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• Cellular indexing of transcriptomes and epitopes sequencing of peritoneal fluid from patients with achalasia

  The data published here contains cellular indexing of transcriptomes and epitopes sequencing (CITEseq) using the oligo-tagged TotalSeq™-B Human Universal Cocktail, V1.0 from BioLegend on peritoneal fluid (PF) from patients with achalasia. Sequencing was performed in a paired-ended fashion on the NovaSeq6000. Below an overview of the epitopes to oligotags as obtained from BioLegend: DNA_ID Description clone Sequence Ensembl ID B0006 anti-human CD86 IT2.2 GTCTTTGTCAGTGCA ENSG00000114013 B0007 anti-human CD274 (B7-H1, PD-L1) 29E.2A3 GTTGTCCGACAATAC ENSG00000120217 B0020 anti-human CD270 (HVEM, TR2) 122 TGATAGAAACAGACC ENSG00000157873 B0023 anti-human CD155 (PVR) SKII.4 ATCACATCGTTGCCA ENSG00000073008 B0024 anti-human CD112 (Nectin-2) TX31 AACCTTCCGTCTAAG ENSG00000130202 B0026 anti-human CD47 CC2C6 GCATTCTGTCACCTA ENSG00000196776 B0029 anti-human CD48 BJ40 CTACGACGTAGAAGA ENSG00000117091 B0031 anti-human CD40 5C3 CTCAGATGGAGTATG ENSG00000101017 B0032 anti-human CD154 24-31 GCTAGATAGATGCAA ENSG00000102245 B0033 anti-human CD52 HI186 CTTTGTACGAGCAAA ENSG00000169442 B0034 anti-human CD3 UCHT1 CTCATTGTAACTCCT ENSG00000167286 B0046 anti-human CD8 SK1 GCGCAACTTGATGAT ENSG00000153563 B0047 anti-human CD56 (NCAM) 5.1H11 TCCTTTCCTGATAGG ENSG00000149294 B0050 anti-human CD19 HIB19 CTGGGCAATTACTCG ENSG00000177455 B0052 anti-human CD33 P67.6 TAACTCAGGGCCTAT ENSG00000105383 B0053 anti-human CD11c S-HCL-3 TACGCCTATAACTTG ENSG00000140678 B0058 anti-human HLA-A,B,C W6/32 TATGCGAGGCTTATC ENSG00000206503 B0063 anti-human CD45RA HI100 TCAATCCTTCCGCTT ENSG00000081237 B0064 anti-human CD123 6H6 CTTCACTCTGTCAGG ENSG00000185291 B0066 anti-human CD7 CD7-6B7 TGGATTCCCGGACTT ENSG00000173762 B0068 anti-human CD105 43A3 ATCGTCGAGAGCTAG ENSG00000106991 B0070 anti-human/mouse CD49f GoH3 TTCCGAGGATGATCT ENSG00000091409 B0071 anti-human CD194 (CCR4) L291H4 AGCTTACCTGCACGA ENSG00000183813 B0072 anti-human CD4 RPA-T4 TGTTCCCGCTCAACT ENSG00000010610 B0073 anti-mouse/human CD44 IM7 TGGCTTCAGGTCCTA ENSG00000026508 B0081 anti-human CD14 M5E2 TCTCAGACCTCCGTA ENSG00000170458 B0083 anti-human CD16 3G8 AAGTTCACTCTTTGC ENSG00000203747 B0085 anti-human CD25 BC96 TTTGTCCTGTACGCC ENSG00000134460 B0087 anti-human CD45RO UCHL1 CTCCGAATCATGTTG ENSG00000081237 B0088 anti-human CD279 (PD-1) EH12.2H7 ACAGCGCCGTATTTA ENSG00000188389 B0089 anti-human TIGIT (VSTM3) A15153G TTGCTTACCGCCAGA ENSG00000181847 B0090 Mouse IgG1, κ isotype MOPC-21 GCCGGACGACATTAA B0091 Mouse IgG2a, κ isotype MOPC-173 CTCCTACCTAAACTG B0092 Mouse IgG2b, κ isotype MPC-11 ATATGTATCACGCGA B0095 Rat IgG2b, κ isotype RTK4530 GATTCTTGACGACCT B0100 anti-human CD20 2H7 TTCTGGGTCCCTAGA ENSG00000156738 B0101 anti-human CD335 (NKp46) 9E2 ACAATTTGAACAGCG ENSG00000189430 B0124 anti-human CD31 WM59 ACCTTTATGCCACGG ENSG00000261371 B0127 anti-Human Podoplanin NC-08 GGTTACTCGTTGTGT ENSG00000162493 B0134 anti-human CD146 P1H12 CCTTGGATAACATCA ENSG00000076706 B0136 anti-human IgM MHM-88 TAGCGAGCCCGTATA ENSG00000211899 B0138 anti-human CD5 UCHT2 CATTAACGGGATGCC ENSG00000110448 B0141 anti-human CD195 (CCR5) J418F1 CCAAAGTAAGAGCCA ENSG00000160791 B0142 anti-human CD32 FUN-2 GCTTCCGAATTACCG ENSG00000143226 B0143 anti-human CD196 (CCR6) G034E3 GATCCCTTTGTCACT ENSG00000112486 B0144 anti-human CD185 (CXCR5) J252D4 AATTCAACCGTCGCC ENSG00000160683 B0145 anti-human CD103 (Integrin αE) Ber-ACT8 GACCTCATTGTGAAT ENSG00000083457 B0146 anti-human CD69 FN50 GTCTCTTGGCTTAAA ENSG00000110848 B0147 anti-human CD62L DREG-56 GTCCCTGCAACTTGA ENSG00000188404 B0149 anti-human CD161 HP-3G10 GTACGCAGTCCTTCT ENSG00000111796 B0151 anti-human CD152 (CTLA-4) BNI3 ATGGTTCACGTAATC ENSG00000163599 B0152 anti-human CD223 (LAG-3) 11C3C65 CATTTGTCTGCCGGT ENSG00000089692 B0153 anti-human KLRG1 (MAFA) SA231A2 CTTATTTCCTGCCCT ENSG00000139187 B0154 anti-human CD27 O323 GCACTCCTGCATGTA ENSG00000139193 B0155 anti-human CD107a (LAMP-1) H4A3 CAGCCCACTGCAATA ENSG00000185896 B0156 anti-human CD95 (Fas) DX2 CCAGCTCATTAGAGC ENSG00000026103 B0158 anti-human CD134 (OX40) Ber-ACT35 (ACT35) AACCCACCGTTGTTA ENSG00000186827 B0159 anti-human HLA-DR L243 AATAGCGAGCAAGTA ENSG00000204287 B0160 anti-human CD1c L161 GAGCTACTTCACTCG ENSG00000158481 B0161 anti-human CD11b ICRF44 GACAAGTGATCTGCA ENSG00000169896 B0162 anti-human CD64 10.1 AAGTATGCCCTACGA ENSG00000150337 B0163 anti-human CD141 (Thrombomodulin) M80 GGATAACCGCGCTTT ENSG00000178726 B0164 anti-human CD1d 51.1 TCGAGTCGCTTATCA ENSG00000158473 B0165 anti-human CD314 (NKG2D) 1D11 CGTGTTTGTTCCTCA ENSG00000213809 B0167 anti-human CD35 E11 ACTTCCGTCGATCTT ENSG00000203710 B0168 anti-human CD57 Recombinant QA17A04 AACTCCCTATGGAGG