R4RA molecular paper: RNAseq and metadata

This dataset has been used in our study that was recently accepted by Nature Medicine: "Rituximab versus tocilizumab in rheumatoid arthritis: Synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial". <br><br>Sample collection protocol:A minimum of 6 samples (ultrasound-guided synovial biopsies) per patient were immediately immersed in RNA-Later. All patients provided written informed consent before the synovial tissue biopsy procedure. They were fulfilling 2010 ACR/EULAR classification criteria for RA and were eligible for treatment with rituximab therapy according to UK NICE guidelines, i.e. failing or intolerant to csDMARD therapy and at least one biologic therapy (excluding trial IMPs) were recruited when fulfilling the trial inclusion/exclusion criteria (for the full study protocol and baseline patient characteristics see Humby et al). The patients were recruited under R4RA clinical trial.<br><br><br>RNAseq: <br>Image analysis and base calling were conducted by the HiSeq Control Software (HCS). Raw sequence data (.bcl files) generated from Illumina HiSeq was converted into fastq files and de-multiplexed using Illumina's bcl2fastq 2.17 software. One mismatch was allowed for index sequence identification.<br>Fastq files were trimmed to remove the Illumina adaptors using bbduk from the BBMap package version 37.93 using the default parameters. Transcripts were then quantified using Salmon version 0.13.1 and an index generated from the Gencode release 29 transcriptome following the standard operating procedure.<br>Tximport version 1.13.10 was used to aggregate the transcript level expression data to genes, counts were then subject to variance stabilizing transformation (VST) and transcripts per million (TPM) using the DESeq2 version 1.25.9 package and in-house script, respectively.<br>