a bioinformatician and a programmer, working on problems
of various difficulties, be it file processing automation or gene
expression modeling. I specialize in processing and analyzing
Next-Generation Sequencing (NGS) data, such as RNA-seq. My expertise
extends to Linux server administration, web application development,
Excel automation, Raspberry Pi projects, and more!
If you face a challenge which requires a blend of technical expertise and biological
insight, or you need an assistance in IT-related areas, do not hesitate to contact me.
Open source projects
xcore
an R package for inference of gene expression regulators
xcore is an R package for transcription factor activity modeling
based on known molecular signatures and user's gene expression
data. Accompanying xcoredata package provides a collection of
molecular signatures, constructed from publicly available
ChiP-seq experiments.
sumsamstats
Parser and tools for summarising outputs of samtools stats, with ATAC-seq in mind.
Shipped together with a Shiny application to help visualize the outputs.
RNA-seq data analysis for biologists
RNA-seq workshop covering one of the simplest data analysis workflows,
starting with data download and finishing at differential expression calling.
Wheather station
Mini-project weather station build around BME280 sensor using ESP32
and E-Ink display.
midasHLA
Meaningful Immunogenetic Data at Scale
midasHLA is an R package for statistical analysis of human
immunogenetic variation in the form of HLA and KIR types.
The package enables association analysis and using immunogenetic
data transformation functions for HLA amino acid fine mapping,
analysis of HLA evolutionary divergence as well as HLA-KIR
interactions. midasHLA closes the gap between inference of immunogenetic
variation and its efficient utilization to make meaningful discoveries.
ATAC-seq pipeline
Data analysis pipeline implemented in Nextflow. It starts with the raw FASTQ files
and outputs peaks denoting nucleosome free regions toghether with count quantification.
The pipeline supports peak calling using information from multiple replicates.
shiitake
Mini-project, automatizing Shiitake mushrooms growth monitoring
using Raspberry Pi and Raspberry Pi Camera.
JavaScript FASTA format validator
Publications
Migdał, M., Arakawa, T., Takizawa, S., Furuno, M., Suzuki, H., Arner, E., Winata, C.L., Kaczkowski, B. xcore: an R package for inference of gene expression regulators. BMC Bioinformatics. 2023. 24:14. doi: https://doi.org/10.1186/s12859-022-05084-0Uszczynska-Ratajczak, B., Sugunan, S., Kwiatkowska, M., Migdal, M., Carbonell-Sala, S., Sokol, A., Winata, C.L., Chacinska, A. Profiling subcellular localization of nuclear-encoded mitochondrial gene products in zebrafish. Life Sci. Alliance. 2022. 6:e202201514. doi: https://doi.org/10.26508/lsa.202201514Migdał, M., Tralle, E., Abu Nahia, K., Bugajski, Ł., Kędzierska, K.Z., Garbicz, F., Piwocka, K., Winata, C.L., Pawlak, M. Multi-omics analyses of early liver injury reveals cell-type-specific transcriptional and epigenomic shift. BMC Genomics. 2021. 22:904. doi: https://doi.org/10.1186/s12864-021-08173-1Abu Nahia, K., Migdał, M., Quinn, T.A., Poon, K., Łapiński, M., Sulej, A., Liu, J., Mondal, S.S., Pawlak, M., Bugajski, Ł., Piwocka, K., Brand, T., Kohl, P., Korzh, V., Winata, C. Genomic and physiological analyses of the zebrafish atrioventricular canal reveal molecular building blocks of the secondary pacemaker region. Cell. Mol. Life Sci.. 2021. 78:6669-6687. doi: https://doi.org/10.1007/s00018-021-03939-yMigdal, M., Ruan, D.F., Forrest, W.F., Horowitz, A., Hammer, C. MiDAS—Meaningful Immunogenetic Data at Scale. PLoS Comput Biol. 2021. 17:e1009131. doi: https://doi.org/10.1371/journal.pcbi.1009131 Chen, J., Madireddi, S., Nagarkar, D., Migdał, M., et al. In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales. Briefings in Bioinformatics. 2021. doi: 10.1093/bib/bbaa223.Pawlak, M., Kedzierska, K.Z., Migdal, M., Nahia, K.A., Ramilowski, J.A., Bugajski, L., Hashimoto, K., Marconi, A., Piwocka, K., Carninci, P., Winata, C.L. Dynamics of cardiomyocyte transcriptome and chromatin landscape demarcates key events of heart development. Genome Res.. 2019. 29:506-519. doi: https://doi.org/10.1101/gr.244491.118
