The largest database of trusted experimental protocols

30 protocols using snp 6

1

Multiomics Analysis of Glioblastoma Transcriptome

Check if the same lab product or an alternative is used in the 5 most similar protocols
In TCGA datasets, RNAseq data (level 3, RSEM‐normalized data), methylation array data (Illumina Human Methylation 450) and CNV data (Affymetrix SNP 6.0) of GBMs were downloaded from the NIH National Cancer Institute GDC Data Portal (https://portal.gdc.cancer.gov/). Two external independent transcriptome datasets of GBMs were used for validation, namely, the Chinese Glioma Genome Atlas RNA sequencing dataset (CGGA data) and GEO microarray datasets GSE16011, as well as their corresponding clinical information.
A total of 404 immuno‐related human genes, including 4 immune response types, 24 immune cells, and 22 immune response categories, that were curated from the nCounter® PanCancer Immune Profiling Panel (NanoString) were implemented as candidate genes in this study. Detailed annotations for these 404 genes are listed in Table S2.
+ Open protocol
+ Expand
2

Breast Tissue eQTL Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
eQTL analyses were conducted in two studies: 123 normal breast tissue and 254
breast tumours from women in the Norwegian Breast Cancer Study (NBCS); all women
were of Caucasian origin. The 123 normal breast tissue is a cohort of expression
data from normal breasts biopsy (n=74), reduction plastic surgery
(n=37) and adjacent normal (n=12) (adjacent to tumour).
Correlations between the two most likely causative SNPs (rs4442975 and
rs6721996) and expression levels of nearby genes (500 kb upstream and
downstream of the SNPs) were assessed using a linear regression model in which
an additive effect on expression level was assumed for each copy of the rare
allele. Calculations were carried out using the eMap library in R ( www.bios.unc.edu/~weisun/software/eMap).
The second eQTL analysis was based on 135 adjacent normal breast samples from
women of Caucasian origin in the METABRIC study27 (link). Matched gene
expression (Illumina HT-12 v3 microarray) and germline SNP data that were either
genotyped (Affymetrix SNP 6.0) or imputed (1000 Genomes Project, March 2012 data
using IMPUTE version 2.0) were used. Statistical methods were identical to the
NBCS analysis.
+ Open protocol
+ Expand
3

Somatic Lesions in Prostate Cancer

Check if the same lab product or an alternative is used in the 5 most similar protocols
Whole-exome or whole-genome sequencing data from prostate cancer tissue samples was queried for early somatic lesions1 , 9 (link), 11 (link). Patients with relevant clinical annotations (age, PSA), functional variant genotypes and lesion status for SPOP (N = 539, 12.1% mutated), TMPRSS2-ERG (N = 451, 47.2% rearranged) and FOXA1 (N = 520, 5.4% mutated) were included in the study (N total = 539, Supplementary Data 4). Variants genotypes were determined using standard APT tools 1.16.1 pipeline from Affymetrix SNP 6.0. As all data sets used clinically localized prostate cancer cases, none of these data sets have meaningful clinical follow up data, which would require ten or more years.
+ Open protocol
+ Expand
4

Cell Culture Conditions for Ba/F3 Cell Lines

Check if the same lab product or an alternative is used in the 5 most similar protocols
NIH-3T3 cells were cultured in DMEM supplemented with 10% fetal calf serum (FCS) and 1% penicillin/streptomycin (PS). Parental Ba/F3 cells were cultured in RPMI supplemented with 10% FCS and 1% PS supplemented with 10 ng/mL IL3. Ba/F3 ERBB2YF/ ERBB3 wt cells were a kind gift from Kevan M. Shokat. Ba/F3 ERBB2YF/ ERBB3 wt cells were cultured in RPMI (Gibco) supplemented with 10% FCS and 1% PS supplemented with 6.25 ng/mL recombinant human NRG1. Human Neuregulin-1 (hNRG-1) from Cell Signaling Technology No. 5218 was used for the cell culture, this recombinant human NRG-1 Thr176-Lys238 (Accession No. NP_001153480) was produced in Escherichia coli cells. NP_001153480 is the NCBI accession number for isoform HRG-beta2b. The cell lines have been authenticated via genotyping (SNP 6.0; Affymetrix) or verified by STR profiling at the Institute for Forensic Medicine of the University Hospital of Cologne. All cells were grown in a humidified incubator at 37°C and 5% CO2 and tested regularly for mycoplasma infection.
+ Open protocol
+ Expand
5

