CITE-seq performed as described previously (29 (link)). 500,000 cells were resuspended in PBS + 1% FBS and spun at 300g for 10 minutes at 4oC and then resuspended in 25 μL staining buffer (BioLegend #420201). 2.5 μL human TruStain FcX (BioLegend #42230) was added per sample and incubated at 4oC for 10 minutes. Hash-Tag Antibodies, used to label the samples and minimize batch effects, were added at 250 ng/sample (0.5 μL/sample) and incubated at 4oC for 30 minutes. Cells were washed twice in 1 mL staining buffer and spun at 300g for 5 minutes at 4oC. Samples were pooled 1:1 at 1000 cells/μL and libraries were generated using the 3’ V3 10X Genomics Chromium Controller following the manufacturer’s protocol (CG000183). Final library quality was assessed using the Tapestation 4200 (Agilent) and libraries were quantified by Kapa qPCR (Roche). Pooled libraries were then subjected to paired-end sequencing according to the manufacturer’s protocol (Illumina NovaSeq 6000). Bcl2fastq2 Conversion Software (Illumina) was used to generate de-multiplexed Fastq files and the CellRanger (3.1) Pipeline (10X Genomics) was used to align reads and generate count matrices. Further quality control and analyses were performed in R (see Lawlor Lab Github for code).
Bcl2fastq2 conversion software
Manufactured by Illumina
Sourced in United States
Bcl2fastq2 Conversion Software is a bioinformatics tool developed by Illumina to convert BCL files, which are the primary output format from Illumina sequencing instruments, into FASTQ files. FASTQ files are a widely used format for storing and sharing sequencing data. The software performs the necessary conversion and demultiplexing of sequencing data, enabling downstream analysis and data sharing.
Automatically generated - may contain errors
Lab products found in correlation
2100 bioanalyzer, by Agilent Technologies (11 mentions)
Novaseq 6000, by Illumina (10 mentions)
Kapa library quantification kit, by Roche (8 mentions)
Trizol reagent, by Thermo Fisher Scientific (8 mentions)
Hiseq 3000, by Illumina (7 mentions)
Fragment analyzer, by Agilent Technologies (5 mentions)
Kapa stranded mrna sample kits with indexed adaptors, by Roche (5 mentions)
Direct zol rna miniprep kit, by Zymo Research (4 mentions)
Tapestation 2200, by Agilent Technologies (4 mentions)
Kapa qpcr, by Roche (3 mentions)
Tapestation 4200, by Agilent Technologies (3 mentions)
Truseq stranded mrna reagents, by Illumina (3 mentions)
Cellranger 3.1 pipeline, by 10x Genomics (2 mentions)
Sciclone liquid handling robot, by PerkinElmer (2 mentions)
Hiseq 3000 4000 sr cluster kit reagents, by Illumina (2 mentions)
Hiseq 3000 4000 sbs kit reagents, by Illumina (2 mentions)
Nextseq500 ho flowcells, by Illumina (2 mentions)
Truseq rna exome library kit, by Illumina (2 mentions)
Agilent high sensitivity dna kit, by Illumina (2 mentions)
Kapa mrna hyperprep kit, by Roche (2 mentions)
48 protocols using bcl2fastq2 conversion software
1
Single-Cell CITE-seq Analysis Protocol
2
Bovine miRNA Sequencing and Analysis
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The base call files from the sequencing run were de-multiplexed and converted into FASTQ files using the bcl2fastq2 conversion software, version 2.20 (Illumina). The FASTQ-formatted sequence data were quality-checked using FastQC version 0.11.965 . The sequence data were pre-processed using Trim Galore (v0.6.6) to remove low-quality and adapter-like sequences (https://github.com/FelixKrueger/TrimGalore ). The detection and expression profiling of miRNA was performed using the miRDeep2 software package66 (link),67 (link). Briefly, the pre-processed high-quality reads [by trimming low-quality reads (mean Q-score < 20) and filtering too short or too long reads (> 26 or < 16 nucleotides)] were aligned to the bovine reference genome assembly, ARS-UCD1.2 using mirDeep2. Known and novel miRNA in the sequencing samples were detected by the miRDeep2 algorithms based on positional alignment, secondary RNA structure, entropy, biogenesis-based model, and the reference of bovine miRNA and conserved miRNA cross-species (human and mouse) from miRBase 22 release. Novel miRNA were excluded from further analysis.