ENSG00000109956 B0170 anti-human CD272 (BTLA) MIH26 GTTATTGGACTAAGG ENSG00000186265 B0171 anti-human/mouse/rat CD278 (ICOS) C398.4A CGCGCACCCATTAAA ENSG00000163600 B0174 anti-human CD58 (LFA-3) TS2/9 GTTCCTATGGACGAC ENSG00000116815 B0176 anti-human CD39 A1 TTACCTGGTATCCGT ENSG00000138185 B0179 anti-human CX3CR1 K0124E1 AGTATCGTCTCTGGG ENSG00000168329 B0180 anti-human CD24 ML5 AGATTCCTTCGTGTT ENSG00000272398 B0181 anti-human CD21 Bu32 AACCTAGTAGTTCGG ENSG00000117322 B0185 anti-human CD11a TS2/4 TATATCCTTGTGAGC ENSG00000005844 B0187 anti-human CD79b (Igβ) CB3-1 ATTCTTCAACCGAAG ENSG00000007312 B0189 anti-human CD244 (2B4) C1.7 TCGCTTGGATGGTAG ENSG00000122223 B0206 anti-human CD169 7-239 TACTCAGCGTGTTTG ENSG00000088827 B0214 anti-human/mouse integrin β7 FIB504 TCCTTGGATGTACCG ENSG00000139626 B0215 anti-human CD268 (BAFF-R) 11C1 CGAAGTCGATCCGTA ENSG00000159958 B0216 anti-human CD42b HIP1 TCCTAGTACCGAAGT ENSG00000203618 B0217 anti-human CD54 HA58 CTGATAGACTTGAGT ENSG00000090339 B0218 anti-human CD62P (P-Selectin) AK4 CCTTCCGTATCCCTT ENSG00000174175 B0219 anti-human CD119 (IFN-γ R α chain) GIR-208 TGTGTATTCCCTTGT ENSG00000027697 B0224 anti-human TCR α/β IP26 CGTAACGTAGAGCGA B0236 Rat IgG1, κ isotype RTK2071 ATCAGATGCCCTCAT B0238 Rat IgG2a, κ Isotype RTK2758 AAGTCAGGTTCGTTT B0242 anti-human CD192 (CCR2) K036C2 GAGTTCCCTTACCTG ENSG00000121807 B0246 anti-human CD122 (IL-2Rβ) TU27 TCATTTCCTCCGATT ENSG00000100385 B0352 anti-human FcεRIα AER-37 (CRA-1) CTCGTTTCCGTATCG ENSG00000179639 B0353 anti-human CD41 HIP8 ACGTTGTGGCCTTGT ENSG00000005961 B0355 anti-human CD137 (4-1BB) 4B4-1 CAGTAAGTTCGGGAC ENSG00000049249 B0358 anti-human CD163 GHI/61 GCTTCTCCTTCCTTA ENSG00000177575 B0359 anti-human CD83 HB15e CCACTCATTTCCGGT ENSG00000112149 B0363 anti-human CD124 (IL-4Rα) G077F6 CCGTCCTGATAGATG ENSG00000077238 B0364 anti-human CD13 WM15 TTTCAACGCCCTTTC ENSG00000166825 B0367 anti-human CD2 TS1/8 TACGATTTGTCAGGG ENSG00000116824 B0368 anti-human CD226 (DNAM-1) 11A8 TCTCAGTGTTTGTGG ENSG00000150637 B0369 anti-human CD29 TS2/16 GTATTCCCTCAGTCA ENSG00000150093 B0370 anti-human CD303 (BDCA-2) 201A GAGATGTCCGAATTT ENSG00000198178 B0371 anti-human CD49b P1E6-C5 GCTTTCTTCAGTATG ENSG00000164171 B0373 anti-human CD81 (TAPA-1) 5A6 GTATCCTTCCTTGGC ENSG00000110651 B0384 anti-human IgD IA6-2 CAGTCTCCGTAGAGT ENSG00000211898 B0385 anti-human CD18 TS1/18 TATTGGGACACTTCT ENSG00000160255 B0386 anti-human CD28 CD28.2 TGAGAACGACCCTAA ENSG00000178562 B0389 anti-human CD38 HIT2 TGTACCCGCTTGTGA ENSG00000004468 B0390 anti-human CD127 (IL-7Rα) A019D5 GTGTGTTGTCCTATG ENSG00000168685 B0391 anti-human CD45 HI30 TGCAATTACCCGGAT ENSG00000081237 B0393 anti-human CD22 S-HCL-1 GGGTTGTTGTCTTTG ENSG00000012124 B0394 anti-human CD71 CY1G4 CCGTGTTCCTCATTA ENSG00000072274 B0396 anti-human CD26 BA5b GGTGGCTAGATAATG ENSG00000197635 B0398 anti-human CD115 (CSF-1R) 9-4D2-1E4 AATCACGGTCCTTGT ENSG00000182578 B0404 anti-human CD63 H5C6 GAGATGTCTGCAACT ENSG00000135404 B0406 anti-human CD304 (Neuropilin-1) 12C2 GGACTAAGTTTCGTT ENSG00000099250 B0407 anti-human CD36 5-271 TTCTTTGCCTTGCCA ENSG00000135218 B0408 anti-human CD172a (SIRPα) 15-414 CGTGTTTAACTTGAG ENSG00000198053 B0419 anti-human CD72 3F3 CAGTCGTGGTAGATA ENSG00000137101 B0420 anti-human CD158 (KIR2DL1/S1/S3/S5) HP-MA4 TATCAACCAACGCTT ENSG00000125498 B0446 anti-human CD93 VIMD2 GCGCTACTTCCTTGA ENSG00000125810 B0575 anti-human CD49a TS2/7 ACTGATGGACTCAGA ENSG00000213949 B0576 anti-human CD49d 9F10 CCATTCAACTTCCGG ENSG00000115232 B0577 anti-human CD73 (Ecto-5'-nucleotidase) AD2 CAGTTCCTCAGTTCG ENSG00000135318 B0579 anti-human CD9 HI9a GAGTCACCAATCTGC ENSG00000010278 B0581 anti-human TCR Vα7.2 3C10 TACGAGCAGTATTCA B0582 anti-human TCR Vδ2 B6 TCAGTCAGATGGTAT B0591 anti-human LOX-1 15C4 ACCCTTTACCGAATA ENSG00000173391 B0592 anti-human CD158b (KIR2DL2/L3, NKAT2) DX27 GACCCGTAGTTTGAT ENSG00000243772 B0599 anti-human CD158e1 (KIR3DL1, NKB1) DX9 GGACGCTTTCCTTGA ENSG00000167633 B0822 anti-human CD142 NY2 CACTGCCGTCGATTA ENSG00000117525 B0830 anti-human CD319 (CRACC) 162.1 AGTATGCCATGTCTT ENSG00000026751 B0864 anti-human CD352 (NTB-A) NT-7 AGTTTCCACTCAGGC ENSG00000162739 B0867 anti-human CD94 DX22 CTTTCCGGTCCTACA ENSG00000134539 B0871 anti-human CD162 KPL-1 ATATGTCAGAGCACC ENSG00000110876 B0896 anti-human CD85j (ILT2) GHI/75 CCTTGTGAGGCTATG ENSG00000104972 B0897 anti-human CD23 EBVCS-5 TCTGTATAACCGTCT ENSG00000104921 B0902 anti-human CD328 (Siglec-7) 6-434 CTTAGCATTTCACTG ENSG00000168995 B0918 anti-human HLA-E 3D12 GAGTCGAGAAATCAT ENSG00000204592 B0920 anti-human CD82 ASL-24 TCCCACTTCCGCTTT ENSG00000085117 B0944 anti-human CD101 (BB27) BB27 CTACTTCCCTGTCAA ENSG00000134256 B1046 anti-human CD88 (C5aR) S5/1 GCCGCATGAGAAACA ENSG00000197405 B1052 anti-human CD224 KF29 CTGATGAGATGTCAG ENSG00000100031

