<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Kanishk Asthana</submitter><organism>mixed sample</organism><software>ChronoSeq-Tools</software><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15965</full_dataset_link><description>We checked our ability to uniquely identify each Time-Tag. We did this by mixing beads from odd numbered Time-Tags with human cells and even numbered Time-Tags with mouse cells manually in bulk. These beads were then washed and combined for Reverse Transcription, library preparation and sequencing. Time-Tag resolved cleanly into either human or mouse dominant with 1.6% or less mixed beads detected for each Time-Tag.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Nucleic Acid Extraction - Oligo-DT beads were used to capture mRNA from lysed Single-Cells inside droplets.</sample_protocol><sample_protocol>Sample Collection - Cells were manually mixed directly with the beads. 10μl of Time-Tagged beads at 450 beads/μl suspended in lysis buffer were directly mixed with 8μl of mouse or human cells at 600cells/μl. Odd numbered Time-Tags were mixed with human(K562) cells while even numbered Time-Tags were mixed with mouse(EL4) cells.</sample_protocol><sample_protocol>Library Construction - Beads are washed once with 6X SSC buffer and then twice with 1.25X RT buffer. Beads were then pooled together for a single RT reaction. very similar to Drop-seq. https://kanishkasthana.github.io/ChronoSeq/protocol_library_preparation_for_dropseq_chronoseq_beads.html</sample_protocol><sample_protocol>Growth Protocol - K562 and EL4 cells grown in suspension in DMEM with 10% FBS and 1%PEN-STREP at 5%CO2 and 37C.  https://kanishkasthana.github.io/ChronoSeq/protocol_for_preparing_cells_AdditionalFiltration.html</sample_protocol><sample_protocol>Sequencing - Illumina NovaSeq X 10B on one lane in PE150 configuration with Custom Read 1 primer. 10% PhiX spike in. Mix primers with Illumina Primers</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Sequence Alignment - mm10-hg19 Drop-seq mixed reference used for alignment. Data processed using ChronoSeq-Tools pipeline. https://github.com/kanishkasthana/ChronoSeq-Tools</data_protocol><data_protocol>Data Transformation - UMIs and gene information were used to generate unique transcripts captured and remove PCR duplicates using Drop-seq tools.</data_protocol><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq X</instrument_platform><study_type>RNA-seq of coding RNA</study_type><species>mixed sample</species><pubmed_authors>Kanishk Asthana</pubmed_authors></additional><is_claimable>false</is_claimable><name>Bulk K562 and EL4 cells mixed with 12 Time-Tags for verification (QC) for ChronoSeq Beads</name><description>We checked our ability to uniquely identify each Time-Tag. We did this by mixing beads from odd numbered Time-Tags with human cells and even numbered Time-Tags with mouse cells manually in bulk. These beads were then washed and combined for Reverse Transcription, library preparation and sequencing. Time-Tag resolved cleanly into either human or mouse dominant with 1.6% or less mixed beads detected for each Time-Tag.</description><dates><release>2025-11-03T00:00:00Z</release><modification>2026-05-26T17:12:38.337Z</modification><creation>2025-11-03T16:24:21.092Z</creation></dates><accession>E-MTAB-15965</accession><cross_references><ENA>ERP183602</ENA><Biostudies>E-MTAB-15927</Biostudies><Biostudies>E-MTAB-15928</Biostudies><Biostudies>E-MTAB-15956</Biostudies><Biostudies>E-MTAB-15955</Biostudies><Biostudies>E-MTAB-15947</Biostudies><Biostudies>E-MTAB-15946</Biostudies><Biostudies>E-MTAB-15894</Biostudies><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0003789</EFO><EFO>EFO_0004917</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0003738</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>