Using control genes to correct for unwanted variation in microarray data. - Wikidata - awgldk - TriplyDB

Using control genes to correct for unwanted variation in microarray data.

Using control genes to correct for unwanted variation in microarray data.

http://www.wikidata.org/entity/Q34078893

about

Practical impacts of genomic data "cleaning" on biological discovery using surrogate variable analysis Comparability and reproducibility of biomedical data Normalizing RNA-sequencing data by modeling hidden covariates with prior knowledge.MSPrep--summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic data.Covariance adjustment for batch effect in gene expression data Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments.Variation-preserving normalization unveils blind spots in gene expression profiling.Normalization of RNA-seq data using factor analysis of control genes or samples Detecting and correcting systematic variation in large-scale RNA sequencing data Comprehensive analysis of DNA methylation data with RnBeads.svaseq: removing batch effects and other unwanted noise from sequencing data Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.Functional normalization of 450k methylation array data improves replication in large cancer studies.Statistical methods for handling unwanted variation in metabolomics data Removing unwanted variation in a differential methylation analysis of Illumina HumanMethylation450 array data.quantro: a data-driven approach to guide the choice of an appropriate normalization method How data analysis affects power, reproducibility and biological insight of RNA-seq studies in complex datasets Correcting gene expression data when neither the unwanted variation nor the factor of interest are observed Limitations of empirical calibration of p-values using observational data Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction.Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data.The contribution of cell cycle to heterogeneity in single-cell RNA-seq data.Identifying and removing the cell-cycle effect from single-cell RNA-Sequencing data.Accessory subunits are integral for assembly and function of human mitochondrial complex I.Comparison of different cell type correction methods for genome-scale epigenetics studies.IQRray, a new method for Affymetrix microarray quality control, and the homologous organ conservation score, a new benchmark method for quality control metrics.Fast and robust adjustment of cell mixtures in epigenome-wide association studies with SmartSVA Accounting for cellular heterogeneity is critical in epigenome-wide association studies.Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.Cautionary Note on Using Cross-Validation for Molecular Classification.Differential expression analysis for RNAseq using Poisson mixed models.Volcano plots in analyzing differential expressions with mRNA microarrays.Improved moderation for gene-wise variance estimation in RNA-Seq via the exploitation of external information.Heterogeneity of gene expression in murine squamous cell carcinoma development-the same tumor by different means.Protein signatures correspond to survival outcomes of AJCC stage III melanoma patients.Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.The functional consequences of variation in transcription factor binding.Increasing consistency of disease biomarker prediction across datasets.Evaluation of bias-variance trade-off for commonly used post-summarizing normalization procedures in large-scale gene expression studies.Integrated network analysis and logistic regression modeling identify stage-specific genes in Oral Squamous Cell Carcinoma

P2860

Q28607690-BFE55F6F-5A17-4E25-981A-1ECE65AAE30A Q28677246-E5B4CEB9-2B75-4E6B-9C3A-4687BBEC7BD1 Q30656581-4EA5092B-18AA-44FB-8DEF-2121C859C23E Q30686321-B99309B6-E2A5-427F-9E1E-6C8F2FF0D8B1 Q30790283-C380A4EF-228D-4E07-9C16-E472CD1D0D91 Q30829447-02015879-AE1D-464E-9296-D399535C322F Q30841312-36E3E45B-04B9-4822-B5DE-98D8705C1D68 Q30844396-1C8579AD-78E7-4D03-A2C6-0B939BC9D9BE Q30844399-299CF31B-1130-4AE9-A60C-A0E9C6F642FA Q30855530-1DE8F697-6230-4DC2-83F0-24331A18D657 Q30858102-7091122F-CDA3-4C08-83F0-9D2C3DCBC73D Q30884891-DBB2FDFF-E332-4486-9582-B978BA653F38 Q30884917-82191A96-F445-40CF-A0DB-FB4695FEBC96 Q30894998-108CB614-18D5-4641-879B-82F1B6B2B3D4 Q30954756-752D5A90-DB31-4396-AF15-EE0A9E9B4F83 Q30964731-9512E5E2-48BF-47E5-A451-ED0BA91994BA Q30982167-FE292F05-8AE1-4A1F-B496-32A708847910 Q30988074-C75E9ADE-027B-4557-8F9D-62B87C3D9BD7 Q31057420-EF2257AF-1926-492A-9B2E-59FA0A079CC5 Q31081473-C64F8F15-3512-437D-8343-AA5951CDC2F8 Q31106182-80393227-4543-40C2-807C-1F2C3EFC9095 Q31106823-C40EB0C7-839A-45C0-9C6C-C2462C93B32E Q31133242-ADD12252-7E2A-41C5-AE29-4A3DE5CD18EF Q32884468-DEF5195D-F854-4DCE-B4EC-647A13AB5D26 Q33564415-76C7026C-A803-4215-8AD3-4C55D6021CEE Q33593372-ECEA1F60-0E73-4BCB-A20E-EFB87F636B5E Q33733669-4347D1B8-BCC7-49EE-8855-A93D24113F49 Q33742004-9E2BDA7B-0EC0-4E39-9BE2-D05A49BE45C1 Q33812192-D394CE9A-C238-4372-BE08-A9F8020F38EB Q33816989-55B4D50A-EB6D-405F-A9BF-4CD2DB914FE3 Q33878991-7478E01E-FCF2-4A27-87EB-60A9F5EAAA21 Q34306646-386E2C66-2334-4777-99D7-B525AC131EE1 Q34569594-475F32C1-0B0B-411E-BE5A-99BC5B90220A Q34634007-49D5C4E0-6317-498B-97E0-9DE3FCD9A265 Q34842139-27C85163-D97D-4F42-AE14-EA2240810982 Q34986607-668833D5-F2CC-4863-AC99-313573DB44B1 Q35112922-40F57798-086C-4625-B202-335326BBE2F2 Q35150852-0D99DD55-DAEC-49F3-B186-3A38D64DE85B Q35190389-7C8EF03B-83E0-4DF7-B8FC-DB5E2447630D Q35693163-0C110964-14AA-4971-9321-724B01BA2AA8