  Dataset EGAD50000000252

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• How to encrypt files with EGACryptor

  File preparation Due to the processes used at the EGA for file archival the use of non-alphanumeric characters in a filename will cause issues in archival. By convention whitespaces in filenames are to be avoided and should be replaced with the underscore character (_). Before encrypting your files please make sure that any files that will be uploaded to EGA do not use special characters such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &  Crypt4gh EGACryptor Files encrypted with EGACryptor must be uploaded via FTP EGACryptor The EGACryptor v.2.0.0 is a JAVA-based application which enables submitters to produce EGA compliant encrypted files along with files for the encrypted and unencrypted md5sum for each file to be submitted. The application will generate an output folder that will by default mirror the directory structure containing the original files. This output folder can subsequently be uploaded to the EGA FTP staging area via an FTP or Aspera client. Download EgaCryptor Download EgaCryptor Using the EgaCryptor Using the EgaCryptor Encrypting single file Encrypting multiple files Encrypting all files in folder Points to note Troubleshooting Troubleshooting Download EGACryptor The required jar files can be obtained by downloading EgaCrytptor jar file After the file has been downloaded, extraction of the zipped archive is required. The EGACryptor has been built to work with Java Runtime Environments from version 6 and above and with the OpenJDK Environment. Please refer to the relevant resources for installation guidance. Installing the latest version of the OpenJDK will include the JCE files. If your installation of Java JRE is less than 1.8.0_151 will require the manual installation of the JCE Policy Files. You can verify the version of the Java SE Runtime Environment (JRE) installed by using the command: $ java -version If you need to install the JCE please follow the instructions below: Installing the JCE policy files (due to licensing terms and conditions the required policy files must be downloaded direct from the ORACLE website) : Download the unlimited strength JCE policy files (JRE 6 / JRE 7/ JRE 8) Uncompress and extract the downloaded file. This will create a subdirectory called JCE. This directory contains the following files: README.txt, COPYRIGHT.html, local_policy.jar and US_export_policy.jar Install the two policy JAR files by replacing the existing ones in your java home directory. Install the two policy JAR files by replacing the existing ones in your directory. The standard place for JCE jurisdiction policy JAR files is: /lib/security [Unix] or \lib\security [Win32] Notes: refers to the directory where the Java SE Runtime Environment (JRE) was installed. Additional performance enhancements that have been included in the EGACryptor V2.0.0: The ability to parallelise the processing of datasets through the use of the resources on a system. Multicore systems will allow the user to specify n-1 cores for an n-core system. The use of this feature on clusters may speed up the processing of datasets that have large file numbers but consult your local cluster guide to ensure that there are not monopolising resources that are needed by other system users. The default for this process remains single threaded. 3 levels of system usage can be specified. Full usage within the limits detailed above. A limited mode that will ensure that 50% of the system resources are available for other tasks. Maximum mode is limited to 75% of system resources, this allows encryption to be prioritised but allows for the system to be usable for light alternate tasks. Finally there is a throttling mode that allows you to specify the exact number of computational threads to be used. the EGACryptor is able to ingest a structured directory and will output a directory with the same structure containing the encrypted files along with the md5checksums for the plain and encrypted files. The entire output directory can then be uploaded to the EGA for archival. as with the input path, it is now possible to specify the output path. the options have been updated inline with the upgraded functionality. The tool can only be used via the command line. The EGACryptor is designed to perform a single task, encrypting your data, for upload of these files please refer to our uploading guide Using the EgaCryptor Below are the three ways on how the EGACryptor tool can be used: Encrypting a single file : java -jar ../EGA-Cryptor_2_0_0.jar -i example1.bam Encrypting multiple files : java -jar ../EGA-Cryptor_2_0_0.jar -i "example1.bam,example2.bam" Encrypting all the files within a folder java -jar ../EGA-Cryptor_2_0_0.jar -i path/to/target/directory By default the EGACryptor v2 will create a new output directory containing all encrypted files and the relevant checksums within the target directory. If a specific directory is desired this can be specified by using the -o flag. This can be achieved in a similar manner to the following example: java -jar ../EGA-Cryptor_2_0_0.jar -i /path/to/target/directory -o /path/to/output/directory The tool will output three files per input file: file.gpg ( encrypted file ) file.md5( file md5 sum value file ) file.gpg.md5 ( encrypted file md5 sum value file ) All output files must then be uploaded to your submission account using Aspera or FTP. Further documentation on how to upload files: FTP and Aspera. Points to note Remember to provide the path to EgaCryptor.jar and run the command from within the directory the file/s are located. ECryptor writes files to the source directory of your local file system, as a result you must have write-access permissions for the source directory. Troubleshooting If in doubt about the function of the EGACryptor it is recommended to first consult the built-in documentation. This can be accessessed by using the -h flag as stated in the following table. Built-in Commands Table: list of the command line options built into EGA-Cryptor v2.0.0. Command line Option Action --------------------- ----------- -f Set this option to allow application to create maximum threads to utilise full capacity of cores/processors available on machine -h Use this option to view the bult-in help menu * -i File(s) to encrypt. Provide file/folder path or comma separated file path if multiple files in double quotes -l Set this option to allow application to create maximum threads equals to 50% capacity of cores/processors available on machine -m Set this option to allow application to create maximum threads equals to 75% capacity of cores/processors available on machine -o Path of the output file. This is optional. If not provided then output files will be generated in the same path as that of source file (default: output- files) -t Set this option if user wants to control application to create maximum threads as specified. Application will calculate no. of cores/processors available on machine & will create threads accordingly Encryption Errors UnixFileSystem.createFileExclusively (Native Method) The error is thrown by UNIX ("UnixFileSystem.createFileExclusively(Native Method)"). It appears that the user does not have write-access to the file system where the file to be uploaded is located. EGACryptor always writes MD5 checksums into files before uploading them to the server, and these files are created in the same location where the uploaded file itself resides.Solution: address your directory permission issue and re-run the command. Install JCE Unlimited Strength Jurisdiction Policy files The JCE policy unlimited strength jurisdiction files should be installed according to your current java version If you are still facing difficulty with the EGACryptor v.2 after having consulted the documentation please contact the EGA Helpdesk.

  Documentation submission/data/file-preparation/egacryptor

• Uncovering the Genetic Architecture of Colorectal Cancer with Focus of Rare and Less Frequent Variants

