Convenience package for parsing RNA-seq quantification results
Project description
## readquant
This package contains helper functions for parsing both expression values
and technical features from common RNA-seq quantification tools.
The goal is to simplify going from a collection of quantification results to
expression table, as well as sample meta data.
A minimal example could look something like this:
In [1]: from readquant import read_quants, read_qcs
In [2]: tpm = read_quants('salmon/*E4_salmon_out', version='0.4.0')
In [3]: tpm.head()
Out[3]:
salmon/1771-026-195-E4_salmon_out \
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
salmon/1771-026-190-E4_salmon_out \
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
salmon/1771-026-196-E4_salmon_out \
Name
ERCC-00158 0.000
ERCC-00154 906.236
ERCC-00150 0.000
ERCC-00143 0.000
ERCC-00142 0.000
salmon/1771-026-198-E4_salmon_out \
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
salmon/1771-023-118-E4_salmon_out \
Name
ERCC-00158 0.00000
ERCC-00154 9.35988
ERCC-00150 0.00000
ERCC-00143 724.44800
ERCC-00142 0.00000
salmon/1771-026-193-E4_salmon_out
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
In [4]: sample_info = read_qcs('salmon/*_salmon_out', version='0.4.0', flen_lim=(10, 100))
In [5]: sample_info.head()
Out[5]:
percent_mapped num_processed \
salmon/1771-026-197-G4_salmon_out 71.8270 2665988.0
salmon/1771-026-198-D2_salmon_out 67.7853 3841894.0
salmon/1771-026-195-H7_salmon_out 73.4492 3875822.0
salmon/1771-026-194-E9_salmon_out 47.5425 979446.0
salmon/1771-026-195-E4_salmon_out 56.3955 5051277.0
global_fl_mode robust_fl_mode
salmon/1771-026-197-G4_salmon_out 103.0 103.0
salmon/1771-026-198-D2_salmon_out 122.0 122.0
salmon/1771-026-195-H7_salmon_out 110.0 110.0
salmon/1771-026-194-E9_salmon_out 111.0 111.0
salmon/1771-026-195-E4_salmon_out 111.0 111.0
This package contains helper functions for parsing both expression values
and technical features from common RNA-seq quantification tools.
The goal is to simplify going from a collection of quantification results to
expression table, as well as sample meta data.
A minimal example could look something like this:
In [1]: from readquant import read_quants, read_qcs
In [2]: tpm = read_quants('salmon/*E4_salmon_out', version='0.4.0')
In [3]: tpm.head()
Out[3]:
salmon/1771-026-195-E4_salmon_out \
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
salmon/1771-026-190-E4_salmon_out \
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
salmon/1771-026-196-E4_salmon_out \
Name
ERCC-00158 0.000
ERCC-00154 906.236
ERCC-00150 0.000
ERCC-00143 0.000
ERCC-00142 0.000
salmon/1771-026-198-E4_salmon_out \
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
salmon/1771-023-118-E4_salmon_out \
Name
ERCC-00158 0.00000
ERCC-00154 9.35988
ERCC-00150 0.00000
ERCC-00143 724.44800
ERCC-00142 0.00000
salmon/1771-026-193-E4_salmon_out
Name
ERCC-00158 0.0
ERCC-00154 0.0
ERCC-00150 0.0
ERCC-00143 0.0
ERCC-00142 0.0
In [4]: sample_info = read_qcs('salmon/*_salmon_out', version='0.4.0', flen_lim=(10, 100))
In [5]: sample_info.head()
Out[5]:
percent_mapped num_processed \
salmon/1771-026-197-G4_salmon_out 71.8270 2665988.0
salmon/1771-026-198-D2_salmon_out 67.7853 3841894.0
salmon/1771-026-195-H7_salmon_out 73.4492 3875822.0
salmon/1771-026-194-E9_salmon_out 47.5425 979446.0
salmon/1771-026-195-E4_salmon_out 56.3955 5051277.0
global_fl_mode robust_fl_mode
salmon/1771-026-197-G4_salmon_out 103.0 103.0
salmon/1771-026-198-D2_salmon_out 122.0 122.0
salmon/1771-026-195-H7_salmon_out 110.0 110.0
salmon/1771-026-194-E9_salmon_out 111.0 111.0
salmon/1771-026-195-E4_salmon_out 111.0 111.0
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