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• High hyperdiploid ALL single cell whole genome sequencing

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15).

  Dataset EGAD00001008988

• scRNA-seq and snRNA-seq of trophoblast stem cells (TSCs) differentiation into extravillous trophoblast organoids (EVTs)

  This dataset is part of a study that aims to compare in vivo human trophoblast differentiation into EVTs to different in vitro trophoblast organoids using single-cell and single-nuclei RNA sequencing. This specific dataset includes scRNA-seq and snRNA-seq data from trophoblast stem cells (TSCs). Trophoblast stem cell (TSC) lines BTS5 and BTS11 derived by Okae and colleagues were grown as described previously (Okae et al. 2018) together with EVT differentiation media. This study shows that the main regulatory programs mediating EVT invasion in vivo are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. Data for primary trophoblast organoids is available under E-MTAB-12650.

  Dataset EGAD00001010017

• Longitudinal study of whole blood gene expression in Kenyan children exposed to malaria

  We have collected RNA samples from whole blood of Kenyan children exposed to malaria in the Kilifi region of Kenya. Collections were performed each year from 2015 until 2018. This is a follow-up study to that described in Bediako et al. (in preparation). The SIMS consortium is seeking to identifying the underlying reasons why some children are more susceptible to malaria than others. In this study we hope to track changes in children’s immune systems over time which relate to the number of malaria episodes they experience. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001015405

• An integrated single-cell reference atlas of the human endometrium

  This dataset includes both the anchor scRNA-seq and snRNA-seq datasets used to build the Human Endometrial Cell Atlas (HECA). HECA provides a comprehensive definition of endometrial cell types and states throughout the menstrual cycle in donor with and without endometriosis. It identifies consensus cell types across datasets generated by teams worldwide, as well as previously unreported cell types, all of which are validated and mapped in situ using spatial transcriptomics. Processed data is available from ArrayExpress with accession number E-MTAB-14039. See Marečková, M., Garcia-Alonso, L., Moullet, M. et al. An integrated single-cell reference atlas of the human endometrium. Nat Genet 56, 1925–1937 (2024) https://doi.org/10.1038/s41588-024-01873-w for more information.

