Practical Bioinformatics Mark Voorhies 5/29/2019 Mark Voorhies Practical Bioinformatics
Example Pipeline: Overview Mark Voorhies Practical Bioinformatics
Example Pipeline: Overview Generate Genome Transfer Pre-process Samples Coverage & Archival Transcriptome Pro fi le Di ff erential ~2.5-4 years Expression Annotation/ Analysis Paper (publish) Mark Voorhies Practical Bioinformatics
Example Pipeline: Overview Generate Genome Transfer Pre-process Samples Coverage & Archival Transcriptome Pro fi le ~1 day Di ff erential ~2.5-4 years Expression Annotation/ Analysis Paper (publish) Mark Voorhies Practical Bioinformatics
Example Pipeline: Overview Generate Genome Transfer Pre-process Samples Coverage & Archival Transcriptome Pro fi le ~1 day Di ff erential ~2.5-4 years Expression Annotation/ Analysis Follow-up Experiments Paper (publish) Mark Voorhies Practical Bioinformatics
Example Pipeline: Overview Generate Genome Transfer Pre-process Samples Coverage & Archival Transcriptome Pro fi le ~1 day Di ff erential ~2.5-4 years Expression Annotation/ Analysis Follow-up Experiments Paper (publish) Mark Voorhies Practical Bioinformatics
Example Pipeline: Overview Mark Voorhies Practical Bioinformatics
Example Pipeline: Details Mark Voorhies Practical Bioinformatics
GSE88801 Pipelines Mark Voorhies Practical Bioinformatics
Abundance estimation with kallisto Index transcript kmers Mark Voorhies Practical Bioinformatics
Abundance estimation with kallisto Assume a uniform Index transcript kmers transcriptional pro fi le abundance transcript Mark Voorhies Practical Bioinformatics
Abundance estimation with kallisto Assume a uniform Index transcript kmers transcriptional pro fi le abundance Assign reads based on pro fi le transcript Mark Voorhies Practical Bioinformatics
Abundance estimation with kallisto Assume a uniform Index transcript kmers transcriptional pro fi le abundance Assign reads based on pro fi le transcript Update pro fi le based on assignments abundance transcript Mark Voorhies Practical Bioinformatics
Abundance estimation with kallisto Assume a uniform Index transcript kmers transcriptional pro fi le abundance Assign reads based on pro fi le transcript Update pro fi le based on assignments abundance transcript Mark Voorhies Practical Bioinformatics
Abundance estimation with kallisto Assume a uniform Index transcript kmers transcriptional pro fi le abundance Assign reads based on pro fi le transcript Update pro fi le based on assignments abundance transcript abundance transcript Mark Voorhies Practical Bioinformatics
Abundance estimation with kallisto transcriptome=”GRCm38 all mRNA” export while read i ; do export jobname=”$ { i } . $ { transcriptome } . f r ” k a l l i s t o quant − i ”$ { transcriptome } . idx ” \ − t 4 −− s i n g l e −− fr − stranded − l 250 − s 50 − o ”$ { jobname } ” ”$ { i } 1 . f a s t q . gz” \ > ”$ { jobname } . log ” \ 2 > ”$ { jobname } . e r r ” done < sample names . t x t Mark Voorhies Practical Bioinformatics
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