Simultaneous Pathway Activity Inference and Global Gene Expression Analysis Using RNA Sequencing
Data accompanied with the paper "Simultaneous Pathway Activity Inference and Global Gene Expression Analysis Using RNA Sequencing" The data is generated using TF-seq experimental technique that measures binding activity of more than 40 different transcription factors in parallel. It covers three experiments: * Stimulation of wild-type and Myd88 knockout BMDMs with 12 different pathogen associated molecular patterns (PAMPs) * Small molecule screen on BMDMs * Dose-response experiment using Halofuginone on BMDMs, with and without LPS stimulation The data consists of : * fastq files * associated well and reporter tags * counts of all reads, RNA and DNA UMIs * script we used to convert fastq files to count matrices
Steps to reproduce
To translate fastq files to count tables one has to decompose the read to following parts (using positions starting from 1) UMI: positions 1-10 well tag: positions 11-16 reporter tag: reverse complement of positions 17-33 These pieces of sequence can be mapped against the associated vectag and welltag files, to count the occurrences of certain reads corresponding to certain reporter in certain well.