  The Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) is a collaborative effort comprised of a coordinating center and scientific researchers from well-characterized cohort and case-control studies conducted in North America and Europe. This international consortium aims to accelerate the discovery of common and rare genetic risk variants for colorectal cancer by conducting large-scale meta-analyses of existing and newly generated genome-wide association study (GWAS) data, replicating and fine-mapping of GWAS discoveries, and investigating how genetic risk variants are modified by environmental risk factors. To expand these efforts, we assembled case-control sets or nested case-control sets from 20 different North American or European studies. Summary descriptions and study participant inclusions/exclusion criteria for each of these studies are detailed below. The Black Women&#39;s Health Study (BWHS): Is the largest follow-up study of the health of African-American women (Cozier et al., 2004; Rosenberg et al., 1995) [PMID: 15018884; PMID: 7722208]. The purpose is to identify and evaluate causes and preventives of cancers and other serious illnesses in African-American women. Among the diseases being studied are breast cancer, colorectal cancer, type 2 diabetes, uterine fibroids, systemic lupus erythematosus, and cardiovascular disease. The study began in 1995, when 59,000 black women from all parts of the United States enrolled through postal questionnaires. The women provided demographic and health data on the 1995 baseline questionnaire, including information on weight, height, smoking, drinking, contraceptive use, use of other selected medications, illnesses, reproductive history, physical activity, diet, use of health care, and other factors. The participants are followed through biennial questionnaires to determine the occurrence of cancers and other illnesses and to update information on risk factors. Self-reports of cancer are confirmed through medical records and state cancer registry records. Mouthwash-swish samples, as a source of DNA, were obtained from &#126;26,000 BWHS participants in 2002-2007. DNA was isolated from the mouthwash-swish samples at the Boston University Molecular Core Genetics Laboratory using the QIAAMP DNA Mini Kit (Qiagen). All incident colorectal cancer cases with a DNA sample were included in the present analysis. Two controls per case, selected from among BWHS participants free of colorectal cancer at end of follow-up, were matched to cases on year of birth (&#43;/- 2 years) and geographical region of residence (Northeast, South, Midwest, and West). A total 209 colorectal cancer cases and 423 controls were sent for genotyping. Campaign Against Cancer and Heart Disease (CLUE II): The Campaign Against Cancer and Heart Disease, is a prospective cohort designed to identify biomarkers and other factors associated with risk of cancer, heart disease, and other conditions (Kakourou et al., 2015) [PMID: 26220152]. 32,894 participants were recruited from May through October 1989 from Washington County, Maryland and surrounding communities. Colorectal cancer cases (n &#61; 297) and matched controls (n &#61; 296) were identified between 1989 and 2000 among participants in the CLUE II cohort of Washington County, Maryland. Colorectal Cancer Study of Austria (CORSA): In the ongoing colorectal cancer study of Austria (CORSA), more than 13,000 Caucasian participants have been recruited within the province-wide screening project &#34;Burgenland Prevention Trial of Colorectal Disease with Immunological Testing&#34; (B-PREDICT) since 2003 (Hofer et al., 2011) [PMID: 21422235]. All inhabitants of the Austrian province Burgenland aged between 40 and 80 years are annually invited to participate in fecal immunochemical testing and haemoccult positive screening participants are invited for colonoscopy. CORSA includes genomic DNA and plasma of colorectal cancer cases, low-risk and high-risk adenomas, and colonoscopy-negative controls. Controls received a complete colonoscopy and were free of colorectal cancer or polyps. CORSA participants have been recruited in the four KRAGES hospitals in Burgenland, Austria, and additionally, at the Medical University of Vienna (Department of Surgery), the Viennese hospitals &#34;Rudolfstiftung&#34; and the &#34;Sozialmedizinisches Zentrum Sud&#34;, and at the Medical University of Graz (Department of Internal Medicine). 1403 colorectal cancer and advanced colorectal adenoma cases, and 1404 matched controls were selected for the study. Distribution of factors sex and age (5 year strata) were evenly matched between cases and controls. Cancer Prevention Study II (CPS II): The CPS II Nutrition cohort is a prospective study of cancer incidence and mortality in the United States, established in 1992 and described in detail elsewhere (Calle et al., 2002; Campbell et al., 2014) [PMID: 12015775; PMID: 25472679]. At enrollment, participants completed a mailed self-administered questionnaire including information on demographic, medical, diet, and lifestyle factors. Follow-up questionnaires to update exposure information and to ascertain newly diagnosed cancers were sent biennially starting in 1997. Reported cancers were verified through medical records, state cancer registry linkage, or death certificates. The Emory University Institutional Review Board approves all aspects of the CPS II Nutrition Cohort. A total of 360 cases and 359 controls were selected for this study. Czech Republic Colorectal Cancer Study (Czech Republic CCS): Cases with positive colonoscopy results for malignancy, confirmed by histology as colon or rectal carcinomas, were recruited between September 2003 and May 2012 in several oncological departments in the Czech Republic (Prague, Pilsen, Benesov, Brno, Liberec, Ples, Pribram, Usti and Labem, and Zlin). Two control groups, sampled at the same time of cases recruitment, were included in the study. The first group consisted of hospital-based individuals with a negative colonoscopy result for malignancy or idiopathic bowel diseases. The reasons for the colonoscopy were: i) positive fecal occult blood test, ii) hemorrhoids, iii) abdominal pain of unknown origin, and iv) macroscopic bleeding. The second control group consisted of healthy blood donor volunteers from a blood donor center in Prague. All individuals were subjected to standard examinations to verify the health status for blood donation and were cancer-free at the time of the sampling. Details of CRC cases and controls have been reported previously (Vymetalkova et al., 2014; Naccarati et al., 2016; Vymetalkova et al., 2016) [PMID: 24755277; PMID: 26735576; PMID: 27803053]. All subjects were informed and provided written consent to participate in the study. They approved the use of their biological samples for genetic analyses, according to the Declaration of Helsinki. The design of the study was approved by the Ethics Committee of the Institute of Experimental Medicine, Prague, Czech Republic. All subjects included in the study were Caucasians and comprised 1792 cases and 1764 matched controls. Controls were matched to CRC cases as 1&#58;1 ratio. Matching was done on age and sex. Age was matched on &#43;&#45;5 years, whereas sex was matched exactly. For the cases without matched controls, matching was done only on sex. Early Detection Research Network (EDRN): The aim of the EDRN initiative is to develop and sustain a biorepository for support of translational research (Amin et al., 2010) [PMID: 21031013]. High-quality biospecimens were accrued and annotated with pertinent clinical, epidemiologic, molecular and genomic information. A user-friendly annotation tool and query tool was developed for this purpose. The various components of this annotation tool include: CDEs are developed from the College of American Pathologists (CAP) Cancer Checklists and North American Association of Central Cancer Registries (NAACR) standards. The CDEs provides semantic and syntactic interoperability of the data sets by describing them in the form of metadata or data descriptor. A total of 352 colorectal case samples and 399 controls were selected for this study. Controls were matched to CRC cases based on age and sex. The EPICOLON Consortium (EPICOLON): The EPICOLON Consortium comprises a prospective, multicentre and population-based epidemiology survey of the incidence and features of CRC in the Spanish population (Fernandez-Rozadilla et al., 2013) [PMID: 23350875]. Cases were selected as patients with de novo histologically confirmed diagnosis of colorectal adenocarcinoma. Patients with familial adenomatous polyposis, Lynch syndrome or inflammatory bowel disease-related CRC, and cases where patients or family refused to participate in the study were excluded. Hospital-based controls were recruited through the blood collection unit of each hospital, together with cases. All of the controls were confirmed to have no history of cancer or other neoplasm and no reported family history of CRC. Controls were randomly selected and matched with cases for hospital, sex and age (&#43;&#45; 5 years). A total of 370 cases and 370 controls were selected for genotyping. Hawaii Adenoma Study: For this adenoma study, two flexible-sigmoidoscopy screening clinics were first used to recruit participants on Oahu, Hawaii. Adenoma cases were identified either from the baseline examination at the Hawaii site of the Prostate Lung Colorectal and Ovarian cancer screening trial during 1996-2000 or at the Kaiser Permanente Hawaii&#39;s Gastroenterology Screening Clinic during 1995-2007. In addition, starting in 2002 and up to 2007, we also approached for recruitment all eligible patients who underwent a colonoscopy in the Kaiser Permanente Hawaii Gastroenterology Department. Cases were patients with histologically confirmed first-time adenoma(s) of the colorectum and were of Japanese, Caucasian or Hawaiian race&#47;ethnicity. Controls were selected among patients with a normal colorectum and were individually matched to the cases on age at exam, sex, race/ethnicity, screening date (&#43;&#45;3 months) and clinic and type of examination (colonoscopy or flexible sigmoidoscopy). We recruited 1016 adenoma cases (67.8% of all eligible) and 1355 controls (69.2% of all eligible); 889 cases and 1169 controls agreed to give a blood and 29 cases and 34 controls, a mouthwash sample. A total of 989 cases and 1185 controls were genotyped for this study. Columbus-area HNPCC Study (HNPCC, OSUMC): Patients with colorectal adenocarcinoma diagnosed at six participating hospitals were eligible for this study, regardless of age at diagnosis or family history of cancer. Patients with a clinical diagnosis of familial adenomatous polyposis were not eligible for this study. These six hospitals perform the vast majority of all operations for CRC in the Columbus metropolitan area (population 1.7 million). The institutional review board at all participating hospitals approved the research protocol and consent form in accordance with assurances filed with and approved by the United States Department of Health and Human Services. Briefly, during the period of January 1999 through August 2004, 1,566 eligible patients with CRC were accrued to the study (Hampel et al., 2008) [PMID 18809606]. A total of 1472 colorectal cancer samples had enough blood DNA remaining to be sent for genotyping. Control samples were provided by the Ohio State University Medical Center%#39;s (OSUMC) Human Genetics Sample Bank. The Columbus Area Controls Sample Bank is a collection of control samples for use in human genetics research that includes both donors&#39; anonymized biological specimens and linked phenotypic data. The data and samples are collected under the protocol &#34;Collection and Storage of Controls for Genetics Research Studies&#34;, which is approved by the Biomedical Sciences Institutional Review Board at OSUMC. Recruitment takes place in OSUMC primary care and internal medicine clinics. If individuals agree to participate, they provide written informed consent, complete a questionnaire that includes demographic, medical and family history information, and donate a blood sample. 