P2860

Using control genes to correct for unwanted variation in microarray data.

http://www.wikidata.org/entity/Q34078893

description

2011 nî lūn-bûn

@nan

2011 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

@hyw

2011 թվականի նոյեմբերին հրատարակված գիտական հոդված

@hy

2011年の論文

@ja

2011年論文

@yue

2011年論文

@zh-hant

2011年論文

@zh-hk

2011年論文

@zh-mo

2011年論文

@zh-tw

2011年论文

@wuu

name

Using control genes to correct for unwanted variation in microarray data.

@ast

Using control genes to correct for unwanted variation in microarray data.

@en

Using control genes to correct for unwanted variation in microarray data.

@nl

type

label

Using control genes to correct for unwanted variation in microarray data.

@ast

Using control genes to correct for unwanted variation in microarray data.

@en

Using control genes to correct for unwanted variation in microarray data.

@nl

prefLabel

Using control genes to correct for unwanted variation in microarray data.

@ast

Using control genes to correct for unwanted variation in microarray data.

@en

Using control genes to correct for unwanted variation in microarray data.

@nl

P1433

Q34078893-9B4989FC-A831-4136-886F-CA3DEF6E8D42

P1476

Q34078893-D5373D86-44B6-45EE-8FBF-6DA366AC0C7D

P2093

Q34078893-79DF4CC5-8591-4E55-9B7E-1B4143BED0CC

P2860

Q34078893-15057078-69E3-4A33-8785-C58501272C64

Q34078893-23490FE4-B850-4085-9F01-47252FF46C9C

Q34078893-25F2A003-68BC-4605-B49A-20FDC96A4443

Q34078893-28FBD8B5-9516-43A0-8082-8F251D0D8489

Q34078893-33B160C0-5D29-4792-BDEA-5D898AC44DA4

Q34078893-34075541-4216-489B-811F-31DD4CA175EB

Q34078893-41BD56EC-D53D-4E18-8D79-1D4022AAD888

Q34078893-5BF5EC9B-AD6D-4E24-AC32-47A770246EC2

Q34078893-60F18D91-A9A2-4C6C-B311-8F0659819F5E

Q34078893-7116A279-D860-418C-8A35-6A9FE3287F62

P304

Q34078893-6D6572C0-2275-4225-8B10-01C522D1814C

P31

Q34078893-6BC99228-A35E-4C54-84BC-8833BCFA1B37

P356

Q34078893-3466D879-9C15-45AF-AE04-B63E77257BE5

P433

Q34078893-5B342925-DDCD-4DE6-9862-85DEDF274A49

P478

Q34078893-6031C43E-C6EF-4CD8-83CE-797D4C39A07F

P50

Q34078893-3960B26B-2BAD-4456-BDB3-B75888EFFADE

P577

Q34078893-6187EE8C-950B-45A7-955C-78D51F8FEC47

P5875

Q34078893-47B1F2F9-ABBE-46B1-B3B5-ACCB3D916C8A

P698

Q34078893-3007DCA8-D794-49C3-BE5E-B9585E3BD4FC

P932

Q34078893-158B0E52-6D37-461A-B651-A6BAB5BBBB7F

P356

P1433

P1476

Using control genes to correct for unwanted variation in microarray data.

@en

P2093

Johann A Gagnon-Bartsch

http://www.w3.org/2001/XMLSchema#string

P2860

Gender-specific gene expression in post-mortem human brain: localization to sex chromosomes

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

Linear models and empirical bayes methods for assessing differential expression in microarray experiments

Summaries of Affymetrix GeneChip probe level data

Principal components analysis corrects for stratification in genome-wide association studies

Exploration, normalization, and summaries of high density oligonucleotide array probe level data

Capturing heterogeneity in gene expression studies by surrogate variable analysis

Adjusting batch effects in microarray expression data using empirical Bayes methods

Singular value decomposition for genome-wide expression data processing and modeling

Tackling the widespread and critical impact of batch effects in high-throughput data

P304

539-552

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1093/BIOSTATISTICS/KXR034

http://www.w3.org/2001/XMLSchema#string

P433

3

http://www.w3.org/2001/XMLSchema#string

P478

13

http://www.w3.org/2001/XMLSchema#string

P50

P577

2011-11-17T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

51815431

http://www.w3.org/2001/XMLSchema#string

P698

22101192

http://www.w3.org/2001/XMLSchema#string

P932

3577104

http://www.w3.org/2001/XMLSchema#string