Designing and delivering bioinformatics project-based learning in East Africa.

BACKGROUND: The Eastern Africa Network for Bioinformatics Training (EANBiT) has matured through continuous evaluation, feedback, and codesign. We highlight how the program has evolved to meet challenges and achieve its goals and how experiential learning through mini projects enhances the acquisition of skills and collaboration. We continued to learn and grow through honest feedback and evaluation of the program, trainers, and modules, enabling us to provide robust training even during the Coronavirus disease 2019 (COVID-19) pandemic, when we had to redesign the program due to restricted travel and in person group meetings. RESULTS: In response to the pandemic, we developed a program to maintain "residential" training experiences and benefits remotely. We had to answer the following questions: What must change to still achieve the RT goals? What optimal platforms should be used? How would we manage connectivity and data challenges? How could we avoid online fatigue? Going virtual presented an opportunity to reflect on the essence and uniqueness of the program and its ability to meet the objective of strengthening bioinformatics skills among the cohorts of students using different delivery approaches. It allowed an increase in the number of participants. Evaluating each program component is critical for improvement, primarily when feedback feeds into the program's continuous amendment. Initially, the participants noted that there were too many modules, insufficient time, and a lack of hands-on training as a result of too much focus on theory. In the subsequent iterations, we reduced the number of modules from 27 to five, created a harmonized repository for the materials on GitHub, and introduced project-based learning through the mini projects. CONCLUSION: We demonstrate that implementing a program design through detailed monitoring and evaluation leads to success, especially when participants who are the best fit for the program are selected on an appropriate level of skills, motivation, and commitment.

A mentorship and incubation program using project-based learning to build a professional bioinformatics pipeline in Kenya.

The demand for well-trained bioinformaticians to support genomics research continues to rise. Unfortunately, undergraduate training in Kenya does not prepare students for specialization in bioinformatics. Graduates are often unaware of the career opportunities in bioinformatics, and those who are may lack mentors to help them choose a specialization. The Bioinformatics Mentorship and Incubation Program seeks to bridge the gap by laying the foundation for a bioinformatics training pipeline using project-based learning. The program selects six participants through an intensive open recruitment exercise for highly competitive students to join the program for four months. The six interns undergo intensive training within the first one and a half months before being assigned to mini-projects. We track the progress of the interns weekly through code review sessions and a final presentation at the end of the four months. We have trained five cohorts, most of whom have secured master's scholarships within and outside the country and job opportunities. We demonstrate the benefit of structured mentorship using project-based learning in filling the training gap after undergraduate programs to generate well-trained bioinformaticians who are competitive in graduate programs and bioinformatics jobs.

Genomic analysis reveals independent evolution of Plasmodium falciparum populations in Ethiopia.

BACKGROUND: Plasmodium falciparum parasite populations in Ethiopia have been experiencing local selective pressures from drugs and immunity, leading to evolutionary adaptation. However, there was a paucity of data on genomic characterization and evolutionary adaptations of P. falciparum isolates from the central area of Ethiopia. METHODS: Whole-genome analysis of 25 P. falciparum isolates from central Ethiopia, specifically from West Arsi, were studied to determine their genetic diversity, population structures, and signatures of selection in known drug resistance alleles against global isolates from Cambodia, Thailand, DR Congo, and Malawi. RESULTS: A total of 18,517 high-quality single-nucleotide polymorphisms (SNPs) were identified in Ethiopian P. falciparum isolates. About 84% of the Ethiopian P. falciparum isolates had a FWS value > 0.95 showing a dominant single genotype infection in most isolates at the time of collection with little potential for out-crossing as expected in areas with low transmission intensity. Within-host diversity of Ethiopian infections was significantly different from East African (p < 0.001), but not Southeast Asian infections (P > 0.05). A significant population structure has been observed by PCA and population differentiation between Ethiopian parasites and East African (Fst ~ 10%) and Southeast Asian populations (Fst ~ 18%), suggesting limited gene flow and the independent evolution of the Ethiopian parasite population. Moreover, a total of 125 genes under balancing selection was found that include ama1, trap, eba175, and lsa3, previously identified as targets of human host immunity. Recent directional selection analysis using integrated standardized haplotype score (IHS) did not detect any selection signatures in the Pfcrt, Pfdhfr, Pfdhps, Pfmdr1, and PfK13 genes. However, known drug resistance-conferring mutations analysis showed that at least one SNP marker was fixed in these genes, but not in Pfdhps and PfK13. CONCLUSION: Plasmodium falciparum populations in the central region of Ethiopia was structurally diverged from both Southeast Asian and other East African populations. Malaria infections in Ethiopia had low within-host diversity, and parasites carry fixed chloroquine resistance markers despite the withdrawal of this drug for the treatment of P. falciparum.