3
Transcriptomic Analysis of Primary Brain Endothelial Cells
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Ch25hfl/fl and Ch25hECKO female mice were injected with tamoxifen. Nine brains per genotype were pooled and primary brain microvascular endothelial cells (pMBMEC) were isolated and plated in a 96‐well plate (2 wells/brain). Confluent pMBMEC were left unstimulated or stimulated IL‐1β for 24 h. RNA of three wells was pooled to obtain one replicate for RNA sequencing. The Lausanne Genomic Technologies Facility performed the RNA‐seq. RNA quality was assessed on a Fragment Analyzer (Agilent Technologies), and all RNAs had a RQN between 8.7 and 10. RNA‐seq libraries were prepared from 500 ng of total RNA with the Illumina TruSeq Stranded mRNA reagents (Illumina) using a unique dual indexing strategy, and following the official protocol automated on a Sciclone liquid handling robot (PerkinElmer). Libraries were quantified by a fluorometric method (QubIT, Life Technologies) and their quality assessed on a Fragment Analyzer (Agilent Technologies).
Cluster generation was performed with 2 nM of an equimolar pool from the resulting libraries using the Illumina HiSeq 3000/4000 SR Cluster Kit reagents and sequenced on the Illumina HiSeq 4000 using HiSeq 3000/4000 SBS Kit reagents for 150 cycles (single end). Sequencing data were demultiplexed using the bcl2fastq2 Conversion Software (version 2.20, Illumina).
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Ch25hfl/fl and Ch25hECKO female mice were injected with tamoxifen. Nine brains per genotype were pooled and primary brain microvascular endothelial cells (pMBMEC) were isolated and plated in a 96‐well plate (2 wells/brain). Confluent pMBMEC were left unstimulated or stimulated IL‐1β for 24 h. RNA of three wells was pooled to obtain one replicate for RNA sequencing. The Lausanne Genomic Technologies Facility performed the RNA‐seq. RNA quality was assessed on a Fragment Analyzer (Agilent Technologies), and all RNAs had a RQN between 8.7 and 10. RNA‐seq libraries were prepared from 500 ng of total RNA with the Illumina TruSeq Stranded mRNA reagents (Illumina) using a unique dual indexing strategy, and following the official protocol automated on a Sciclone liquid handling robot (PerkinElmer). Libraries were quantified by a fluorometric method (QubIT, Life Technologies) and their quality assessed on a Fragment Analyzer (Agilent Technologies).
Cluster generation was performed with 2 nM of an equimolar pool from the resulting libraries using the Illumina HiSeq 3000/4000 SR Cluster Kit reagents and sequenced on the Illumina HiSeq 4000 using HiSeq 3000/4000 SBS Kit reagents for 150 cycles (single end). Sequencing data were demultiplexed using the bcl2fastq2 Conversion Software (version 2.20, Illumina).
4
Nexterra TruSeq Library Preparation and Sequencing
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HMW DNA for the blood and tumor tissue was independently sheared and used as starting materials for the Nextera TruSeq Library Preparation with PCR amplification. Each sample underwent 2 × 150 cycle sequencing on an Illumina HiSeq X Ten instrument generating a mean coverage of 36.5X for the blood and 69.06X for the tumor, with a mapped read rate of 98.01% and 98.33%, respectively (Supplementary Table 1 ).
Sequenced reads were adapter-trimmed using Illumina's Bcl2fastq2 Conversion software (http://www.illumina.com/ ) and filtered using cutadapt v1.9 [59 ] to remove bases < Q15, reads < 70 bp and missing paired-reads. Filtered reads were aligned to the human reference genome Hg19 (http://hgdownload.soe.ucsc.edu/goldenPath/hg19 ) using bwa-mem v0.7.12 [60 (link)]. The GATK Pipeline v3.5 [61 (link), 62 (link)] was used for identifying duplicate reads, performing local re-alignment at indel intervals, base quality score recalibration and co-realignment of the tumor-blood pair. Mapping statistics were calculated using QualiMap v2.1.3 [63 (link)].
Sequenced reads were adapter-trimmed using Illumina's Bcl2fastq2 Conversion software (
5
Single-Cell RNA-Seq Data Processing Pipeline
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Raw sequencing reads were transformed into fastq file with Illumina bcl2fastq2 Conversion Software v2.20 at https://support.illumina.com/downloads/bcl2fastq-conversion-software-v2-20.html , and quality checked with FastQC software v0.11.9, at https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ . Standard pipelines of cell ranger were used to do sequence processing, alignment to GRch38 genome with default parameters (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/ ).