  Dataset EGAD00001015446

• How to upload GPG files

  Uploading files Users that holds an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. In order to manage the available resources, we enforce a limit of 10Tb per submission account at any one time. Please do not exceed this limit. INBOX FTP The FTP is only compatible with files encrypted using the EGACryptor tool Before uploading Once your submission files have been prepared using the EGAryptor, the resulting encrypted files and associated md5sum files can be uploaded to your submission account using Aspera or FTP. The EGA is a shared, public service with limited resources. In order to manage the available resources, EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. If you are approaching this limit please contact contact EGA Helpdesk so that we can advise on how to register the associated metadata and trigger the archiving of files, so that you can continue with your submission. If we note that your submission account increases above 10Tb on a consistent base your password will be changed until metadata is associated. Aspera Download Aspera Using Aspera FTP FTP windows FTP Linux / Unix FTP client (Filezilla) FTP and TLS Troubleshooting Troubleshooting Aspera Download Aspera is a commercial file transfer protocol that may provide faster transfer speeds than ftp especially over longer distances. The Aspera ascp command line client. Please select Aspera Connect. The ascp command line client is distributed as part of the aspera connect highperformance transfer browser plugin and is free to use, without registration. The minimum required version of the IBM Aspera Cli is V4. Further instructions. Using the Aspera ascp command line program The location of the ascp program in the filesystem: Mac: on the desktop go cd /Applications/Aspera\ Connect.app/Contents/Resources/ there you'll see the command line utilities where you're going to use ascp. Windows: the downloaded files are a bit hidden. For instance, in Windows 7 the ascp.exe is located in the users home directory in: AppData\Local\Programs\Aspera\Aspera Connect\bin\ascp.exe Linux: should be in your user's home directory, cd /home/username/.aspera/connect/bin/ there you'll see the command line utilities where you're going to use ascp. Your command should look similar to this: ascp -P33001 -O33001 -QT -l300M -L- /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path If you wish to upload several files without being requested the password, please use the below command : ASPERA_SCP_PASS=ega-box-password ascp -P33001 -O33001 -QT -l300M /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path/ Explanation of parameters l300M option sets the upload speed limit to 30MB/s. You may wish to lower this value to increase the reliability of the transfer. L option is for printing logs out while transferring files to upload can be a file mask (e.g. '/homes/submitter/*.srf) or a list of files. ega-box-N is your submission account login. Add k2 switch for transfer restarts Check the command line transfer usage for more configuration details. Using FTP to upload your prepared files Use your preferred ftp client. For example, lftp is a popular choice for Linux and Mac users. Use binary mode for file transfers. Use ftp.ega.ebi.ac.uk as the target host. Login with your ega-box username and password. Upload files to your private ega-box upload area. Depending on your network setting you might wish to start FTP in passive or active mode. Using default FTP command line client in Windows Start the command line interpreter: press WinR, type cmd, hit enter Enter ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Use exit command to exit the command line interpreter. Using default FTP command line client in Linux / Unix Open a terminal and type ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Using FTP client FileZilla We recommend the use of FileZilla, a free FTP client . FileZilla is open source software distributed free of charge under the terms of the GNU General Public License. Use the following connection details (File - Site Manager) and add yoursubmission account username and password: Using FTP client FileZilla Select the files you wish to upload and then select upload: Using FTP client Filezilla Using LFTP with TLS We recommend the following to force the use of a secure connection. lftp > set ftp:ssl-force yes We also recommend setting the following for not encrypting the bulk data itself for performance reasons (theauthentication will still be encrypted): lftp > ftp:ssl-protect-data no In order to verify the certificate,the recommended way would be to use the CA certificates from your machine. To do that use this command in lftp adjusting the path to your ca-certificates location. lftp > ssl:ca-file "/etc/ssl/certs/ca-certificates.crt" If that is not possible or certificates are old and you can't update them, you can download the certificates needed from Quo Vadis Digital Repository The two certificates to download in PEM format are: QuoVadis Root CA2 G3 QuoVadis EV SSL ICA G3 Then you can concatenate them in a file one after the other and save it as lftp-certificates.pem Once this is done you have to point the ssl:ca-file variable to the path lftp > set ssl:ca-file "/path/to/lftp-certificates.pem" Also note that you can save this configuration at ~/.lftp/rc Another option is to download the certificates and add them to the ca-certificates of your machine. For example: In RHEL7 and cenots and others box the process to add the certificates globally is: Download the two certificates (in PEM or DER format, doesn't matter) and save them to "/etc/pki/ca-trust/source/anchors/" Run "update-ca-trust extract" Another less secure option is to turn off certificate verification with the following command: lftp > set ssl:verify-certificate false Troubleshooting If you are having problems with Aspera connection timeouts, it can be down to either one of the following. Transfers cannot start the connection fails instantly. Ensure that TCP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewall. The connection is made, transfers are started, but 0 bytes (0%) are uploaded for each file. Ensure that UDP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewal

  Documentation submission/data/uploading-files/ftp

• ARRA - NHLBI Lung Cohorts Sequencing Project: Genetic modifiers of

  The major goal of this project is to apply second generation resequencing technology to identify disease causing variants influencing pediatric and adult lung diseases in a collection of two longitudinal population cohorts of cystic fibrosis patients that have been well characterized for a comprehensive set of clinical traits. In Phase I, exome sequencing was performed on 43 cystic fibrosis patients with early Pa infection and 48 cystic fibrosis patients with late Pa infection to identify variants influencing the time to onset of Pa infection. In Phase II, additional exomes were added to the study, to reach a total of 91 individuals with early Pa infection and 96 with late Pa infection. The majority of the 340 subjects of Phase II do not have a Pa infection phenotype, but instead have a pulmonary function phenotype (121 severe vs. 124 mild impairment) as determined by the survival corrected Kulich FEV percentile of Corey et al. A small minority have intermediate phenotypes and/or show severe decline in lung function during childhood.