Tumor Characterization and Profiling

Check if the same lab product or an alternative is used in the 5 most similar protocols
ER status, as well as other tumor characteristics (tumor grade, stage, and size) were obtained from the medical records. RNA and DNA were extracted for transcriptional and genomic profiling on the Illumina Human v3 microarray and Affymetrix SNP 6.0 platforms, respectively36 (link). Tumors were classified for TP53 functional status (mutant-like/wildtype-like) using the RNA-based TP53 signature32 (link) and for PAM50 intrinsic subtype (basal-like/non-basal-like) using a research version of the PAM50 predictor30 (link),33 (link).
+ Open protocol
+ Expand
6

SNP Array-Based Copy Number Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
SNP array data were available for 148 patients from this cohort, using SNP6.0 (Affymetrix, Santa Clara, CA) or Infinium CytoSNP-850K (Ilumina Inc., San Diego, CA). SNP arrays were analysed using Nexus Copy Number 10 (Bio-discovery, El Segundo, CA), as previously reported [37 (link)].
+ Open protocol
+ Expand
7

Integrative Genomic Analysis of Cancer

Check if the same lab product or an alternative is used in the 5 most similar protocols
We used data for 211 normal breast tissue samples and 99 normal ovarian tissue samples from the Genotype-Tissue Expression (GTEx) project (version 7 release).19 (link) Germline genotypes in the GTEx data had been called from whole-genome sequencing (Illumina HiSeq X), and gene expression was profiled using RNA-sequencing (Illumina TruSeq). We also used data from 681 breast cancer20 (link) and 295 high-grade serous ovarian cancer (HGSOC)21 (link) cases from The Cancer Genome Atlas (TCGA) network. Germline genotypes in the TCGA data had been called from genotyping arrays (Affymetrix SNP 6.0), and gene expression was profiled using RNA-sequencing (Illumina HiSeq 2000). Imputation of TCGA germline genotypes using the 1000 Genomes version 5 reference panel was performed as described previously.22 (link),23 (link) TCGA sample sizes reported here refer to only those samples that had >95% European ancestry. Ancestry was estimated using the Local Ancestry in adMixed Populations tool (LAMP version 2.5).24 (link) Downstream PrediXcan modeling (described below) used variants imputed with quality > 0.8 that had a minor allele frequency > 5% in TCGA datasets.
+ Open protocol
+ Expand
8

Identifying Copy Number Aberrations in CRC

Check if the same lab product or an alternative is used in the 5 most similar protocols
Discovery of DNA copy number aberrations associated with PFS under the three drug regimens was performed on the aCGH data from the CAIRO (CAP and CAPIRI) and CAIRO2 (CAPOX-B) samples. For biological validation, the association of DNA copy number aberrations of the genes involved with mRNA expression was evaluated using publicly available data from TCGA15 (link)46 (link). This data set consisted of 141 CRCs for which both DNA copy number data (obtained with the Affymetrix SNP 6.0 platform) and mRNA expression data (obtained with the Agilent G4502A platform) were available.
+ Open protocol
+ Expand
9

Copy Number Analysis of DIPG

Check if the same lab product or an alternative is used in the 5 most similar protocols
Copy number analysis was conducted for 40 DIPG samples using SNP6.0 (Affymetrix, Santa Clara, CA). Digestion, labeling and hybridization of DNA were performed by The Centre for Applied Genomics at the Hospital for Sick Children or at the Microarray Centre at the University Health Network. CEL data was analyzed for copy number alterations using segmentation tool and hidden Markov model in Partek Genomics Suite (v6.6) (Partek Incorporated, St. Louis, MO) and Genotyping Console 4.1 (GTC4.1; Affymetix) as previously described9 (link).
+ Open protocol
+ Expand
10

TCGA Genome Data Analysis Pipeline

Check if the same lab product or an alternative is used in the 5 most similar protocols
We used open source data generated by TCGA genome data analysis centers [19 (link)]. Data on methylation 450K were downloaded from the TCGA Data Portal (https://tcga-data.nci.nih.gov/tcga/tcgaHome2.jsp). Data on CNV and RNA expression were downloaded from the Broad genome data analysis center Firehose website (http://gdac.broadinstitute.org/). Data on RNA expression of XIST and clinical data were gathered using the CGDS-R package, which is a package of R for querying the Cancer Genomics Data Server and is hosted by the Computational Biology Center at Memorial-Sloan-Kettering Cancer Center [21 ]. The beta values for DNA methylation status were estimated using the Illumina Infinium Human Methylation 450K arrays. The beta value was calculated as an estimate of the ratio of intensities between methylated and unmethylated alleles. Segmented copy number was estimated by log2 of the ratio of total intensity of the tumor and the normal tissue using Affymetrix SNP6.0. Normalized RNA-Seq by expectation maximization (RSEM) were used as an estimate for mRNA expression [22 (link)]. Detailed information about the patients and experiment methods have been described elsewhere [19 (link)].
+ Open protocol
+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required

Sign up now

Revolutionizing how scientists
search and build protocols!