Project description:Linker file for COMBAT CITEseq sequencing data. Links COMBAT sample IDs with sequencing pools and their associated raw sequence data. Sequence data can be found in the following datasets:
ADT data: EGAD00001007962
GEX data: EGAD00001008007
VDJ (B-cell): EGAD00001007964
VDJ (T-cell): EGAD00001007965
Project description:This data set was generated by the UK Brain Expression Consortium and consists of gene expression data generated from post-mortem human brain samples, dissected from 10 brain regions and originating from a large cohort of neurologically and neuropathologically normal individuals. The UK Brain Expression Consortium has generated gene expression data on a large cohort of neurologically and neuropathologically normal individuals in order to better understand gene expression differences across the human brain.
Project description:This data set was generated by the UK Brain Expression Consortium and consists of gene expression data generated from post-mortem human brain samples, dissected from 10 brain regions and originating from a large cohort of neurologically and neuropathologically normal individuals. The UK Brain Expression Consortium has generated gene expression data on a large cohort of neurologically and neuropathologically normal individuals in order to better understand gene expression differences across the human brain.
Project description:This dataset includes gene expression data from 103 primary tumour samples. 86 samples from this dataset have already been deposited into GEO (GSE36924), and has been duplicated here since the data has been processed differently. This data is also available through the International Cancer Genome Consortium (ICGC) Data Portal (http://dcc/icgc.org), under the project code: Pancreatic Cancer (QCMG, AU). Access to the restricted clinical data must be made through the ICGC Data Access Compliance Office (http://www.icgc.org/daco).
Project description:ATAC-Seq was performed for 35 AML primary specimens from primary AML cells, followed by a detailed ATAC-Seq pipeline for data processing. We provide both raw files as well as various processed files such as individual and consensus peaks.
Project description:This data set was generated by the UK Brain Expression Consortium and consists of gene expression data generated from post-mortem human brain samples, dissected from 10 brain regions and originating from a large cohort of neurologically and neuropathologically normal individuals. The UK Brain Expression Consortium has generated gene expression data on a large cohort of neurologically and neuropathologically normal individuals in order to better understand gene expression differences across the human brain. 1231 samples are analysed in total and these samples originate from 134 Caucasian individuals. From each individual, up to ten brain regions were sampled and analysed.
Project description:This data set was generated by the UK Brain Expression Consortium and consists of gene expression data generated from post-mortem human brain samples, dissected from 10 brain regions and originating from a large cohort of neurologically and neuropathologically normal individuals. The UK Brain Expression Consortium has generated gene expression data on a large cohort of neurologically and neuropathologically normal individuals in order to better understand gene expression differences across the human brain. 1231 samples are analysed in total and these samples originate from 134 Caucasian individuals. From each individual, up to ten brain regions were sampled and analysed.
Project description:In the present study, zebrafish were exposed to permethrin during early-life, and F1 and F2 generations were bred unexposed. Permethrin exposed F0 fish showed a hypoactive phenotype at adulthood, whereas males from the F1 and F2 generations showed a decrease in anxiety-like behavior. We performed transcriptomic analyses on whole brains (GSE154020), and here, we further performed RRBS analyses to identify whether there was any stable change in DNA methylation that could be linked to the effects observed at other levels of organization. Due to technical issues during sequencing, we had to perform a correction on the raw data (CombaT) in order to remove a batch effect (flow-cell). We made sure that this did not create any false-positive differentially methylated region. Processed files available are the results from methyl calling before batch correction(with a min coverage >= 5 per C). A matrix of corrected data is available as supplementary file.
Project description:We present a meta-dataset comprising of a total of 178 samples including both primary tumors and tumor-free pancreatic tissues from four independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
