<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Zhao Y</submitter><funding>National Cancer Institute</funding><funding>NCI NIH HHS</funding><funding>National Institutes of Health</funding><pagination>269</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8220791</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>19(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis.&lt;h4>Methods&lt;/h4>In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate sampl</pubmed_abstract><journal>Journal of translational medicine</journal><pubmed_title>TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository.</pubmed_title><pmcid>PMC8220791</pmcid><funding_grant_id>HHSN261200800001E</funding_grant_id><pubmed_authors>Williams PM</pubmed_authors><pubmed_authors>Doroshow JH</pubmed_authors><pubmed_authors>Das B</pubmed_authors><pubmed_authors>Li MC</pubmed_authors><pubmed_authors>Chen L</pubmed_authors><pubmed_authors>Karlovich C</pubmed_authors><pubmed_authors>Konate MM</pubmed_authors><pubmed_authors>Evrard YA</pubmed_authors><pubmed_authors>Zhao Y</pubmed_authors><pubmed_authors>McShane LM</pubmed_authors></additional><is_claimable>false</is_claimable><name>TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository.</name><description>&lt;h4>Background&lt;/h4>In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis.&lt;h4>Methods&lt;/h4>In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate sampl</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Jun</publication><modification>2026-05-08T00:29:09.864Z</modification><creation>2022-02-10T15:58:31.158Z</creation></dates><accession>S-EPMC8220791</accession><cross_references><pubmed>34158060</pubmed><doi>10.1186/s12967-021-02936-w</doi></cross_references></HashMap>