Community-based surveys for Plasmodium falciparum pfhrp2 and pfhrp3 gene deletions in selected regions of mainland Tanzania.

BACKGROUND: Histidine-rich protein 2 (HRP2)-based malaria rapid diagnostic tests (RDTs) are effective and widely used for the detection of wild-type Plasmodium falciparum infections. Although recent studies have reported false negative HRP2 RDT results due to pfhrp2 and pfhrp3 gene deletions in different countries, there is a paucity of data on the deletions of these genes in Tanzania. METHODS: A community-based cross-sectional survey was conducted between July and November 2017 in four regions: Geita, Kigoma, Mtwara and Ruvuma. All participants had microscopy and RDT performed in the field and provided a blood sample for laboratory multiplex antigen detection (for Plasmodium lactate dehydrogenase, aldolase, and P. falciparum HRP2). Samples showing RDT false negativity or aberrant relationship of HRP2 to pan-Plasmodium antigens were genotyped to detect the presence/absence of pfhrp2/3 genes. RESULTS: Of all samples screened by the multiplex antigen assay (n = 7543), 2417 (32.0%) were positive for any Plasmodium antigens while 5126 (68.0%) were negative for all antigens. The vast majority of the antigen positive samples contained HRP2 (2411, 99.8%), but 6 (0.2%) had only pLDH and/or aldolase without HRP2. Overall, 13 samples had an atypical relationship between a pan-Plasmodium antigen and HRP2, but were positive by PCR. An additional 16 samples with negative HRP2 RDT results but P. falciparum positive by microscopy were also chosen for pfhrp2/3 genotyping. The summation of false negative RDT results and laboratory antigen results provided 35 total samples with confirmed P. falciparum DNA for pfhrp2/3 genotyping. Of the 35 samples, 4 (11.4%) failed to consistently amplify positive control genes; pfmsp1 and pfmsp2 and were excluded from the analysis. The pfhrp2 and pfhrp3 genes were successfully amplified in the remaining 31 (88.6%) samples, confirming an absence of deletions in these genes. CONCLUSIONS: This study provides evidence that P. falciparum parasites in the study area have no deletions of both pfhrp2 and pfhrp3 genes. Although single gene deletions could have been missed by the multiplex antigen assay, the findings support the continued use of HRP2-based RDTs in Tanzania for routine malaria diagnosis. There is a need for the surveillance to monitor the status of pfhrp2 and/or pfhrp3 deletions in the future.

Compliance with follow-up and adherence to medication in hypertensive patients in an urban informal settlement in Kenya: comparison of three models of care.