6
Differential Transcript Profiling via RNA-seq
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Sequencing data was demultiplexed to generate FASTQ files using Illumina bcl2fastq2 Conversion Software. FASTQ files were assessed with FastQC22 ,23 to verify that there was high sequence quality, expected sequence length, and no adapter contamination. Paired-end FASTQ files for each replicate were mapped to the Ensembl human reference transcriptome (GRCh38)24 (link) using Kallisto25 (link),26 . Abundance data generated with Kallisto was read into R, annotated with Ensembl human gene annotation data (version 86)24 (link), and summarized as log2 counts per million (cpm) at the transcript level. Transcripts with greater than 0.2488206 cpm in at least 3 samples were retained after filtering. This threshold was chosen because it selected for transcripts with at least 10 counts in the smallest library sample. Samples were normalized with the trimmed mean of M values (TMM) method27 (link). The R package ‘limma’28 (link) was used to identify differentially expressed transcripts by first applying precision weights to each transcript based on its mean-variance relationship using the VOOM function and then linear modeling and Bayesian statistics were employed to detect transcripts that were up- or down-regulated in each condition. Transcripts with an adjusted P-value < 0.05 and |log2 fold change| > 1 were considered significantly differentially expressed.
7
Comprehensive Genomic Variant Profiling
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De‐multiplexing was performed using bcl2fastq2 Conversion Software (Illumina). Alignment was performed on University of California Santa Cruz human genome reference build 19 using the Burrows‐Wheeler Aligner. Genome Analysis Toolkit (GATK) and PICARD tools were used for base quality score recalibration (BaseRecalibrator) and realignment (RealignerTargetCreator, IndelRealigner), as recommended by Eurogentest guidelines (Matthijs et al., 2016). Variant calling was performed using GATK HaplotypeCaller and annotated using EnsemblVariantEffectPredictor. Copy number variation analysis was performed using ExomeDef. Variants were filtered for quality score ≥ 30, depth ≥ 50x, and present in ≥20% of reads.
8
Illumina Sequencing of cf-tDNA
9
RNA Exome Library Preparation and Sequencing
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Sequencing libraries were generated using the TruSeq RNA exome library kit (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions.
Libraries were quantitated by qPCR using the KAPA library quantification kit–Illumina/ABI Prism (Kapa Biosystems, Wilmington, MA, USA) and validated using the Agilent high-sensitivity DNA kit on a bioanalyser. Libraries were normalized to 2.6 pM and subjected to cluster and paired-end read sequencing, performed for 2 × 75 cycles on two NextSeq500 HO flow cells (Illumina), according to the manufacturer’s instructions. Sequencing depth was 30 million reads/sample. Base calling was performed using the NextSeq500 instrument and RTA 2.4.6. FASTQ files were generated using bcl2fastq2 conversion software (v.2.17; Illumina).
Libraries were quantitated by qPCR using the KAPA library quantification kit–Illumina/ABI Prism (Kapa Biosystems, Wilmington, MA, USA) and validated using the Agilent high-sensitivity DNA kit on a bioanalyser. Libraries were normalized to 2.6 pM and subjected to cluster and paired-end read sequencing, performed for 2 × 75 cycles on two NextSeq500 HO flow cells (Illumina), according to the manufacturer’s instructions. Sequencing depth was 30 million reads/sample. Base calling was performed using the NextSeq500 instrument and RTA 2.4.6. FASTQ files were generated using bcl2fastq2 conversion software (v.2.17; Illumina).
10
Next-Generation Sequencing QC and Bioinformatic Analysis
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Upon completion of the sequencing run, WC AGTC staff verify that the quality of the sequencing run meets basic QC standards (Q30 ≥ 75%, clusters passing filter ≥ 75%, and cluster density 140–240 K/mm2). A QC report is generated including a coverage calculation and percentage of reads passing filter for each sample, as well as the total reads passing filter for the whole run. Before bioinformatic analyses could be performed, the eight bcl files per sample were demultiplexed and converted into one R1.fastq.gz and one R2.fastq.gz file using Illumina’s bcl2fastq2 Conversion Software (hosted on a local instance of Galaxy). Converted .fastq files were parsed out according to the WCBL project code and saved on local, shared servers. Once QC analysis and bcl2fasq conversion were complete, the WC AGTC shared the QC report and filepath locations of the converted .fastq files. Each unit within WCBL performs further project-specific analyses, including, but not limited to additional QC according to parameters established by project partners (Table 1 ). Project-specific bioinformatic analysis, data sharing with collaborators and/or surveillance networks as appropriate, and the creation of various reports are completed by each unit as required.
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