Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Next-generation sequencing analysis to compare expression pattern of relapse and baseline MDS samples

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE136816 | GEO | 2022/01/02

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "CMP pattern" MDS samples

Project description:Transcriptional changes occurring in the expanding LT-HSC population of "CMP pattern" MDS patients with blast expansion post-HMA failure were compared with the transcriptional profile of untreated (baseline) "CMP pattern" MDS patients.

2022-01-03 | GSE136815 | GEO

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "GMP pattern" MDS samples

Project description:Transcriptional changes occurring in the expanding LMPP population of "GMP pattern" MDS patients with blast expansion post-HMA failure were compared with the transcriptional profile of untreated (baseline) "GMP pattern" MDS patients.

2022-01-03 | GSE136812 | GEO

Next-generation sequencing analysis to compare expression pattern of relapse and baseline MDS samples

Project description:Next-generation sequencing analysis to compare expression pattern of relapse and baseline MDS samples

| PRJNA563722 | ENA

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "CMP pattern" MDS samples

Project description:Next-generation sequencing analysis to compare expression pattern of relapse and baseline "CMP pattern" MDS samples

| PRJNA563724 | ENA

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "GMP pattern" MDS samples

Project description:Next-generation sequencing analysis to compare expression pattern of relapse and baseline "GMP pattern" MDS samples

| PRJNA563710 | ENA

Do next-generation sequencing results drive diagnostic and therapeutic decisions in MDS?

Project description:This article has a companion Point by Thol and Platzbecker.

| S-EPMC6855105 | biostudies-literature

Accurate detection of subclonal variants in paired diagnosis-relapse acute myeloid leukemia samples by next generation Duplex Sequencing.

Project description:Mutations characterize diverse human cancers; there is a positive correlation between elevated mutation frequency and tumor progression. One exception is acute myeloid leukemia (AML), which has few clonal single nucleotide mutations. We used highly sensitive and accurate Duplex Sequencing (DS) to show now that AML, in addition, has an extensive repertoire of variants with low allele frequencies, < 1%, which is below the accurate detection limit of most other sequencing methodologies. The subclonal variants are unique to each individual and change in composition, frequency, and sequence context from diagnosis to relapse. Their functional significance is apparent by the observation that many are known variants and cluster within functionally important protein domains. Subclones provide a reservoir of variants that could expand and contribute to the development of drug resistance and relapse. In accord, we accurately identified subclonal variants in AML driver genes NRAS and RUNX1 at allele frequencies between 0.1% and 0.3% at diagnosis, which expanded to comprise a major fraction (14-53%) of the blast population at relapse. Early and accurate detection of subclonal variants with low allele frequency thus offers the opportunity for early intervention, prior to detection of clinical relapse, to improve disease outcome and enhance patient survival.

| S-EPMC9014797 | biostudies-literature

Next Generation Protein Sequencing

Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.

2017-04-03 | PXD003804 | Pride

Pattern Recognition on Read Positioning in Next Generation Sequencing.

Project description:The usefulness and the utility of the next generation sequencing (NGS) technology are based on the assumption that the DNA or cDNA cleavage required to generate short sequence reads is random. Several previous reports suggest the existence of sequencing bias of NGS reads. To address this question in greater detail, we analyze NGS data from four organisms with different GC content, Plasmodium falciparum (19.39%), Arabidopsis thaliana (36.03%), Homo sapiens (40.91%) and Streptomyces coelicolor (72.00%). Using machine learning techniques, we recognize the pattern that the NGS read start is positioned in the local region where the nucleotide distribution is dissimilar from the global nucleotide distribution. We also demonstrate that the mono-nucleotide distribution underestimates sequencing bias, and the recognized pattern is explained largely by the distribution of multi-nucleotides (di-, tri-, and tetra- nucleotides) rather than mono-nucleotides. This implies that the correction of sequencing bias needs to be performed on the basis of the multi-nucleotide distribution. Providing companion software to quantify the effect of the recognized pattern on read positioning, we exemplify that the bias correction based on the mono-nucleotide distribution may not be sufficient to clean sequencing bias.

| S-EPMC4907491 | biostudies-literature

Detecting selective sweeps from pooled next-generation sequencing samples.

Project description:Due to its cost effectiveness, next-generation sequencing of pools of individuals (Pool-Seq) is becoming a popular strategy for characterizing variation in population samples. Because Pool-Seq provides genome-wide SNP frequency data, it is possible to use them for demographic inference and/or the identification of selective sweeps. Here, we introduce a statistical method that is designed to detect selective sweeps from pooled data by accounting for statistical challenges associated with Pool-Seq, namely sequencing errors and random sampling among chromosomes. This allows for an efficient use of the information: all base calls are included in the analysis, but the higher credibility of regions with higher coverage and base calls with better quality scores is accounted for. Computer simulations show that our method efficiently detects sweeps even at very low coverage (0.5× per chromosome). Indeed, the power of detecting sweeps is similar to what we could expect from sequences of individual chromosomes. Since the inference of selective sweeps is based on the allele frequency spectrum (AFS), we also provide a method to accurately estimate the AFS provided that the quality scores for the sequence reads are reliable. Applying our approach to Pool-Seq data from Drosophila melanogaster, we identify several selective sweep signatures on chromosome X that include some previously well-characterized sweeps like the wapl region.

| S-EPMC3424412 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data