OBJECTIVE: To determine and compare, among three models of care, compliance with scheduled clinic appointments and adherence to antihypertensive medication of patients in an informal settlement of Kibera, Kenya. METHODS: Routinely collected patient data were used from three health facilities, six walkway clinics and one weekend/church clinic. Patients were eligible if they had received hypertension care for more than 6 months. Compliance with clinic appointments and self-reported adherence to medication were determined from clinic records and compared using the chi-square test. Univariate and multivariate logistic regression models estimated the odds of overall adherence to medication. RESULTS: A total of 785 patients received hypertension treatment eligible for analysis, of whom two-thirds were women. Between them, there were 5879 clinic visits with an overall compliance with appointments of 63%. Compliance was high in the health facilities and walkway clinics, but men were more likely to attend the weekend/church clinics. Self-reported adherence to medication by those complying with scheduled clinic visits was 94%. Patients in the walkway clinics were two times more likely to adhere to antihypertensive medication than patients at the health facility (OR 1.97, 95% CI 1.25-3.10). CONCLUSION: Walkway clinics outperformed health facilities and weekend clinics. The use of multiple sites for the management of hypertensive patients led to good compliance with scheduled clinic visits and very good self-reported adherence to medication in a low-resource setting.

WiPFIM: A digital platform for interlinking biocollections of wild plants, fruits, associated insects, and their molecular barcodes.

The current knowledge on insects feeding on fruits is limited, and some of the scarce existing data on the fruit-associated insects are secluded within the host institutions. Consequently, their value is not fully realized. Moreover, in countries like Kenya, the integration of biocollections data within a digital framework has not been fully exploited. To address these gaps, this article presents a description of the development of a web-based platform for data sharing and integrating biodiversity historical data of wild plants, fruits, associated insects, and their molecular barcodes (WiPFIM) while leveraging data science technologies. The barcodes corresponding to the biocollections data were retrieved from BOLD database. The platform is an online resource about fruit-insect interactions that can be of interest to a worldwide community of users and can be useful in building innovative tools. The platform is accessible online at https://test-dmmg.icipe.org/wpfhi.

Multi-omics analyses reveal rumen microbes and secondary metabolites that are unique to livestock species.

Ruminant livestock, including cattle, sheep, goats, and camels, possess a distinctive digestive system with complex microbiota communities critical for feed conversion and secondary metabolite production, including greenhouse gases. Yet, there is limited knowledge regarding the diversity of rumen microbes and metabolites benefiting livestock physiology, productivity, climate impact, and defense mechanisms across ruminant species. In this study, we utilized metataxonomics and metabolomics data from four evolutionarily distinct livestock species, which had fed on diverse plant materials like grass, shrubs, and acacia trees, to uncover the unique signature microbes and secondary metabolites. We established the presence of a distinctive anaerobic fungus called Oontomyces in camels, while cattle exhibited a higher prevalence of unique microbes like Psychrobacter, Anaeromyces, Cyllamyces, and Orpinomyces. Goats hosted Cleistothelebolus, and Liebetanzomyces was unique to sheep. Furthermore, we identified a set of conserved core microbes, including Prevotella, Rickenellaceae, Cladosporium, and Pecoramyces, present in all the ruminants, irrespective of host genetics and dietary composition. This underscores their indispensable role in maintaining crucial physiological functions. Regarding secondary metabolites, camel's rumen is rich in organic acids, goat's rumen is rich in alcohols and hydrocarbons, sheep's rumen is rich in indoles, and cattle's rumen is rich in sesquiterpenes. Additionally, linalool propionate and terpinolene were uniquely found in sheep rumen, while valencene was exclusive to cattle. This may suggest the existence of species-specific microbes and metabolites that require host rumen-microbes' environment balance. These results have implications for manipulating the rumen environment to target specific microbes and secondary metabolite networks, thereby enhancing livestock productivity, resilience, reducing susceptibility to vectors, and environmentally preferred livestock husbandry.IMPORTANCERumen fermentation, which depends on feed components and rumen microbes, plays a crucial role in feed conversion and the production of various metabolites important for the physiological functions, health, and environmental smartness of ruminant livestock, in addition to providing food for humans. However, given the complexity and variation of the rumen ecosystem and feed of these various livestock species, combined with inter-individual differences between gut microbial communities, how they influence the rumen secondary metabolites remains elusive. Using metagenomics and metabolomics approaches, we show that each livestock species has a signature microbe(s) and secondary metabolites. These findings may contribute toward understanding the rumen ecosystem, microbiome and metabolite networks, which may provide a gateway to manipulating rumen ecosystem pathways toward making livestock production efficient, sustainable, and environmentally friendly.