4-7 ml of blood is drawn into each of 3 ACD Solution A tubes and is used for genomic DNA extraction and the establishment of an EBV-transformed lymphoblastoid cell culture, cell pellet in Trizol, and plasma. Controls were matched to CRC cases as 1&#58;1. Matching was done on age at reference time (age_ref), race, and sex. Age_ref was matched on &#43;&#45;5 years. Sex and race were matched exactly. For the cases without matched controls, matching was done only on sex and race with 1&#58;1 ratio. Since controls are fewer than cases, one control is matched on 2 cases at most. Health Professionals Follow-up Study (HPFS): A parallel prospective study to the NHS (Nurses&#39; Health Study). The HPFS cohort comprised 51,529 men aged 40-75 who, in 1986, responded to a mailed questionnaire (Rimm et al., 1990) [PMID: 2090285]. Participants provided information on health related exposures, including current and past smoking history, age, weight, height, diet, physical activity, aspirin use, and family history of colorectal cancer. Colorectal cancer and other outcomes were reported by participants or next-of-kin and were followed up through review of the medical and pathology record by physicians. Overall, more than 97% of self-reported colorectal cancers were confirmed by medical record review. Information was abstracted on histology and primary location. Incident cases were defined as those occurring after the subject provided the blood sample. Prevalent cases were defined as those occurring after enrollment in the study but before the subject provided the blood sample. Follow-up evaluation has been excellent, with 94% of the men responding to date. Colorectal cancer cases were ascertained through January 1, 2008. In 1993-1995, 18,825 men in the HPFS mailed blood samples by overnight courier, which were aliquoted into buffy coat and stored in liquid nitrogen. In 2001-2004, 13,956 men in the HPFS who had not provided a blood sample previously mailed in a swish-and-spit sample of buccal cells. Incident cases were defined as those occurring after the subject provided a blood or buccal sample. Prevalent cases were defined as those occurring after enrollment in the study in 1986, but before the subject provided either a blood or buccal sample. After excluding participants with histories of cancer (except nonmelanoma skin cancer), ulcerative colitis, or familial polyposis, case-control sets were previously constructed. In addition to colorectal cancer cases and controls, a set of adenoma cases and matched controls with available DNA from buffy coat were selected for genotyping. Over the follow-up period, data were collected on endoscopic screening practices and, if individuals had been diagnosed with a polyp, the polyps were confirmed to be adenomatous by medical record review. Adenoma cases were ascertained through January 1, 2008. A separate case-control set was constructed of participants diagnosed with advanced adenoma matched to control participants who underwent a lower endoscopy in the same time period and did not have an adenoma. Advanced adenoma was defined as an adenoma 1 cm or larger in diameter and&#47;or with tubulovillous, villous, or highgrade dysplasia&#47;carcinoma-in-situ histology. Matching criteria included year of birth (within 1 year) and month&#47; year of blood sampling (within 6 months), the reason for their lower endoscopy (screening, family history, or symptoms), and the time period of any prior endoscopy (within 2 years). Controls matched to cases with a distal adenoma either had a negative sigmoidoscopy or colonoscopy examination, and controls matched to cases with proximal adenoma all had a negative colonoscopy. In total, 159 advanced adenoma cases and 109 controls were selected for genotyping. Leeds Colorectal Cancer Study (LCCS): Following local ethical approval, colorectal cancer cases were recruited from 1997 until 2012 in Leeds, UK through surgical clinics. Initially, funding was provided by the UK Ministry of Agriculture, Farming and Fisheries (subsequently the Food Standards Agency) and Imperial Cancer Research Fund (subsequently Cancer Research UK). Recruitment also occurred similarly in Dundee, Perth and York between the periods of 1997 and 2001 using the same protocol and the data and samples were combined. Pathologically confirmed cases were consented at outpatient clinics, providing information on known and postulated risk factors for colorectal cancer (diet, lifestyle and family history) as well as providing a blood sample for DNA. Exclusion criteria included pre-existing diverticular disease and an inability to complete the questionnaire. The General Practitioners of cases (all UK residents have a nominated General Practitioner to whom to refer initial medical queries) and these GPs were asked to send letters to other persons on their patient list of the same gender and born within 5 years of the case. Subsequently to enhance the number of controls, we systematically invited patients from selected GP practices. Diet was assessed in cases and controls using an extensive dietary and lifestyle questionnaire modified by that produced by the European Prospective Investigation in Cancer (EPIC). The frequency that each specific food items were eaten was recorded and we also obtained average fruit and vegetable consumption as a cross-check. In total, 1591 cases and 739 controls provided a DNA sample. The North Carolina Colon Cancer Studies (NCCCS I/II): The North Carolina Colon Cancer Studies (NCCCS I- colon and NCCCS II-rectal) were population-based case-control studies conducted in 33 counties of North Carolina. Cases were identified using the rapid case ascertainment system of the North Carolina Central Cancer Registry. Patients with a first diagnosis of histologically confirmed invasive adenocarcinoma of the colon (cecum through sigmoid colon) between October 1996 and September 2000 were classified as potential cases in the NCCCS I. The NCCCS II included patients with a first diagnosis of histologically confirmed invasive adenocarcinoma of the sigmoid colon, rectosigmoid, or rectum (hereafter collectively referred to as rectal cancer) between May 2001 and September 2006. Additional eligibility requirements were: aged 40-80 years, residence in one of the 33 counties, ability to give informed consent and complete an interview, had a driver&#39;s license or identification card issued by the North Carolina Department of Motor Vehicles (if under the age of 65), and had no objections from the primary physician in regards to contacting the individual. Controls, identified and sampled during the respective study dates, were selected from two sources. Potential controls under the age of 65 were identified using the North Carolina Department of Motor Vehicles records. For those 65 years and older, records from the Center for Medicare and Medicaid Services were used. Controls were matched to cases using randomized recruitment strategies. Recruitment probabilities were done using strata of 5-year age, sex, and race groups. Dietary information was collected using a modified version of the semiquantitative food frequency questionnaire developed at the National Cancer Institute. In addition, participants were asked about vitamin and mineral supplementation, special diets, restaurant eating, sodium use, and fats used in cooking. In NCCCS I, 515 colorectal cases and 687 matched controls were sent for genotyping. In NCCCS II, 796 colorectal cases and 823 controls were sent from the NCCCS II for genotyping. Controls were matched to CRC cases as 1&#58;1 ratio. Matching was done on age, race, and sex. Age was matched on &#43;&#45;5 years. Race and sex was matched exactly. For the cases without matched controls, matching was done only on sex and race. Nurses Health Study (NHS): The NHS cohort began in 1976 when 121,700 married female registered nurses age 30-55 years returned the initial questionnaire that ascertained a variety of important health-related exposures (Belanger et al., 1978) [PMID: 248266]. Since 1976, follow-up questionnaires have been mailed every 2 years. Colorectal cancer and other outcomes were reported by participants or next-of-kin and followed up through review of the medical and pathology record by physicians. Overall, more than 97% of self-reported colorectal cancers were confirmed by medical-record review. Information was abstracted on histology and primary location. The rate of follow-up evaluation has been high: as a proportion of the total possible follow-up time, follow-up evaluation has been more than 92%. Colorectal cancer cases were ascertained through June 1, 2008. In 1989 -1990, 32,826 women in NHS I mailed blood samples by overnight courier, which were aliquoted into buffy coat and stored in liquid nitrogen. In 2001-2004, 29,684 women in NHS I who did not previously provide a blood sample mailed a swish-and-spit sample of buccal cells. Incident cases were defined as those occurring after the subject provided a blood or buccal sample. Prevalent cases were defined