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Commit 05c84c4b authored by Blaise Li's avatar Blaise Li
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Merge branch 'master' of gitlab.pasteur.fr:bli/bioinfo_utils

parents bc8c60d0 bd07159a
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...@@ -20,6 +20,15 @@ major, minor = sys.version_info[:2] ...@@ -20,6 +20,15 @@ major, minor = sys.version_info[:2]
if major < 3 or (major == 3 and minor < 6): if major < 3 or (major == 3 and minor < 6):
sys.exit("Need at least python 3.6\n") sys.exit("Need at least python 3.6\n")
# TODO (04/10/2022):
# * normalize spike-in counts by their length (RPKM)
# * use scikit-learn to have a correction factor for transcript RPKM
# TODO first (04/10/2022):
# * output normalizations by total spike-ins (currently normalization is hard-coded to use protein_coding): raw from featureCounts / spike and RPKM (M would be "by million spike-in reads")
# * output slope and intercept of spike-in response in a file (and on the plot?)
# * find example config file activating spike-in stuff
# TODO: plot spike-in vs spike-in between libraries to detect anormal spike-ins: should be a straight line # TODO: plot spike-in vs spike-in between libraries to detect anormal spike-ins: should be a straight line
# TODO: Add rules to take into account spike-ins. # TODO: Add rules to take into account spike-ins.
...@@ -1408,7 +1417,10 @@ rule plot_spikein_responses: ...@@ -1408,7 +1417,10 @@ rule plot_spikein_responses:
title=f"{libname} spike-ins TPM response") title=f"{libname} spike-ins TPM response")
# TODO: gather squared_diffs across libraries and find the most stable spike-ins # TODO: gather squared_diffs across libraries and find the most stable spike-ins
# Then use those to compute slope again and use it for normalization # Then use those to compute slope again and use it for normalization
# TODO (04/10/2022): save regline_slope and regline_intercept somewhere.
( (
# Not the data transformed by LinearRegression
# Just pre-processed data
transformed_data, transformed_data,
regline_slope, regline_slope,
regline_intercept, regline_intercept,
......
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