Building awareness and capacity of bioinformatics and open science skills in Kenya: a sensitize, train, hack, and collaborate model.

We have applied the sensitize-train-hack-community model to build awareness of and capacity in bioinformatics in Kenya. Open science is the practice of science openly and collaboratively, with tools, techniques, and data freely shared to facilitate reuse and collaboration. Open science is not a mandatory curriculum course in schools, whereas bioinformatics is relatively new in some African regions. Open science tools can significantly enhance bioinformatics, leading to increased reproducibility. However, open science and bioinformatics skills, especially blended, are still lacking among students and researchers in resource-constrained regions. We note the need to be aware of the power of open science among the bioinformatics community and a clear strategy to learn bioinformatics and open science skills for use in research. Using the OpenScienceKE framework-Sensitize, Train, Hack, Collaborate/Community-the BOSS (Bioinformatics and Open Science Skills) virtual events built awareness and empowered researchers with the skills and tools in open science and bioinformatics. Sensitization was achieved through a symposium, training through a workshop and train-the-trainer program, hack through mini-projects, community through conferences, and continuous meet-ups. In this paper, we discuss how we applied the framework during the BOSS events and highlight lessons learnt in planning and executing the events and their impact on the outcome of each phase. We evaluate the impact of the events through anonymous surveys. We show that sensitizing and empowering researchers with the skills works best when the participants apply the skills to real-world problems: project-based learning. Furthermore, we have demonstrated how to implement virtual events in resource-constrained settings by providing Internet and equipment support to participants, thus improving accessibility and diversity.

Metatranscriptomic analysis of the gut microbiome of black soldier fly larvae reared on lignocellulose-rich fiber diets unveils key lignocellulolytic enzymes.

Recently, interest in the black soldier fly larvae (BSFL) gut microbiome has received increased attention primarily due to their role in waste bioconversion. However, there is a lack of information on the positive effect on the activities of the gut microbiomes and enzymes (CAZyme families) acting on lignocellulose. In this study, BSFL were subjected to lignocellulose-rich diets: chicken feed (CF), chicken manure (CM), brewers' spent grain (BSG), and water hyacinth (WH). The mRNA libraries were prepared, and RNA-Sequencing was conducted using the PCR-cDNA approach through the MinION sequencing platform. Our results demonstrated that BSFL reared on BSG and WH had the highest abundance of Bacteroides and Dysgonomonas. The presence of GH51 and GH43_16 enzyme families in the gut of BSFL with both α-L-arabinofuranosidases and exo-alpha-L-arabinofuranosidase 2 were common in the BSFL reared on the highly lignocellulosic WH and BSG diets. Gene clusters that encode hemicellulolytic arabinofuranosidases in the CAZy family GH51 were also identified. These findings provide novel insight into the shift of gut microbiomes and the potential role of BSFL in the bioconversion of various highly lignocellulosic diets to fermentable sugars for subsequent value-added products (bioethanol). Further research on the role of these enzymes to improve existing technologies and their biotechnological applications is crucial.

Antimicrobial Resistance and Virulence Characteristics of Klebsiella pneumoniae Isolates in Kenya by Whole-Genome Sequencing.