as those occurring after enrollment in the study in 1976 but before the subject provided either a blood or buccal sample. After excluding participants with histories of cancer (except nonmelanoma skin cancer), ulcerative colitis, or familial polyposis, case-control sets were previously constructed from which DNA was isolated from either buffy coat or buccal cells for genotyping. In addition to colorectal cancer cases and controls, a set of advanced adenoma cases and matched controls with available DNA from buffy coat were selected for genotyping. Over the follow-up period, data were collected on endoscopic screening practices and, if individuals had been diagnosed with a polyp, the polyps were confirmed to be adenomatous by medical record review. Adenoma cases were ascertained through June 1, 2011. A separate case-control set was constructed of participants diagnosed with advanced adenoma matched to control participants who underwent a lower endoscopy in the same time period and did not have an adenoma. Advanced adenoma was defined as an adenoma more than 1 cm in diameter and/or with tubulovillous, villous, or high-grade dysplasia/carcinoma-in-situ histology. Matching criteria included year of birth (within 1 year) and month/year of blood sampling (within 6 months), the reason for their lower endoscopy (screening, family history, or symptoms), and the time period of any prior endoscopy (within 2 years). Controls matched to cases with a distal adenoma either had a negative sigmoidoscopy or colonoscopy examination, and controls matched to cases with proximal adenoma all had a negative colonoscopy. A total of 272 cases and 236 matched controls were sent to CIDR for the advanced adenoma case-control set. Northern Swedish Health and Disease Study (NSHDS): Comprises over 110,000 participants, including approximately one third with repeated sampling occasions, from three population-based cohorts (Dahlin et al., 2010; Myte et al., 2016) [PMID: 20197478; PMID: 27367522]. The largest is the ongoing Vasterbotten Intervention Programme, in which all residents of Vasterbotten County are invited to a health examination upon turning 30 (some years), 40, 50 and 60 years of age. Extensive measured and self-reported health and lifestyle data, as well as blood samples for central biobanking in Umea, Sweden, are collected at the health exam. Leucocyte DNA samples for 1&#58;1-matched CRC case-control sets from the NSHDS, of which 878 samples are included in this study, have been selected for genotyping. This is in addition to 354 samples from the NSHDS previously analyzed as part of the multicenter EPIC cohort. Cancer-specific and overall survival data are available for all patients. For at least 425 patients, archival tumor tissue has been analyzed for the BRAF V600E mutation and by sequencing codon 12 and 13 for KRAS mutations, as well as for MSI screening status by immunohistochemistry and for an eight-gene CIMP panel using quantitative real-time PCR (MethyLight). Ohio Colorectal Cancer Prevention Initiative (OCCPI, OSUMC): OCCPI (ClinicalTrials.gov identifier: NCT01850654) is a population-based study of colorectal cancer patients diagnosed in one of 51 hospitals throughout the state of Ohio from January 1, 2013 through December 31, 2016. The OCCPI was created to decrease CRC incidence in Ohio by identifying patients with hereditary predisposition (statewide universal tumor screening for newly diagnosed CRC patients), increase colonoscopy compliance for first-degree relatives of CRC patients, and encourage future research through the creation of a biorepository. The 51 Ohio hospitals participating in the OCCPI were selected to represent a cross-section of clinical centers in the state based on high reported volume of CRC patients, affiliation with a high volume hospital, or interest in participation. Institutional Review Board (IRB) approval was obtained by the individual hospitals, Community Oncology Programs, or by ceding review to the OSU IRB. Written informed consent was obtained. A total of 2139 colorectal cases were genotyped. Patients were considered eligible for this study if they were age 18 or older at the time of enrollment, if they had a surgical resection (or biopsy if unresectable) in the state of Ohio demonstrating an adenocarcinoma of the colorectum from 1&#47;1&#47;13 - 12&#47;31&#47;16. Matched control samples were selected from the Ohio State University Medical Center&#39;s (OSUMC) Human Genetics Sample Bank in an identical way to the selection for the Columbus-area HNPCC Study (please refer to the description for the Columbus-area HNPCC Study). Prostate, Lung, Colorectal and Ovarian Cancer Screening Trail (PLCO): PLCO enrolled 154,934 participants (men and women, aged between 55 and 74 years) at ten centers into a large, randomized, two-arm trial to determine the effectiveness of screening to reduce cancer mortality. Sequential blood samples were collected from participants assigned to the screening arm. Participation was 93% at the baseline blood draw. In the observational (control) arm, buccal cells were collected via mail using the &#34;swish-and-spit&#34; protocol and participation rate was 65%. Details of this study have been previously described (Huang et al., 2016) [PMID&#58; 27673363] and are available online (http://dcp.cancer.gov/plco). For this study 1651 advanced adenoma cases and 1392 controls were selected for genotyping. Selenium and Vitamin E Prevention Trial (SELECT): The Selenium and Vitamin E Cancer Prevention Trial (SELECT) was a double-blind, placebo controlled clinical trial which explored using selenium and vitamin E alone and in combination to prevent prostate cancer in healthy men (Lippman et al., 2009) [PMID&#58; 19066370]. Secondary endpoints included the prevention of colorectal and lung cancers. SELECT was conducted at 427 sites and centers in the United States, Canada and Puerto Rico; 35,533 men 55 years and older (50 or older if African American) were randomized beginning August 22, 2001. Supplementation was discontinued on October 23, 2008 due to futility. 308 colorectal cancer cases and 308 matched controls were selected from the SELECT population and sent for genotyping. Screening Markers For Colorectal Disease Study and Colonoscopy and Health Study (SMS-REACH): Details on this study population were previously reported (Burnett-Hartman et al., 2014) [PMID&#58; 24875374]. Participants were enrollees in an integrated health-care delivery system in western Washington State (Group Health Cooperative, Seattle, Washington) aged 24-79 years who underwent an index colonoscopy for any indication between 1998 and 2007 and donated a buccal-cell or blood sample for genotyping analysis. Study recruitment took place in 2 phases, with phase 1 occurring in 1998-2003 and phase 2 occurring in 2004-2007. Persons who had undergone a colonoscopy less than 1 year prior to the index colonoscopy, persons with inadequate bowel preparation for the index colonoscopy, and persons with a prior or new diagnosis of colorectal cancer, a familial colorectal cancer syndrome (such as familial adenomatous polyposis), or another colorectal disease were ineligible. Patients diagnosed with adenomas or serrated polyps and persons who were polyp-free at the index colonoscopy (controls) were systematically recruited during both phases of recruitment. Approximately 75% agreed to participate and provided written informed consent. Based on medical records, persons who agreed to participate and those who refused study participation were similar with respect to age, sex, and colorectal polyp status. Study protocols were approved by the institutional review boards of the Group Health Cooperative and the Fred Hutchinson Cancer Research Center (Seattle, Washington). A total of 575 cases and 508 matched were selected for the study. Controls were matched to CRC cases as 1&#58;1 ratio. Matching was done on age_ref, race, and sex. Age_ref was matched on &#43;&#45;5 years. The Women&#39;s Health Initiative (WHI): WHI is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts&#58; a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are: Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg&#47;d plus medroxyprogesterone acetate [MPA] 2.5 mg&#47;d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg&#47;d) and vitamin D (400 IU&#47;d) supplements or a matching placebo. The Observational Study (OS)examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. All centrally confirmed cases of invasive colorectal cancers, or deaths from colorectal cancer were selected as potential cases from September 30, 2015 database. Controls were participants free of colorectal cancer (invasive or in situ) as of September 30, 2015. Potential cases and controls were excluded if they (1) were non-White; (2) had history of colorectal cancers at baseline; (3) lost to follow-up after enrollment; (4) DbGAP ineligible; (5) had &#60;1.25ug of DNA; (6) selected for WHI study M26 Phase I or II; (7) selected for WHI study AS224 and also included in the imputation project. A total of 578 cases and 104,429 controls met the eligibility criteria. Each case was matched with 1 control (1&#58;1) that exactly met the following matching criteria: age (&#43;&#45;5 years), 40 randomization centers (exact), WHI date (&#43;&#45;3 years), CaD date (&#43;&#45;3 years), OS flag (exact), HRT assignments (exact), DM assignments (exact), and CaD assignments (exact). Control selection was done in a time-forward manner, selecting one control for each case from the risk set at the time of the case&#39;s event. The matching algorithm was allowed to select the closest match based on a criteria to minimize an overall distance measure (Bergstralh EJ, Kosanke JL. Computerized matching of cases to controls. Technical Report #56, Department of Health Sciences Research, Mayo Clinic, Rochester MN. April 1995). Each matching factor was given the same weight. When exact matches could not be found, the matching criteria were gradually relaxed among unmatched cases and controls until all cases had found matched controls. Using the matching criteria specified above, 559 of the 578 eligible cases found exact matches. The matching criteria was then relaxed to &#58; Age&#43;&#45;5, randomization centers, WHI date &#43;&#45; 3 years, CaD date &#43;&#45; 3 years, OS flag, HRT flag, DM flag, CaD flag. 17 of the remaining 19 unmatched cases found matched controls. By matching on Age&#43;&#45;5, randomization centers, WHI date &#43;&#45; 3 years, CaD date &#43;&#45; 3 years, OS flag, HRT flag, the remaining 2 unmatched cases found their matches.