  Study phs000254

• POISED (Peanut Oral Immunotherapy: Safety, Efficacy, and Discovery)

  Phase 2 POISED (Peanut Oral Immunotherapy: Safety, Efficacy, Discovery) Study In this randomized, double-blind, placebo-controlled (DBPC) clinical trial, blinded placebo group received oat flour, whereas in active participants, dosage was built-up for over ~ 52 weeks and subsequently maintained on 4000 mg peanut protein, daily for next 52 weeks. 80 (98.77%) per-protocol active participants passed the food challenge at week 104. Subsequently, for 12 weeks, peanut ingestion was avoided in a randomized group of 51 blinded active participants (i.e., peanut avoidance group). 21 (41.2%) participants in the peanut avoidance group passed the 4000 mg double-blind, placebo-controlled food challenge (DBPCFC) without any allergic reaction at week 117, thus demonstrating sustained unresponsiveness. These 21 participants continued oral immunotherapy (OIT) for every three months and afterwards were allowed to continue peanut OIT discontinuation if they passed. 8 participants passed the DBPCFCs, 12 months after peanut discontinuation (week 156), i.e. they achieved long-term sustained unresponsiveness with no allergic reaction in response to food challenge. For detailed description, please refer to Chinthrajah et al., PMID: 31522849.

  Study phs003071

• Multi-Omic Profiling of Glioma Patient Tumors and Patient-Derived Model Systems

  We have created a resource of transcriptomic (RNAseq), genomic (whole-exome seq), and lipidomic (untargeted shotgun) profiling data from over 175 molecularly diverse glioma tumors and derivative models in orthotopic mouse xenografts and gliomasphere cultures from over 110 unique patient tumor lines. Provided in this dataset are matched bulk RNA and whole-exome paired-end sequencing data from resected gliomas and derived model systems performed on Illumina HiSeq and NovaSeq sequencing instruments. This comprehensive dataset powers multiple studies aiming to derive molecular signatures of intertumoral heterogeneity and perturbation responses in glioma. Through integrative multi-omic analyses in Minami, et al., 2023, PMID: 37236196, we identified that CDKN2A deletion remodels the GBM lipidome and consequently primes CDKN2A-deleted tumors for ferroptosis. Lipidomics data related to this study are publicly available here. In another study, we used a combination of molecular profiling and functional profiling of apoptotic potential to stratify patients into groups with differential vulnerability to the current standard-of-care in gliomas, and in combination with drugs targeting intrinsic apoptosis, largely informed but not limited to TP53 mutation status.

  Study phs003286

• Human liver cholangiocyte organoids capture the heterogeneity of in vivo human liver ductal epithelium

  Human liver ductal epithelium is morphologically, functionally and transcriptionally heterogeneous. However, understanding the dynamics within human biliary/ductal epithelium has been hampered by the absence of an in vitro system that fully mimics its complex cellular heterogeneity. Here, we found that the human liver cholangiocyte (ductal-cell) organoids we previously published (Huch et al., 2015) are fairly homogenous and do not retain the cellular heterogeneity of the in vivo human biliary/ductal epithelium. Inspired by the knowledge of the in vivo niche, we refined our previous organoid culture medium to fully capture the cellular heterogeneity of the human ductal epithelium. We employed this refined system to analyse the interactions and relationships between the different human biliary epithelial cell states and discovered that acquiring a bipotent ductal cell state is necessary for differentiating the human ductal epithelium into functional hepatocyte-like cells. Our improved cholangiocyte organoid model represents a new platform to investigate cell plasticity and duct-to-hepatocyte differentiation in human liver.

  Study EGAS50000001000

• Mechanisms_of_patient_response_to_Dabrafenib_in_Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)•NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]•CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Study EGAS00001000946