

Organoid culture of small intestinal cells and lentiviral transduction C57BL/6J mice and BALB/cAnu/nu immune-deficient nude mice were purchased from CLEA Japan (Tokyo, Japan). The small intestine was harvested from wild-type male C57BL/6J mice at 3–5 weeks of age (Additional file 1: Figure S9A). Crypts were purified and dissociated into single cells,…

Continue Reading Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model | BMC Biology

KEGG ENZYME: 1.14.12.17

Entry EC 1.14.12.17               Enzyme                                  Name nitric oxide dioxygenase Class Oxidoreductases;Acting on paired donors, with incorporation or reduction of molecular oxygen;With NADH or NADPH as one donor, and incorporation of two atoms of oxygen into the other donorBRITE hierarchy Sysname nitric oxide,NAD(P)H:oxygen oxidoreductase Reaction(IUBMB) 2 nitric oxide + 2 O2 + NAD(P)H =…

Continue Reading KEGG ENZYME: 1.14.12.17

Single cell DNA sequencing reveals punctuated and gradual clonal evolution in hepatocellular carcinoma

Footnotes Grant support This work is jointly supported by National Natural Science Foundation of China (82173035, 81802813,82030079, 81972656, 81988101, and 81902401), the National Science and Technology Major Project of China (2018ZX10723204), the Michigan Medicine and Peking University Health Science Center Joint Institute for Translational and Clinical Research (BMU2020JI005), Natural Science…

Continue Reading Single cell DNA sequencing reveals punctuated and gradual clonal evolution in hepatocellular carcinoma

Predicting and characterizing a cancer dependency map of tumors with deep learning

INTRODUCTION The development of novel cancer therapies requires knowledge of specific biological pathways to target individual tumors and eradicate cancer cells. Toward this goal, the landscape of genetic vulnerabilities of cancer, or the cancer dependency map, is being systematically profiled. Using RNA interference (RNAi) loss-of-function screens, Marcotte et al. (1),…

Continue Reading Predicting and characterizing a cancer dependency map of tumors with deep learning

Difference between linear and log2 CNA values

Difference between linear and log2 CNA values 0 Hi, Simply what the title is asking. Cbioportal allows for either Log2 cna values or linear cna values. Is this simply how the values were normalized? Is there a way to differentiate between the two value types by seeing the numbers? Thanks!…

Continue Reading Difference between linear and log2 CNA values

Copy number differences between groups

Copy number differences between groups 0 Analogous to differential expression with RNA data, is there a statistic or tool to analyze the frequency of copy number alterations between two groups? I had imagined this to be a Chi-square performed like 20,000 times (each gene) to see if that particular gene…

Continue Reading Copy number differences between groups