  Study phs001415

• A Study to Assess the Cardiovascular, Cognitive, and Subjective Effects of Atomoxetine in Combination with Intravenous Methamphetamine

  The Study to Assess the Cardiovascular, Cognitive, and Subjective Effects of Atomoxetine in Combination with Intravenous Methamphetamine started in 2007 and ended in 2011. It was a small pilot study that included methamphetamine abusing individuals and healthy control participants aged 18-50 years. Participants who qualified over the telephone were scheduled to visit the London Laboratory at the UCLA Semel Institute for Neuroscience and Human Behavior for the In-Person Screening Phase. The screening procedures, usually scheduled over two visits, determined if participants were eligible to complete the subsequent study visits. Both groups completed identical screening procedures, including a SCID diagnostic interview to rule out any major psychiatric disorders. Methamphetamine users also answered questionnaires specific to their drug use. Urine toxicology for marijuana, opiates, cocaine, methamphetamine, and benzodiazepines were monitored at the beginning and throughout the study. Additionally, participants had blood samples to test for Rapid Plasma Reagin (exposure to syphilis), purified protein derivative (PPD), HIV and Hepatitis-C (HCV). Positive test results were relayed by a study physician and resulted in termination from continuing in the study. The inpatient portion of the study lasted a total of 24 days. To confirm compliance with abstinence from illicit and prescription drug use for the duration of the study, urine and breath alcohol testing was performed for both inpatient (methamphetamine users) and outpatient (healthy control) groups. Each subject was randomized to receive either atomoxetine (80 mg daily) or placebo. During inpatient days of the study, a study physician oversaw research subjects daily and experimental procedures were conducted in the General Clinical Research Center (GCRC). During drug administration sessions, heart rate and blood pressure were assessed at frequent intervals. Experimental sessions lasted around three hours and were conducted at approximately the same time of day for a given participant. Lunch was provided to participants at 11:30am with the prohibition of caffeine on study days involving methamphetamine administration. Participants were provided with smoke breaks as needed to assure that acute nicotine withdrawal did not negatively impact performance on cognitive testing. The following outlines the day to day procedures for a methamphetamine inpatient: Phase I Inpatient Study (15 days total) Days 1-3: On the day of admission, participants received blood tests and an EKG in order to determine that they had no occult medical conditions which would make their participation in the study medically contraindicated. A three day washout period was provided at the beginning of the study to establish an appropriate methamphetamine-free baseline for testing. Days 4-6: Participants completed cognitive test batteries to assess inhibitory control including self-report measures and cognitive testing, as well as up to three MRI scanning sessions. Day 7: On day 7, at 9AM and 1PM, participants received methamphetamine in a single-blinded condition. It was administered as two IV infusions of 15mg separated by a 60min break. The total dose of IV methamphetamine was 30mg. Participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in the absence of study medication. Day 8: On day 8 we evaluated the safety and residual effects of the methamphetamine administered on the previous day. Days 9-10: After demonstrating medical and psychiatric stability of the initial methamphetamine infusion, participants were then randomized to receive placebo or atomoxetine (0 or 40mg) under double-blind conditions, which would be given at 8AM on both study days. Days 11-12: On days 11 and 12, participants remained in the GCRC and took two doses of test compound atomoxetine (0 or 40mg) at 8AM and 8PM. On the morning of day 12, participants completed a series of cognitive testing. Day 13: On day 13, participants remained in the GCRC, and took two doses of the test compound atomoxetine (0 or 40mg) at 8AM and 8PM. At 9AM and noon, they received methamphetamine under double-blind conditions administered non-contingently as two infusions of 0 or 15mg by IV (intravenously), with each infusion separated by 60min. The total dose of IV methamphetamine that each participant received was 30mg. As before, participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in those participants receiving study medication. Day 14: On day 14 at 8AM, participants received their final dosing of the first test compound (atomoxetine 0 or 40mg). At 9AM and 1PM, participants selected between methamphetamine infusion or money using double-blind conditions in a multiple-choice self-administration paradigm. Participants were able to take up to two infusions of 0 or 15mg of methamphetamine, separated by 60min. The total dose of IV methamphetamine that each participant received on day 14 was 30mg. Participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in those participants receiving study medication. At 5pm on day 14 discharge laboratory studies were drawn. Day 15: On day 15, a final EKG was performed as well as a review of discharge laboratory studies, including review of the EKG and continued medical and psychiatric stability. Upon clearance from a physician, participants were discharged on day 15. Participants spent at least 2 weeks (14 days) out of the hospital prior to returning to the UCLA GCRC for inpatient Phase II. Phase II Inpatient Study (9 days total) Day 1-2: On the day of re-admission, participants received blood tests and an EKG. A two day washout period was provided at the beginning of the study to establish an appropriate methamphetamine free condition for safe administration of the second test compound condition. Days 3-4: On days 3 and 4, given medical stability, participants were then switched to the opposite test compound (atomoxetine 0 or 40mg) under double-blind conditions, in the same manner as in Days 9-10 in Phase I. Days 5-6: Same procedure as in Days 11-12 in Phase I but with opposite medication condition. Day 7: Same procedure as in Day13 in Phase I but with opposite medication condition. Day 8: Same procedure as in Day14 in Phase I but with opposite medication condition. Day 9: Same procedure as in Day14 in Phase I but with opposite medication condition. For healthy control participants, the study consisted of 30 days or fewer of out-patient testing. Healthy control participants had an extensive screening, including a history and physical exam performed by a study physician, an EKG, and laboratory studies performed to assess for medical or psychiatric conditions. Control participants meeting criteria were invited back to UCLA to undergo cognitive testing, and some participants received fMRI scans. Participants were required to refrain from illicit and prescription drug use for the duration of the study, which was confirmed with urine toxicology and breath alcohol level testing on examination days. Caffeine was restricted on study days for least 2 hours prior to cognitive testing and MRI scans. Participants were permitted to drink their normal daily intake of caffeine, given the caveat above. On study days, cigarette smoking was permitted to match conditions used with methamphetamine users. The incorporation of smoke breaks during the test day assured that acute nicotine withdrawal did not negatively impact performance on cognitive tests or neuroimaging. The following outlines procedures for healthy control participants: For normal controls, participation involved one day of outpatient screening, and one day of baseline cognitive testing and possible MRI scans. After these procedures were completed, participants were randomized to the first test compound (atomoxetine 40mg or placebo), to be taken once daily in the morning for 2 days. It was then increased to twice daily for the next 3 days, followed by a final dose (40mg or placebo) on the sixth day of study medication. Participants were also asked to bring their pill packages to assess compliance with the study medication. Additionally, control participants completed a series of repeated-measures cognitive testing (on placebo or atomoxetine, respectively) and possibly two fMRI sessions (separated by a short break). After at least a four-day washout period, control participants were instructed to start the opposite test compound (atomoxetine 40mg or placebo), again to be taken once daily in the morning for two days, then twice daily for 3 days, reaching the final dose (40mg or placebo) of the second test compound in the morning. Participants were again asked to bring their pill packages to assess compliance and had blood drawn to assess atomoxetine levels. Control participants then completed another series of cognitive testing and fMRI testing sessions. They were subsequently discharged from the study. Normal control participants returned two weeks after completion of both study phases in order to complete assessments to their physical and psychological status following treatment.

  Study phs001195

• The Thrifty Microbiome: The Role of the Gut Microbiota in Obesity in the Amish

  Emerging evidence that the gut microbiota may contribute in important ways to human health and disease has led us and others to hypothesize that both symbiotic and pathological relationships between gut microbes and their host may be key contributors to obesity and the metabolic complications of obesity. Our "Thrifty Microbiome Hypothesis" poses that gut microbiota play a key role in human energy homeostasis. Specifically, constituents of the gut microbial community may introduce a survival advantage to its host in times of nutrient scarcity, promoting positive energy balance by increasing efficiency of nutrient absorption and improving metabolic efficiency and energy storage. However, in the presence of excess nutrients, fat accretion and obesity may result, and in genetically predisposed individuals, increased fat mass may result in preferential abdominal obesity, ectopic fat deposition (liver, muscle), and metabolic complications of obesity (insulin resistance, hypertension, hyperlipidemia). Furthermore, in the presence of excess nutrients, a pathological transition of the gut microbial community may occur, causing leakage of bacterial products into the intestinal lymphatics and portal circulation, thereby inducing an inflammatory state, further aggravating metabolic syndrome traits and accelerating atherosclerosis. This pathological transition and the extent to which antimicrobial leakage occurs and causes inflammatory and other maladaptive sequelae of obesity may also be influenced by host factors, including genetics. In the proposed study, we will directly test the Thrifty Microbiome Hypothesis by performing detailed genomic and functional assessment of gut microbial communities in intensively phenotyped and genotyped human subjects before and after intentional manipulation of the gut microbiome. To address these hypotheses, five specific aims are proposed: (1) enroll three age- and sex-matched groups from the Old Order Amish: (i) 50 obese subjects (BMI &gt; 30 kg/m2) with metabolic syndrome, (ii) 50 obese subjects (BMI &gt; 30 kg/m2) without metabolic syndrome, and (iii) 50 non-obese subjects (BMI &lt; 25 kg/m2) without metabolic syndrome and characterize the architecture of the gut microbiota from the subjects enrolled in this study by high-throughput sequencing of 16S rRNA genes; (2) characterize the gene content (metagenome) to assess the metabolic potential of the gut microbiota in 75 subjects to determine whether particular genes or pathways are correlated with disease phenotype; (3) characterize the transcriptome in 75 subjects to determine whether differences in gene expression in the gut microbiota are correlated with disease phenotype, (4) determine the effect of manipulation of the gut microbiota with antibiotics on energy homeostasis, inflammation markers, and metabolic syndrome traits in 50 obese subjects with metabolic syndrome and (5) study the relationship between gut microbiota and metabolic and cardiovascular disease traits, weight change, and host genomics in 1,000 Amish already characterized for these traits and in whom 500K Affymetrix SNP chips have already been completed. These studies will provide our deepest understanding to date of the role of gut microbes in terms of &#39;who&#39;s there?&#39;, &#39;what are they doing?&#39;, and &#39;how are they influencing host energy homeostasis, obesity and its metabolic complications? PUBLIC HEALTH RELEVANCE: This study aims to unravel the contribution of the bacteria that normally inhabit the human gastrointestinal tract to the development of obesity, and its more severe metabolic consequences including cardiovascular disease, insulin resistance and Type II diabetes. We will take a multidisciplinary approach to study changes in the structure and function of gut microbial communities in three sets of Old Order Amish patients from Lancaster, Pennsylvania: obese patients, obese patients with metabolic syndrome and non-obese individuals. The Old Order Amish are a genetically closed homogeneous Caucasian population of Central European ancestry ideal for genetic studies. These works have the potential to provide new mechanistic insights into the role of gut microflora in obesity and metabolic syndrome, a disease that is responsible for significant morbidity in the adult population, and may ultimately lead to novel approaches for prevention and treatment of this disorder.