Klebsiella pneumoniae is a globally significant opportunistic pathogen causing healthcare-associated and community-acquired infections. This study examined the epidemiology and the distribution of resistance and virulence genes in clinical K. pneumoniae strains in Kenya. A total of 89 K. pneumoniae isolates were collected over six years from five counties in Kenya and were analyzed using whole-genome sequencing and bioinformatics. These isolates were obtained from community-acquired (62/89) and healthcare-associated infections (21/89), and from the hospital environment (6/89). Genetic analysis revealed the presence of blaNDM-1 and blaOXA-181 carbapenemase genes and the armA and rmtF genes known to confer pan-aminoglycoside resistance. The most abundant extended-spectrum beta-lactamase genes identified were blaCTX-M-15 (36/89), blaTEM (35/89), and blaOXA (18/89). In addition, one isolate had a mobile colistin resistance gene (mcr-8). Fluoroquinolone resistance-conferring mutations in gyrA and parC genes were also observed. The most notable virulence factors were those associated with hyper-virulence (rmpA/A2 and magA), yersiniabactin (ybt), salmochelin (iro), and aerobactin (iuc and iutA). A total of 38 distinct sequence types were identified, including known global lineages ST14, ST15, ST147, and ST307, and a regional clone ST17 implicated in regional outbreaks. In addition, this study genetically characterized two potential hypervirulent isolates and two community-acquired ST147 high-risk clones that contained carbapenemase genes, yersiniabactin, and other multidrug resistance genes. These results demonstrate that the resistome and virulome of Kenyan clinical and hospital environmental K. pneumoniae isolates are diverse. The reservoir of high-risk clones capable of spreading resistance, and virulence factors have the potential to cause unmanageable infection outbreaks with high morbidity and mortality.

Genetic Diversity, Distribution, and Genomic Characterization of Antibiotic Resistance and Virulence of Clinical Pseudomonas aeruginosa Strains in Kenya.

Pseudomonas aeruginosa is a leading cause of nosocomial infections worldwide. It can produce a range of debilitating infections, have a propensity for developing antimicrobial resistance, and present with a variety of potent virulence factors. This study investigated the sequence types (ST), phenotypic antimicrobial susceptibility profiles, and resistance and virulence genes among clinical isolates from urinary tract and skin and soft tissue infections. Fifty-six P. aeruginosa clinical isolates were obtained from six medical centers across five counties in Kenya between 2015 and 2020. Whole-genome sequencing (WGS) was performed to conduct genomic characterization, sequence typing, and phylogenetic analysis of the isolates. Results showed the presence of globally distributed high-risk clones (ST244 and ST357), local high-risk clones (ST2025, ST455, and ST233), and a novel multidrug-resistant (MDR) clone carrying virulence genes (ST3674). Furthermore, 31% of the study isolates were found to be MDR with phenotypic resistance to a variety of antibiotics, including piperacillin (79%), ticarcillin-clavulanic acid (57%), meropenem (34%), levofloxacin (70%), and cefepime (32%). Several resistance genes were identified, including carbapenemases VIM-6 (ST1203) and NDM-1 (ST357), fluoroquinolone genes, crpP, and qnrVCi, while 14 and 22 different chromosomal mutations were detected in the gyrA and parC genes, respectively. All isolates contained at least three virulence genes. Among the virulence genes identified, phzB1 was the most abundant (50/56, 89%). About 21% (12/56) of the isolates had the exoU+/exoS- genotype, while 73% (41/56) of the isolates had the exoS+/exoU- genotype. This study also discovered 12 novel lineages of P. aeruginosa, of which one (ST3674) demonstrated both extensive antimicrobial resistance and the highest number of virulence genes (236/242, 98%). Although most high-risk clones were detected in Nairobi County, high-risk and clones of interest were found throughout the country, indicating the local spread of global epidemic clones and the emergence of new strains. Thus, this study illustrates the urgent need for coordinated local, regional, and international antimicrobial resistance surveillance efforts.

The developmentally dynamic microRNA transcriptome of Glossina pallidipes tsetse flies, vectors of animal trypanosomiasis.

