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fluidigm-ht-c1-rnaseq

Summary

This pipeline analyses RNA sequencing data produced with the Fluidigm Single cell sequencing C1 mRNA Seq HT protocol.

Following conventional bcl2fastq demultiplexing, it uses fluidigm API script for demultiplexing the row barcodes (N=40) of column samples using R1 reads. Subsequently R2 reads are poly-A trimmed (with prinseq-lite) and aligned to given reference genome using the STAR mapper.

See cfg/references.yaml for references used by default (also refer to option --references-cfg). Output of STAR includes the uniquely mapped genome bam file, transcripts mapped bam file, gene based read count matrix, wiggle files etc. (see below). For running STAR we follow recipes given here.

The transcripts/genes expression abundance are estimated by STAR and RSEM (reusing STAR's BAM file). The RSEM results matrix contains mapped reads count and TPM (normalized value) of genes and isoforms.

The pipeline also provides generic stats, coverage, mappability, QC e.g. by running RNA-SeQC.

Note, STAR is very fast and in order to avoid trouble with STAR's shared memory option we align samples sequentially.

A word of warning: Please do not use the underscore symbol ("_") in your sample name, otherwise the fluidigm demultiplexer will crash!

Output

The following lists the most important files/directories that are created per sample in correspondingly named subfolders:

STAR

  • Mapped genome BAM: {sample}_{genome}_Aligned.sortedByCoord.out.bam
  • Mapped transcriptome BAM (RSEM input): {sample}_{genome}_Aligned.toTranscriptome.out.bam
  • Visualization: Wiggle files (*.wig)
  • Read count (genes): {sample}_{genome}_ReadsPerGene.out.tab
  • Mappability stats: {sample}_{genome}_Log.final.out

Exact STAR mapping parameters can be looked up in the Snakefile.

RSEM

  • Genes expression values with annotation: {sample}_{genome}_RSEM.genes.results.desc
  • Isoforms expression values with annotation: {sample}_{genome}_RSEM.isoforms.results.desc
  • Visualization: Wiggle files (*.wig)
  • Plots: {sample}_{genome}_RSEM.pdf

RNA-SeQC

QC and rate of rRNA and distribution of reads on transcripts:

  • countMetrics.html
  • metrics.tsv