This pipeline processes barcode counts sequenced from twelve fluorescence-activated cell sorting (FACS) samples of the synTCS-MutLib strain in the fumarate condition. Sequence data was generated using the Illumina NextSeq platform using paired-end sequencing read amplicons. Raw sequencing data was pre-processed on a high-performance computer using the Makefile script available in the project GitHub repository. Here, pre-processed barcode-count files for all twelve fumarate samples are merged, adjusted abundances are computed using the protocol from Biswas et al., (2021), and a median activation score- here, "median bin"- is calculated for each observed barcode. This analysis is replicated for the No Ligand and Aspartate samples.

This pipeline processes barcode-sequence-phenotype data previously generated in Merge_and_MEFL_Convert.Rmd and determines which multi-barcoded mutnts have significant differences between their fold-change scores.

This pipeline processes and visualizes barcode-sequence-phenotype data previously generated in Merge_and_MEFL_Convert.Rmd.

This pipeline processes barcode counts sequenced from twelve fluroescence-activated cell sorting (FACS) samples of the synTCS-MutLib strain in the aspartate condition. Sequence data was generated using the Illumina NextSeq platform using paired-end sequencing read amplicons. Raw sequencing data was pre-processed on a high-performance computer using the Makefile script available in the project GitHub repository. Here, pre-processed barcode-count files for all twelve aspartate samples are merged, adjusted abundances are computed using the protocol from Biswas et al., (2021), and a median activation score- here, "median bin"- is calculated for each observed barcode. This analysis is replicated for the No Ligand and Fumarate samples.

This pipeline processes barcode counts sequenced from twelve fluroescence-activated cell sorting (FACS) samples of the synTCS-MutLib strain in the no ligand condition. Sequence data was generated using the Illumina NextSeq platform using paired-end sequencing read amplicons. Raw sequencing data was pre-processed on a high-performance computer using the Makefile script available in the project GitHub repository. Here, pre-processed barcode-count files for all twelve no ligand samples are merged, adjusted abundances are computed using the protocol from Biswas et al., (2021), and a median activation score- here, "median bin"- is calculated for each observed barcode. This analysis is replicated for the Fumarate and Aspartate samples.

Mapa

logistic regression

esta ´padre

This pipeline processes barcode-sequence-phenotype data previously generated in Merge_and_MEFL_Convert.Rmd and determines positions which are significantly enriched for influencing aspartate responsiveness and specificity based on the total number of barcodes observed.