Summary: MicroRNAs (miRNAs) are single stranded gene regulators of 18-25 bp in length. They play a crucial role in regulating several biological processes in insects. However, the functions of miRNA in Glossina pallidipes, one of the biological vectors of African animal trypanosomosis in sub-Saharan Africa, remain poorly characterized. We used a combination of both molecular biology and bioinformatics techniques to identify miRNA genes at different developmental stages (larvae, pupae, teneral and reproductive unmated adults, gravid females) and sexes of G. pallidipes. We identified 157 mature miRNA genes, including 12 novel miRNAs unique to G. pallidipes. Moreover, we identified 93 miRNA genes that were differentially expressed by sex and/or in specific developmental stages. By combining both miRanda and RNAhybrid algorithms, we identified 5550 of their target genes. Further analyses with the Gene Ontology term and KEGG pathways for these predicted target genes suggested that the miRNAs may be involved in key developmental biological processes. Our results provide the first repository of G. pallidipes miRNAs across developmental stages, some of which appear to play crucial roles in tsetse fly development. Hence, our findings provide a better understanding of tsetse biology and a baseline for exploring miRNA genes in tsetse flies. Availability and implementation: Raw sequence data are available from NCBI Sequence Read Archives (SRA) under Bioproject accession number PRJNA590626. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Enrichment approach for unbiased sequencing of respiratory syncytial virus directly from clinical samples.

Background: Nasopharyngeal samples contain higher quantities of bacterial and host nucleic acids relative to viruses; presenting challenges during virus metagenomics sequencing, which underpins agnostic sequencing protocols. We aimed to develop a viral enrichment protocol for unbiased whole-genome sequencing of respiratory syncytial virus (RSV) from nasopharyngeal samples using the Oxford Nanopore Technology (ONT) MinION platform. Methods: We assessed two protocols using RSV positive samples. Protocol 1 involved physical pre-treatment of samples by centrifugal processing before RNA extraction, while Protocol 2 entailed direct RNA extraction without prior enrichment. Concentrates from Protocol 1 and RNA extracts from Protocol 2 were each divided into two fractions; one was DNase treated while the other was not. RNA was then extracted from both concentrate fractions per sample and RNA from both protocols converted to cDNA, which was then amplified using the tagged Endoh primers through Sequence-Independent Single-Primer Amplification (SISPA) approach, a library prepared, and sequencing done. Statistical significance during analysis was tested using the Wilcoxon signed-rank test. Results: DNase-treated fractions from both protocols recorded significantly reduced host and bacterial contamination unlike the untreated fractions (in each protocol p<0.01). Additionally, DNase treatment after RNA extraction (Protocol 2) enhanced host and bacterial read reduction compared to when done before (Protocol 1). However, neither protocol yielded whole RSV genomes. Sequenced reads mapped to parts of the nucleoprotein (N gene) and polymerase complex (L gene) from Protocol 1 and 2, respectively. Conclusions: DNase treatment was most effective in reducing host and bacterial contamination, but its effectiveness improved if done after RNA extraction than before. We attribute the incomplete genome segments to amplification biases resulting from the use of short length random sequence (6 bases) in tagged Endoh primers. Increasing the length of the random nucleotides from six hexamers to nine or 12 in future studies may reduce the coverage biases.

Open Science in Kenya: Where Are We?

According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident - the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20-50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign toward open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.

Transcription factor motif quality assessment requires systematic comparative analysis.

Transcription factor (TF) binding site prediction remains a challenge in gene regulatory research due to degeneracy and potential variability in binding sites in the genome. Dozens of algorithms designed to learn binding models (motifs) have generated many motifs available in research papers with a subset making it to databases like JASPAR, UniPROBE and Transfac. The presence of many versions of motifs from the various databases for a single TF and the lack of a standardized assessment technique makes it difficult for biologists to make an appropriate choice of binding model and for algorithm developers to benchmark, test and improve on their models. In this study, we review and evaluate the approaches in use, highlight differences and demonstrate the difficulty of defining a standardized motif assessment approach. We review scoring functions, motif length, test data and the type of performance metrics used in prior studies as some of the factors that influence the outcome of a motif assessment. We show that the scoring functions and statistics used in motif assessment influence ranking of motifs in a TF-specific manner. We also show that TF binding specificity can vary by source of genomic binding data. Finally, we demonstrate that information content of a motif is not in isolation a measure of motif quality but is influenced by TF binding behaviour. We conclude that there is a need for an easy-to-use tool that presents all available evidence for a comparative analysis.