This is a collection of scripts associated with the re-analysis of a pitaya RNA-Seq dataset. Results of this analysis can be found here. These scripts were developed for use with Python 2.7.
python contig_stats.py
--input <FILENAME>
optional:
--min_contig_len <INTEGER> [500]
--out <FULL_PATH_TO_OUTPUT_DIRECTORY>
--exp <EXPRESSION_FILE(normalized)>
--input specifies a (multiple) FASTA file which contains the contigs of an assembly or any other collection of sequences. Statistics will be calculated for these sequences under the assumption that it is an assembly.
--min_contig_len specifies a cutoff to exclude shorter contigs. A new FASTA file will be generated which contains only sequences passing this filter. Default value is 500bp.
--out specifies an output folder where all the generated files will be placed.
--exp specifies a text file which contains normalized expression data (e.g. TPMs, RPKMs, FPKMs). These values are used to calculate ExNx statistics like E90N50. Therefore, it is crucial that the sequence names in this file match the sequence names in the provided FASTA file.
This version is based on previously developed scripts (1, 2).
python calculate_RPKMs.py
--counts <COUNT_TABLE>
--rpkm <RPKM_FILE>
--assembly <ASSEMBLY_FILE>
--counts this text file contains the raw counts in a matrix with samples in columns and sequences (transcripts/genes) in rows.
--rpkm this text file is the output. The layout matches the input file, but all values are normalized based on sequencing depth and sequence length (RPKMs).
--assembly this FASTA file contains the sequences mentioned in the expression data file. Lengths of these transcript sequences will be used to calculate RPKM values.
The scripts pitaya_MYB_exp_plots_summary.py and pitaya_exp_plots_summary_tissue.py contain dataset specific elements of the datasets reanalyzed in Pucker et al., 2021. These scripts are included for documentation purposes and should not be used on other datasets without adjustments.
python pitaya_exp_plots_summary.py
--genes <GENES_FILE>
--exp <EXPRESSION_FILE>
--out <FIGURE_OUTPUT_FILE>
--genes this text file has two TAB-separated columns. The first column specifies a display name for the transcript/gene. The second column is a single sequence ID or a comma-separated list of sequence IDs which are used to connect transcript abundance values to the display name.
--exp this file contains the transcript abundance values as described above. Normalized data (TPMs, RPKMs) should be used for the construction of figures.
--out specifies the figure output file. The file extension specifies the file type (e.g. PNG, JPG, PDF, SVG).
The scripts pitaya2_exp_plots_summary.py and pitaya2_exp_plots_summary.py contain dataset specific elements of the datasets reanalyzed in Pucker & Brockington, 2022. The usage of these scripts is equivalent to pitaya_exp_plots_summary_tissue.py.
Pucker B. & Brockington S.F. (2022). The evidence for anthocyanins in the betalain-pigmented genus Hylocereus is weak. bioRxiv 2021.11.16.468878; doi: 10.1101/2021.11.16.468878.
Pucker B., Singh H.B., Kumari M., Khan M.I., Brockington S.F. (2021) The report of anthocyanins in the betalain-pigmented genus Hylocereus is not well evidenced and is not a strong basis to refute the mutual exclusion paradigm. BMC Plant Biology 21(1): 297. doi:10.1186/s12870-021-03080-9.
Pucker B. and Brockington S. (2020). Pitaya transcriptome assemblies and investigation of transcript abundances. Bielefeld University. doi: 10.4119/unibi/2946374.
Haak, M., Vinke, S., Keller, W., Droste, J., Rückert, C., Kalinowski, J., & Pucker, B. (2018). High Quality de novo Transcriptome Assembly of Croton tiglium. Frontiers in Molecular Biosciences, 5. doi:10.3389/fmolb.2018.00062.
Pucker, B., Holtgräwe, D., Rosleff Sörensen, T., Stracke, R., Viehöver, P., and Weisshaar, B. (2016). A de novo Genome Sequence Assembly of the Arabidopsis thaliana Accession Niederzenz-1 Displays Presence/Absence Variation and Strong Synteny. PloS-ONE 11:e0164321. doi:10.1371/journal.pone.0164321.