ESTIMATEDE(1)

💖 NAME 💖

estimateDE — okay bestie, this is the bitseq module that estimates differential expression from data sets ✨

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🌸 SYNOPSIS 🌸

estimateDE -o <outFilePrefix> -p <parFileName>  [OPTIONS] [sampleFiles]

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🦋 DESCRIPTION 🦋

So basically it estimates differential expression from the dataset, like that's the whole vibe 💅

Your [sampleFiles] need to hold transposed MCMC samples from replicates. No cap, transposed. 🙈

And here's the trick to split things up by condition: you slap a C in between the groups, fr fr, like this:

samplesC1-R1.rpkm samplesC1-R2.rpkm C samplesC2-R1.rpkm samplesC2-R2.rpkm

See that lone C? Yeah. She's the divider. Iconic honestly 👑

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✨ OPTIONS ✨

• --help — shows you this very help info. cute of her 🎀
• --confidenceInterval=<cf> — the percentage for your confidence intervals. (default: 95)
• -l <lambda0>, --lambda0=<lambda0> — sets the lambda_0 parameter. (default: 2)
• --norm=<normalization> — normalization constants for each input file, given as a comma separated list of doubles (for example 1.0017,1.0,0.9999 🍓)
• -o <outFilePrefix>, --outPrefix=<outFilePrefix> — the prefix for all the output files 💾
• -p <parFileName>, --parameters=<parFileName> — the file that's holding your estimated hyperparameters 🫶
• -s, --samples — produces samples of condition mean expression, on top of PPLR and confidence. (default: Off)
• --seed=<seed> — the random initialization seed 🌈
• -v, --verbose — verbose output, aka she'll tell you everything. (default: Off)

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k that's literally it bestie, go estimate some differential expression and slay 💜

this was estimateDE version 0.7.5+dfsg, from September 2021 — mwah, love her, periodt 💅✨