qcAndSalmon | R Documentation |
Fetch raw sra files named in sampTab and convert to fastq (using SRA toolkit), trim reads to standard length, run QC by aligning sub-sampled fastq files aginst several genomes (human, mouse, zebrafish, fly, ecoli, yeast), and counting hits to genomic features of the target genome. Finish by estimating gene expression levels with Salmon.
qcAndSalmon(sampTab, studyID, bucket = "cellnet-rnaseq",
finalLength = 40, subProp = 0.001, target = "mouse",
gtfFile = "/media/ephemeral1/dat/ref/Mus_musculus.GRCm38.83.gtf",
salmonIndex = "/media/ephemeral1/dat/ref/MM_GRCh38.SalmonIndex.030816")
sampTab |
sample table |
studyID |
study id |
bucket |
S3 bucket where to put the results |
finalLength |
final length of reads |
subProp |
proportion of reads to sample from for QC |
target |
species/genome for expression estimates |
gtfFile |
genomic feature of target genome for QC |
salmonIndex |
path to salmon index for expression estimation |
sample table with QC measures appened
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