  Study phs000258

• Risk Assessment of Cerebrovascular Events (RACE) Study

  This study includes 1,220 cases with young onset stroke (stroke before age 60 years) who are participants of the larger RACE study. Risk Assessment of Cerebrovascular Events (RACE) is an on-going existing case-control study of stroke now involving over 5000 imaging confirmed cases of stroke and 5000 controls, recruited from seven centers in Pakistan. The study is aimed to investigate the genetic, biomarker and lifestyle determinants of stroke and its subtypes. Cases are eligible for inclusion in the study if they: (i) are aged at least 18 years; (ii) present with a sudden onset of neurological deficit respecting a vascular territory with sustained deficit at 24 hours verified by medical attention within 72 hours after onset (onset is defined by when the patient was last seen normal and not when found with deficit); and (iii) the diagnosis is supported by CT/MRI; and (iv) present with a Modified Rankin Score &lt; 2 prior to the stroke. Findings from patient&#39;s history, 12-lead ECG and CT or MRI of the brain. The mandatory procedures for inclusion in this investigation are: (i) clinical verification of cerebrovascular event within 72 hours of onset; (ii) neuroimaging CT (non-contrast) or MRI (MRI is not a mandatory investigation but recorded whenever ordered by the attending physician); and (iii) 12-lead ECG. All other ancillary investigations ordered by the attending physician are recorded as well. The TOAST classification method is used to classify ischemic stroke based on aetiology whereas the Oxfordshire classification is used to classify stroke neuro-anatomically. Control participants for this subset of young onset stroke were individuals enrolled in the Pakistan Risk of Myocardial Infarction Study (PROMIS), a case-control study of acute MI based in Pakistan. RACE capitalizes on the genetic data (including information on GWAS) that has already been collected from the healthy participants enrolled in PROMIS. RACE and PROMIS share similar methodology of recruitment. Participants from both these investigations are derived from similar catchment areas, hence providing an attractive opportunity for RACE to utilize PROMIS controls as common controls for genetic investigations. Controls in PROMIS were recruited following procedures and inclusion criteria as adopted for RACE cases. In order to minimize any potential selection biases, PROMIS controls selected for this stroke substudy were frequency matched to RACE cases based on age and gender and were recruited in the following order of priority: (1) non-blood related or blood related visitors of patients of the out-patient department; (2) non-blood related visitors of stroke patients; (3) patients of the out-patient department presenting with minor complaints (e.g. back pain, minor gastric complaints). Control subjects from the PROMIS study were genotyped at the Wellcome Trust Sanger Institute on the Illumina 660W Quad array. The Center for Non-Communicable Diseases, Pakistan, serves as the coordinating center for both RACE and PROMIS. More information on these research investigations can be found at www.cncdpk.com. This young onset stroke component to the RACE study was funded through the Gene Environment Association Studies initiative (GENEVA, www.genevastudy.org as one of three studies designed to assess the genetics of young onset stroke and modification of genetic effects by smoking. GENEVA is part of the trans-NIH Genes, Environment, and Health Initiative (GEI). Genotyping of 1,220 young onset stroke cases was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to stroke through large-scale genome-wide association studies of cases and controls recruited within Pakistan. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000456

• High-Risk Breast Cancer GWAS

  The GWAS includes High Risk Women from the following epidemiological studies of breast cancer, comprising a total of 3,719 cases and 3,642 controls (cases/controls: MEC, 0/200; ABCFR, 326/418; FCCC, 56/3; BCFR-UT, 66/32; CNIO-BC, 87/92; GESBC, 65/0; LIFE, 164/0; MARIE, 41/105; MAYO, 208/210; MNYR, 293/409; MSKCC, 310/0; NC-BCFR, 234/233; OFBCR, 553/560; POSH, 377/0; HBOC, 47/47; BBCS, 612/1333; UPENN, 280/0 This study was funded by a grant CA165038 to Christopher Haiman (University of Southern California) and John Hopper (University of Melbourne) from the National Cancer Institute, National Institute of Health. The contributing studies: Multiethnic Cohort (MEC). This study was supported by grant UM1 CA164973 from the National Cancer Institute, National Institute of Health. Ontario Familial Breast Cancer Registry, the Ontario site of the Breast Cancer Family Registry Cohort (OFBCR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Utah Breast Cancer Family Registry (BCFR-UT). This study was supported by grant UM1 CA164920 from the National Cancer Institute. New York site of the Breast Cancer Family Registry (MNYR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Northern California site of the Breast Cancer Family Registry (NC-BCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Australian Breast Cancer Family Registry (ABCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Breast Cancer Study (CNIO-BC). This study has been partially funded by The Spanish Network on Rare Diseases (CIBERER) and the Spanish National Genotyping Center (CEGEN). Genetic Epidemiologic Study of Breast Cancer (GESBC). The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and German Cancer Research Center (DKFZ). Mammary Carcinoma Risk Factor Study (MARIE). This study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Hereditary Breast and ovarian Cancer: Genetic and Molecular Studies (HBOC). This study was supported by National Cancer Institute grant CA58860 and The Lon V Smith Foundation: LVSF-44528. Mayo Clinic inherited breast and ovarian cancer study (MAYO). This study was supported by the Breast Cancer Research Foundation, NIH grants CA192393, CA176785, and an NIH CA116201 Specialized Program of Research Excellence (SPORE) in Breast Cancer. British Breast Cancer Study (BBCS); Mammographic oestrogens and growth factor study (MOG). The BBCS and the MOG study are funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledge NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). Genotyping of non-BRCA1/2 mutation carriers (UPENN). The study is supported by the Basser Research Center at the University of Pennsylvania, Rooney Family Foundation, NIH grants CA176785 and CA192393, the Breast Cancer Research Foundation, the Susan G. Komen Foundation for the Cure and Macdonald Family Foundation. Clinical Significance of Germline BRCA Mutations (MSKCC). The study is supported by the Robert and Kate Niehaus Clinical Cancer Genetics Research Initiative, The Breast Cancer Research Foundation, and the Cancer Center Support Grant from the National Institute of Health, National Cancer Institute 5P30 CA08748-40. Women&#39;s Learning the Influence of Family and Environment (LIFE). This study was supported by grants CA17054 and CA74847 from the National Cancer Institute, National Institutes of Health, No. 4PB-0092 from the California Breast Cancer Research Program of the University of California. Philadelphia site of the Breast Cancer Family Registry at Fox Chase Cancer Center (FCCC). This study is supported by NIH grant CA164920.

  Study phs000929

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• Security Overview

  Security Overview The European Genome-phenome Archive (EGA) houses consented human data under controlled access. Access decisions are handled by the relevant Data Access Committee (DAC), which autonomously manages requests through the DAC Portal. This document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. As security is a prime concern of the EGA, the EGA is a member of the Global Alliance for Genomics and Health (GA4GH) Data Security work stream. The EGA contributes and helps develop the recommendations outlined the GA4GH Security Technology Infrastructure document, which defines guidelines, best practices, and standards for building and operating an infrastructure that promotes responsible data sharing in accordance with the GA4GH Privacy and Security Policy. Explore the EGA dataflow to gain deeper insights! Accessing data in the EGA involves several steps. First, users need to create an EGA account. Once logged in, they can request access to data controlled by a DAC through the EGA website (see documentation). The DAC oversees these requests through the DAC Portal, and if approved, grants the necessary permissions to the user's EGA account, allowing them to access and download all relevant data and metadata for the requested dataset(s). The key points of EGA security strategy are: 1 Regular Risk Assessment The EGA regularly identifies and assesses risk related to the following: Breach of confidentiality,Breach of privacy or autonomy,Malicious or accidental corruption or destruction of data archived at EGA,Disruption of services provided by the EGA. 2 Risk mitigation The EGA implements and maintains safeguards to minimise the risks identified above in accordance with the 6 control objectives listed in Appendix 1 and outlined in the GA4GH Security and Infrastructure document.If a breach is discovered, the EGA applies a defined protocol to minimise damage. 3 Identity and authorisation management The EGA authenticates the identity of individuals or software accessing controlled access data held at the EGA.The EGA ensures an appropriate level of assurance (LoA) is applied to the identity consistent with the risk associated with that individual, such as multi-factor authentication for DACs.The EGA provides the minimum access rights and privileges consistent with the user’s identity, allowing access consistent with the GA4GH Privacy and Security Policy, as determined by the appropriate DAC. 4 Audit Logs The EGA maintains a set of logs recording: Changes to user access rights,Data access requests,Resource usage. 5 Cryptography, communication security, and data integrity The EGA ensures data transmission integrity using a hash function.All data transmitted to or from the EGA is end-to-end encrypted.All data at EGA is stored using strong encryption.Encryption keys are not stored in the same system as the encrypted data.All data archived at EGA must be accompanied by a signed submission statement ensuring appropriate consent or ethical approval has been obtained, and is in accordance with all applicable laws and regulations. The EGA has a defined protocol defining the response in the event of a security breach, and is continuing to work with the GA4GH Data Security Work Stream to help define best practice and associated standards for breach responses. Appendix 1 GA4GH Control Objectives Control Objective 1: Implement technology safeguards to minimise the risk of unauthorised access, use, or disclosure of confidential and private data.Control Objective 2: Implement technology safeguards to minimise the risk of discovery, access, and use of individuals’ clinical and genomic data, and individual identities, other than as authorised by applicable jurisdictional law, institutional policy, and individual consents.Control Objective 3: Implement technology safeguards to minimise the risk of accidental or malicious corruption or destruction of data.Control Objective 4: Implement technology safeguards to minimise the risk of disruption, degradation, and interruption of services enabling access to data.Control Objective 5: Implement technology safeguards to minimise the risk of potential security attacks and misuse of authorised accesses and privileges.Control Objective 6: Implement technology safeguards to promptly detect the failure to attain the above control objectives and to respond with proper countermeasures.Appendix 2Refer to the document below to learn more about EGA long-term data preservation policy and procedures at EMBL-EBI.Long-term data preservation

  Documentation about/security